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BACKGROUND: Cerebral small vessel disease (CSVD) is a group of neurological disorders that affect the small blood vessels within the brain, for which no effective treatments are currently available. We conducted a Mendelian randomization (MR) study to identify candidate therapeutic genes for CSVD. METHODS: We retrieved genome-wide association study data from 6 recently conducted, extensive investigations focusing on CSVD magnetic resonance imaging markers and performed a 2-sample MR analysis to assess the potential causal effects of gene expression and protein level within druggable genes on CSVD in blood and brain tissues. Colocalization analyses and repeat studies were undertaken to verify the relationship. Additionally, mediation analysis was conducted to explore the potential mechanisms involving druggable genes and known risk factors for CSVD. Finally, phenome-wide MR analyses were applied to evaluate the potential adverse effects related to the identified druggable genes for CSVD treatment. RESULTS: Overall, 5 druggable genes consistently showed associations with CSVD in MR analyses across both the discovery and validation cohorts. Notably, the ALDH2 and KLHL24 genes were identified as associated with CSVD in both blood and brain tissues, whereas the genes ADRB1, BTN3A2, and EFEMP1 were exclusively detected in brain tissue. Moreover, mediation analysis elucidated the proportion of the total effects mediated by CSVD risk factors through candidate druggable genes, which ranged from 5.5% to 18.5%, and offered potential explanations for the observed results. A comprehensive phenome-wide MR analysis further emphasized both the therapeutic benefits and potential side effects of targeting these candidate druggable genes. CONCLUSIONS: This study provides genetic evidence supporting the potential therapeutic benefits of targeting druggable genes for treating CSVD, which will be useful for prioritizing CSVD drug development.
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BACKGROUND: Mesenteric lymphadenitis (ML) demonstrates a distinctive inclination for the pediatric and adolescent demographic and the diagnosis of ML in young children poses a substantial challenge. OBJECTIVE: This prospective study aimed to assess the diagnostic efficacy of Superb Microvascular Imaging (SMI) and Virtual Touch Tissue Imaging quantification (VTIQ) in distinguishing pediatric mesenteric lymphadentitis. METHODS: We examined 82 mesentric lymph node (MLN) in pediatric patients with mesenteric lymphadentitis and 50 MLN in a healthy group. SMI was utilized to evaluate vascularity within the MLN, while MLN stiffness, quantified as shear wave velocity (SWV) in meters per second (m/s), was assessed using VTIQ. We compared the diagnostic performance of greyscale Ultrasound, US combined with SMI, US combined with VTIQ, and US combined with both SMI and VTIQ. RESULTS: SMI revealed a significant distinction between mesenteric lymphadentitis and normal MLN (pâ< â0.001). MLN affected by mesenteric lymphadentis exhibited increased vascularity (marked vascularity: 13/82, 15.85%) compared to normal MLN (marked vascularity: 1/50, 2.00%). Statistically significant differences were observed in SWV values beween mesenteric lymphadentitis and normal MLN (all p-values <0.001). The mean and minimum SWV values for MLN with mesenteric lymphadentitis were 1.66±0.77âm/s and 1.51±0.53âm/s, respectively. Control group SWV values were approximately three times higher than those in the mesenteric lymphadenitis group. The highest area under the curve values were achieved with the combination of all three modalities (0.837, 95% confidence interval: 0.763- 0.896), followed by US + VTIQ (0.795, 0.716- 0.860), US + SMI (0.753, 0.670- 0.824) and US alone (0.642, 0.554- 0.724). CONCLUSION: SMI and VTIQ offer a promising noninvasive adjunct to grayscale ultrasound for identifying mesenteric lymphadentitis in pediatric patients.
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Brain glymphatic dysfunction is critical in neurodegenerative processes. While animal studies have provided substantial insights, understandings in humans remains limited. Recent attention has focused on the non-invasive evaluation of brain glymphatic function. However, its association with brain parenchymal lesions in large-scale population remains under-investigated. In this cross-sectional analysis of 1030 participants (57.14 ± 9.34 years, 37.18% males) from the Shunyi cohort, we developed an automated pipeline to calculate diffusion-weighted image analysis along the perivascular space (ALPS), with a lower ALPS value indicating worse glymphatic function. The automated ALPS showed high consistency with the manual calculation of this index (ICC = 0.81, 95% CI: 0.662-0.898). We found that those with older age and male sex had lower automated ALPS values (ß = -0.051, SE = 0.004, p < .001, per 10 years, and ß = -0.036, SE = 0.008, p < .001, respectively). White matter hyperintensity (ß = -2.458, SE = 0.175, p < .001) and presence of lacunes (OR = 0.004, 95% CI < 0.002-0.016, p < .001) were significantly correlated with decreased ALPS. The brain parenchymal and hippocampal fractions were significantly associated with decreased ALPS (ß = 0.067, SE = 0.007, p < .001 and ß = 0.040, SE = 0.014, p = .006, respectively) independent of white matter hyperintensity. Our research implies that the automated ALPS index is potentially a valuable imaging marker for the glymphatic system, deepening our understanding of glymphatic dysfunction.
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Imagen de Difusión por Resonancia Magnética , Sistema Glinfático , Humanos , Masculino , Femenino , Sistema Glinfático/diagnóstico por imagen , Sistema Glinfático/patología , Sistema Glinfático/fisiopatología , Persona de Mediana Edad , Estudios Transversales , Anciano , Imagen de Difusión por Resonancia Magnética/métodos , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/patología , Procesamiento de Imagen Asistido por Computador/métodos , Adulto , Estudios de CohortesRESUMEN
Alzheimer's disease (AD) is a complex pathophysiological disease. Allowing for heterogeneity, not only in disease manifestations but also in different progression patterns, is critical for developing effective disease models that can be used in clinical and research settings. We introduce a machine learning model for identifying underlying patterns in Alzheimer's disease (AD) trajectory using longitudinal multi-modal data from the ADNI cohort and the AIBL cohort. Ten biologically and clinically meaningful disease-related states were identified from data, which constitute three non-overlapping stages (i.e., neocortical atrophy [NCA], medial temporal atrophy [MTA], and whole brain atrophy [WBA]) and two distinct disease progression patterns (i.e., NCA â WBA and MTA â WBA). The index of disease-related states provided a remarkable performance in predicting the time to conversion to AD dementia (C-Index: 0.923 ± 0.007). Our model shows potential for promoting the understanding of heterogeneous disease progression and early predicting the conversion time to AD dementia.
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The present retrospective study was designed to explore the value of conventional ultrasound (US) and Virtual Touch Tissue Imaging and Quantification (VTIQ) in the assessment of mesenteric lymphadenitis (ML) in a paediatric population. A total of 103 patients with ML and 60 healthy paediatric patients were examined. VTIQ was performed to assess mesenteric lymph node (MLN) stiffness via shear-wave velocity (SWV). Univariate and multivariate logistic regression analyses were conducted to reveal independent variables for the identification of ML. The diagnostic performance of US, and US combined with VTIQ, were compared. All the quantitative VTIQ parameters (including the SWVMean, SWVMax and SWVMin) were significantly greater for MLNs in the control group than for MLNs in the ML group (all P<0.001). The SWV values in the control group were nearly 2-fold greater than that in the ML group. According to the multivariate logistic regression analysis, the longest diameter [odds ratio (OR)=6.042; P=0.046] was revealed to be the strongest independent predictor for ML, followed by the CRP level (OR=2.310; P<0.001) and the SWVMean (OR=0.106; P<0.001). According to the receiver operating characteristic analysis, the area under the curve (AUC) for US combined with VTIQ was 0.890 (95% CI: 0.831-0.949) with a greater sensitivity of 91.26% and a greater specificity of 86.67% than that for US alone (AUC: 0.798; 95% CI: 0.724-0.872; sensitivity: 79.61%; specificity: 80.00%). A significant negative correlation between increased VTIQ parameters and ML was observed. Utilizing VTIQ to assess MLN stiffness offers a non-invasive, convenient, reliable and reproducible approach for identifying mesenteric lymphadenopathy.
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BACKGROUND: This study aims to investigate the temporal and spatial patterns of structural brain injury related to deep medullary veins (DMVs) damage. METHODS AND RESULTS: This is a longitudinal analysis of the population-based Shunyi cohort study. Baseline DMVs numbers were identified on susceptibility-weighted imaging. We assessed vertex-wise cortex maps and diffusion maps at both baseline and follow-up using FSL software and the longitudinal FreeSurfer analysis suite. We performed statistical analysis of global measurements and voxel/vertex-wise analysis to explore the relationship between DMVs number and brain structural measurements. A total of 977 participants were included in the baseline, of whom 544 completed the follow-up magnetic resonance imaging (age 54.97±7.83 years, 32% men, mean interval 5.56±0.47 years). A lower number of DMVs was associated with a faster disruption of white matter microstructural integrity, presented by increased mean diffusivity and radial diffusion (ß=0.0001 and SE=0.0001 for both, P=0.04 and 0.03, respectively), in extensive deep white matter (threshold-free cluster enhancement P<0.05, adjusted for age and sex). Of particular interest, we found a bidirectional trend association between DMVs number and change in brain volumes. Specifically, participants with mild DMVs disruption showed greater cortical enlargement, whereas those with severe disruption exhibited more significant brain atrophy, primarily involving clusters in the frontal and parietal lobes (multiple comparison corrected P<0.05, adjusted for age, sex, and total intracranial volume). CONCLUSIONS: Our findings posed the dynamic pattern of brain parenchymal lesions related to DMVs injury, shedding light on the interactions and chronological roles of various pathological mechanisms.
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Venas Cerebrales , Humanos , Masculino , Femenino , Persona de Mediana Edad , Venas Cerebrales/diagnóstico por imagen , Venas Cerebrales/patología , Estudios Longitudinales , China/epidemiología , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/patología , Adulto , AncianoRESUMEN
BACKGROUND: It is uncertain whether rare NOTCH3 variants are associated with stroke and dementia in the general population and whether they lead to alterations in cognitive function. This study aims to determine the associations of rare NOTCH3 variants with prevalent and incident stroke and dementia, as well as cognitive function changes. METHODS AND RESULTS: In the prospective community-based Shunyi Study, a total of 1007 participants were included in the baseline analysis. For the follow-up analysis, 1007 participants were included in the stroke analysis, and 870 participants in the dementia analysis. All participants underwent baseline brain magnetic resonance imaging, carotid ultrasound, and whole exome sequencing. Rare NOTCH3 variants were defined as variants with minor allele frequency <1%. A total of 137 rare NOTCH3 carriers were enrolled in the baseline study. At baseline, rare NOTCH3 variant carriers had higher rates of stroke (8.8% versus 5.6%) and dementia (2.9% versus 0.8%) compared with noncarriers. After adjustment for associated risk factors, the epidermal growth factor-like repeats (EGFr)-involving rare NOTCH3 variants were associated with a higher risk of prevalent stroke (odds ratio [OR], 2.697 [95% CI, 1.266-5.745]; P=0.040) and dementia (OR, 8.498 [95% CI, 1.727-41.812]; P=0.032). After 5 years of follow-up, we did not find that the rare NOTCH3 variants increased the risk of incident stroke and dementia. There was no statistical difference in the change in longitudinal cognitive scale scores. CONCLUSIONS: Rare NOTCH3 EGFr-involving variants are genetic risk factors for stroke and dementia in the general Chinese population.
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Demencia , Accidente Cerebrovascular , Humanos , Estudios Prospectivos , Accidente Cerebrovascular/epidemiología , Accidente Cerebrovascular/genética , Accidente Cerebrovascular/patología , Encéfalo/patología , Imagen por Resonancia Magnética , Demencia/epidemiología , Demencia/genética , Receptores ErbB , Receptor Notch3/genéticaRESUMEN
Background: As either oncogenes or tumor suppressor genes, long non-coding RNAs (lncRNAs) have a major role in both tumorigenesis and progression of human cancers, including breast cancer (BC). However, the statistical correlation between the lncRNA-lncRNA interaction and prognosis of BC remains unclear. Methods: We analyzed the fragments per kilobase per million (FPKM) lncRNA expression data in tumor tissue samples from 890 female patients with BC in The Cancer Genome Atlas (TCGA) between May 2021 and October 2022. The Cox proportional hazards model adjusted for age, race, clinical stage, neoadjuvant therapy, estrogen receptor (ER), and progesterone receptor (PR) was adopted to evaluate the lncRNA-lncRNA interaction regarding overall survival (OS) of BC. The multiple comparison was corrected by Bonferroni method. Results: RP11-10E18.7×RP11-481C4.2 was significantly associated with OS of BC patients [hazard ratio (HR)interaction =1.04, 95% confidence interval (CI): 1.03-1.06, P=3.35×10-9]. Then, gene-gene interaction analysis was performed for genes co-expressed with lncRNAs. FOXA1×U2SURP (HRinteraction =1.49, 95% CI: 1.28-1.73, P=2.16×10-7) was found to have a similar interactive pattern to RP11-10E18.7×RP11-481C4.2. after classifying the patients by intersection (3.47), we observed that the effect of FOXA1 opposite in patients with different U2SURP expression level (HRhigh vs. low =0.58, 95% CI: 0.34-0.99, P=0.046 in low expression of U2SURP; HRhigh vs. low =1.56, 95% CI: 1.18-2.87, P=0.029 in high expression of U2SURP). Conclusions: Our comprehensive study identified RP11-10E18.7×RP11-481C4.2 as a potential biomarker of BC prognosis. The results play an essential role in the impact of lncRNA-lncRNA interaction on BC survival. Our findings elucidated potential molecular mechanisms of BC progression under complex association patterns and provided potential dynamic and reversible therapeutic targets for BC patients.
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Background: Alzheimer's disease (AD) is a heterogeneously progressive neurodegeneration disorder with varied rates of deterioration, either between subjects or within different stages of a certain subject. Estimating the course of AD at early stages has treatment implications. We aimed to analyze disease progression to identify distinct patterns in AD trajectory. Methods: We proposed a deep learning model to identify underlying patterns in the trajectory from cognitively normal (CN) to a state of mild cognitive impairment (MCI) to AD dementia, by jointly predicting time-to-conversion and clustering out distinct subgroups characterized by comprehensive features as well as varied progression rates. We designed and validated our model on the ADNI dataset (1370 participants). Prediction of time-to-conversion in AD trajectory was used to validate the expression of the identified patterns. Causality between patterns and time-to-conversion was further inferred using Mendelian randomization (MR) analysis. External validation was performed on the AIBL dataset (233 participants). Findings: The proposed model clustered out patterns characterized by significantly different biomarkers and varied progression rates. The discovered patterns also showed a strong prediction ability, as indicated by hazard ratio (CNâMCI, HR = 3.51, p < 0.001; MCIâAD, HR = 8.11, p < 0.001), C-Index (CNâMCI, 0.618; MCIâAD, 0.718), and AUC (CNâMCI, 3 years 0.802, 5 years 0.876; MCIâAD, 3 years 0.914, 5 years 0.957). In the external validation cohort, our model demonstrated competitive performance on conversion time prediction (CNâMCI, C-Index = 0.693; MCIâAD, C-Index = 0.752). Moreover, suggestive associations between CNâMCI/MCIâAD patterns with four/three SNPs were mediated and MR analysis indicated a causal link between MCIâAD patterns and time-to-conversion in the first three years. Interpretation: Our proposed model identifies biologically and clinically meaningful patterns from real-world data and provides promising performance on time-to-conversion prediction in AD trajectory, which could promote the understanding of disease progression, facilitate clinical trial design, and provide potential for decision-making. Funding: The National Key Research and Development Program of China, the Key R&D Program of Zhejiang, and the National Nature Science Foundation of China.
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BACKGROUND AND OBJECTIVES: Previous studies reported that carriers of rare NOTCH3 variants comprised more than 10% of the general population and are susceptible to a heavy overall burden of cerebral small vessel disease while the injury patterns remain uncovered. This study aimed to investigate the imaging features in relation to rare NOTCH3 variants and the interaction between cortical atrophy and white matter lesions from a longitudinal view, with respect to spatial and dynamic patterns. METHODS: As part of a community-based cohort, we included participants with complete whole-exome sequencing and brain MRI in the baseline analysis. All participants were invited for a 5-year follow-up MRI, and those who did not complete the follow-up were excluded from the longitudinal analysis. NOTCH3 variants with minor allele frequency <1% in all 4 public population databases were defined as rare variants. We used general linear models to compare the volume of white matter hyperintensity (WMH) volume and brain parenchymal fraction between rare NOTCH3 variant carriers and noncarriers. In addition, we compared the WMH probability map and vertex-wise cortex maps at a voxel/vertex-wise level. RESULTS: A total of 1,054 participants were included in baseline analysis (13.56% carried rare NOTCH3 variants), among whom 661 had a follow-up brain MRI (13.76% carried rare NOTCH3 variants). Rare NOTCH3 variant carriers had a heavier white matter hyperintensity burden (1.65 vs 0.85 mL, p = 0.025) and had more extensive WMH distributed in the periventricular areas. We also found that rare NOTCH3 variant carriers were susceptible to worse cortical atrophy (ß = -0.004, SE = 0.002, p = 0.057, adjusted for age and sex). Cortical atrophy of multiple regions in the frontal and parietal lobes was related to white matter hyperintensity progression. DISCUSSION: Individuals with rare NOTCH3 variants have a distinct pattern of brain parenchymal damage related to CSVD. Our findings uncover the important genetic predisposition in age-related cerebral small vessel disease in the general population.
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Lesiones Encefálicas , Enfermedades de los Pequeños Vasos Cerebrales , Sustancia Blanca , Humanos , Enfermedades de los Pequeños Vasos Cerebrales/diagnóstico por imagen , Enfermedades de los Pequeños Vasos Cerebrales/genética , Enfermedades de los Pequeños Vasos Cerebrales/patología , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Imagen por Resonancia Magnética/métodos , Neuroimagen , Lesiones Encefálicas/patología , Atrofia/patología , Sustancia Blanca/diagnóstico por imagen , Sustancia Blanca/patología , Receptor Notch3/genéticaRESUMEN
Cerebral venous abnormalities, distinct from traditional arterial diseases, have been linked to brain atrophy in a previous community-based cohort study, specifically in relation to the reduction of deep medullary veins (r-DMVs). To better understand the properties and biological functions of serum extracellular vesicles (EVs) in cerebral venous disease-associated brain atrophy, EVs are extracted from the serum of both participants with r-DMV and normal controls and analyzed their proteomic profiles using Tandem Mass Tag label quantitation analysis. Phenotypic experiments showed that EVs from individuals with r-DMVs are able to disrupt the normal functions of neurons, endothelial cells, and smooth muscle cells, and induce A1 reactive astrocytes. Additionally, this study provided a comprehensive characterization of the proteomic profile of DMV EVs and found that the collagen hydroxyproline is upregulated, while complement C3 is downregulated in the r-DMV group, suggesting that r-DMV may not be a simple pathological phenomenon and highlighting the potential involvement of EVs in the progression of brain atrophy in r-DMVs which has implications for the development of future therapeutic strategies.
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Encefalopatías , Vesículas Extracelulares , Enfermedades Neurodegenerativas , Humanos , Células Endoteliales , Proteómica , Estudios de Cohortes , Encéfalo , Vesículas Extracelulares/fisiología , AtrofiaRESUMEN
BACKGROUND: The mechanism of gait disorder in patients with cerebral small vessel disease (CSVD) remains unclear. Limited studies have compared the effect of cerebral microbleeds (CMBs) and lacunes on gait disturbance in CSVD patients in different anatomical locations. OBJECTIVE: To investigate the relationship of quantitative gait parameters with varied anatomically located MRI imaging markers in patients with CSVD. METHODS: Quantitative gait tests were performed on 127 symptomatic CSVD patients all with diffuse distributed white matter hyperintensities (WMHs). CMBs and lacunes in regard to anatomical locations and burdens were measured. The correlation between CSVD imaging markers and gait parameters was evaluated using general linear model analysis. RESULTS: Presence of CMBs was significantly associated with stride length (ß=â-0.098, pâ=â0.0272) and right step length (ß=â-0.054, pâ=â0.0206). Presence of CMBs in basal ganglia (BG) was significantly associated with stride length and step length. Presence of CMBs in brainstem was significantly associated with gait parameters including stride length, step length, step height, and step width. Presence of lacunes in brainstem was significantly associated with gait speed (ß=â-0.197, pâ=â0.0365). However, presence of lacunes in the other areas was not associated with worse gait performances. CONCLUSION: BG and brain stem located CMBs contributed to gait impairment in symptomatic CSVD patients.
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Hemorragia Cerebral , Enfermedades de los Pequeños Vasos Cerebrales , Humanos , Hemorragia Cerebral/complicaciones , Ganglios Basales/diagnóstico por imagen , Imagen por Resonancia Magnética/métodos , Enfermedades de los Pequeños Vasos Cerebrales/complicaciones , Enfermedades de los Pequeños Vasos Cerebrales/diagnóstico por imagen , Tronco Encefálico/diagnóstico por imagenRESUMEN
Objective: Further studies are needed to improve the understanding of the pathological process underlying cognitive impairments. The purpose of this study is to investigate the global and topographic changes of white matter integrity and cortical structure related to cognitive impairments in a community-based population. Methods: A cross-sectional analysis was performed based on 995 subjects (aged 56.8 ± 9.1 years, 34.8% males) from the Shunyi study, a community-dwelling cohort. Cognitive status was accessed by a series of neurocognitive tests including Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), category Verbal Fluency Test (VFT), Digit Span Test (DST), and Trail Making Tests A and B (TMT-A and TMT-B). Structural and diffusional MRI data were acquired. White matter integrity was assessed using fractional anisotropy (FA), mean diffusivity (MD), and peak width of skeletonized mean diffusivity (PSMD). Cortical surface area, thickness, and volume were measured using Freesurfer. Probabilistic tractography was further conducted to track the white matter fibers connecting to the cortical regions related to cognition. General linear models were used to investigate the association between brain structure and cognition. Results: Global mean FA and MD were significantly associated with performances in VFT (FA, ß 0.119, p < 0.001; MD, ß -0.128, p < 0.001). Global cortical surface area, thickness, and volume were not related to cognitive scores. In tract-based spatial statistics analysis, disruptive white matter integrity was related to cognition impairment, mainly in visuomotor processing speed, semantic memory, and executive function (TMT-A and VFT), rather than verbal short-term memory and working memory (DST). In the whole brain vertex-wise analysis, surface area in the left orbitofrontal cortex, right posterior-dorsal part of the cingulate gyrus, and left central sulcus were positively associated with MMSE and MoCA scores, and the association were independent of the connecting white matter tract. Conclusion: Disrupted white matter integrity and regional cortical surface area were related to cognition in community-dwelling populations. The associations of cortical surface area and cognition were independent of the connecting white matter tract.
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High-throughput metabolic fingerprinting has been deemed one of the most promising strategies for addressing the high false positive rate of prostate cancer (PCa) diagnosis in the prostate-specific antigen (PSA) gray zone. However, the current metabolic fingerprinting remains challenging in achieving high-precision metabolite detection in complex biological samples (e.g., serum and urine). Herein, a novel self-assembly MoS2 /MXene heterostructure nanocomposite with a tailored doping ratio of 10% is presented as a matrix for laser desorption ionization mass spectrometry analysis in clinical biosamples. Notably, owing to the two-dimensional architecture and doping effect, MoS2 /MXene demonstrates favorable laser desorption ionization performance with low adsorption energy, which is evidenced by efficient urinary metabolic fingerprinting with an enhanced area under curve (AUC) diagnosis capability of 0.959 relative to that of serum metabolic fingerprinting (AUC = 0.902) for the diagnosis of PCa in the PSA gray zone. Thus, this MoS2 /MXene heterostructure is anticipated to offer a novel strategy to precisely and noninvasively diagnose PCa in the PSA gray zone.
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Antígeno Prostático Específico , Neoplasias de la Próstata , Masculino , Humanos , Molibdeno , Neoplasias de la Próstata/diagnósticoRESUMEN
BACKGROUND AND PURPOSE: Cerebrovascular parenchymal damage is prevalent in ageing brains; however, its vascular aetiology has not been fully elucidated. In addition to the underlying role of sclerotic arterioles, the correlation between collagenised venules has not been clarified. Here, we aimed to investigate the associations between microvascular injuries, including arteriolosclerosis and venular collagenosis, and related parenchymal damages in ageing brains, to investigate the underlying correlations. METHODS: We evaluated arteriolosclerosis and venular collagenosis in 7 regions from 27 autopsy cases with no history of stroke or brain tumour. The correlations between the ratio of arteriolosclerosis, venular collagenosis and the severity of cerebrovascular parenchymal damage, including lacunes, microinfarcts, myelin loss, and parenchymal and perivascular haemosiderin deposits, were assessed. RESULTS: Arteriolosclerosis and venular collagenosis became more evident with age. Arteriolosclerosis was associated with lacunes (p=0.004) and brain parenchymal haemosiderin deposits in the superior frontal cortex (p=0.024) but not with leukoaraiosis severity. Venular collagenosis was not associated with the number of lacunes or haemosiderin, while white matter generally became paler with severe venular collagenosis in the periventricular (ß=-0.430, p=0.028) and deep white matter (ß=-0.437, p=0.025). CONCLUSION: Our findings imply an important role for venular lesions in relation to microvessel-related parenchymal damage which is different from that for arteriolosclerosis. Different underlying mechanisms of both cerebral arterioles and venules require further investigation.
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Arterioloesclerosis , Humanos , Vénulas/patología , Arterioloesclerosis/diagnóstico , Arterioloesclerosis/patología , Autopsia , Hemosiderina , Encéfalo/patologíaRESUMEN
BACKGROUND AND PURPOSE: The circle of Willis (COW) is a circulatory anastomosis located at the base of the brain. Little is known about the association between covert vascular brain injury and COW configurations in the general population. We explored this relationship in a community-based Chinese sample. METHODS: A total of 1,055 patients (mean age, 54.8 ± 8.9 years; 36.0% men) without intracranial arterial stenosis were included in the analysis. Magnetic resonance imaging was performed to evaluate the presence of imaging markers of covert vascular brain injury, including white matter hyperintensities (WMHs), lacunes, cerebral microbleeds (CMBs), enlarged perivascular spaces, and brain atrophy. Magnetic resonance angiography was used to classify the COW configurations according to the completeness, symmetry, and presence of the fetal posterior cerebral artery (FTP). The association between vascular lesions and variations in COW was analyzed. RESULTS: Among the 1,055 patients, 104 (9.9%) had a complete COW. Completeness correlated with age (p = 0.001). Incomplete COW was positively associated with WMH severity (OR = 2.071; 95% CI, 1.004-4.270) and CMB presence (OR = 1.542; 95% CI, 1.012-2.348), independent of age and sex. The presence of FTP was associated with lacunes (OR = 1.878; 95% CI, 1.069-3.298), more severe WMHs (OR = 1.739; 95% CI, 1.064-2.842), and less severe enlarged perivascular spaces (OR = 0.562; 95% CI, 0.346-0.915). CONCLUSIONS: COW configuration was significantly related to various covert vascular brain injuries.
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Traumatismos Cerebrovasculares , Círculo Arterial Cerebral , Humanos , Círculo Arterial Cerebral/diagnóstico por imagen , Círculo Arterial Cerebral/patología , Encéfalo/diagnóstico por imagen , Imagen por Resonancia Magnética , Angiografía por Resonancia Magnética , Traumatismos Cerebrovasculares/patologíaRESUMEN
Background: There has been an increase in research on the potential adverse effects on children's mental health, especially depression and anxiety, during the coronavirus disease 2019 (COVID-19) pandemic over the past few months. Therefore, the aim of the present study was to investigate depression and anxiety symptoms among children in shelter hospitals during the 2022 Shanghai lockdown. Methods: A total of 98 infected children aged 7-12 years were enrolled in this study between April 19 and June 4, 2022. The Children's Depression Inventory (CDI), Anxiety Scale for Children-Autism Spectrum Disorder (ASC-ASD), and Anxiety Scale or Children-Autism Spectrum Disorder Parent Form (ASC-ADS-P) were used to assess children's depression and anxiety symptoms. Children's guardians completed the survey by verbally asking their child/children the questions. The guardians additionally completed the ASC-ASD-P. Results: The prevalence of depression and anxiety was 12.2% and 13.3%, respectively. A total of 66 respondents reported no physical symptoms. Linear regression showed that myalgia [7.198, 95% confidence interval (CI): 3.163-11.232], headache (7.189, 95% CI: 3.842-10.535) coryza (5.362, 95% CI: 2.654-8.070), and number of quarantine days (4.378, 95% CI: 3.409-5.348) were significantly correlated with higher levels of depression, whereas chills (14.337, 95% CI: 9.799-18.875), coryza (9.309, 95% CI: 6.467-12.152), headache (7.193, 95% CI: 3.182-11.204), myalgia (5.571, 95% CI: 0.684-10.459), number of quarantine days (3.190, 95% CI: 1.796-4.584), and gender (male) (-4.137, 95% CI: -6.609 to 1.665) were associated with anxiety scores. Persistent fever was correlated with depression (P=0.007), whereas physical discomfort, such as persistent fever, cough, sore throat, headache, myalgia, and coryza were correlated with anxiety (all P<0.05). Conclusions: The findings of the present study indicated a moderate prevalence of depression and anxiety among infected children in a shelter hospital during the 2022 Shanghai lockdown. Therefore, the findings of this study could provide scientific basis for the development of targeted psychological intervention. It could be helpful for policy-makers to focus on psychological health among infected children and help to optimize future interventions.
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BACKGROUND: Neuronal intranuclear inclusion disease (NIID) is a progressive neurodegenerative disease. Patients with NIID may present with heterogeneous clinical symptoms, including episodic encephalopathy, dementia, limb weakness, cerebellar ataxia, and autonomic dysfunction. Among the NIID cases reported in China, patients often have complicated and severe manifestations. Therefore, many clinicians do not consider the disease when the patient presents with relatively minor complaints. CASE PRESENTATION: We present the case of a 39-year-old man showing migraine-aura-like symptoms for the past 3 years. Brain magnetic resonance imaging (MRI) revealed hyperintense signals in the splenium of the corpus callosum and corticomedullary junction on diffusion-weighted imaging (DWI) over time. In addition, brain atrophy that was not concomitant with the patient's age was detected while retrospectively reviewing the patient's imaging results. Genetic analysis and skin biopsy confirmed a diagnosis of NIID. The patient was treated with sibelium, and the symptoms did not recur. DISCUSSION AND CONCLUSIONS: Migraine-aura-like symptoms may be the predominant clinical presentation in young patients with NIID. Persistent high-intensity signals on DWI in the brain and early-onset brain atrophy might be clues for the diagnosis of NIID.
Asunto(s)
Epilepsia , Trastornos Migrañosos , Enfermedades Neurodegenerativas , Masculino , Humanos , Adulto , Enfermedades Neurodegenerativas/diagnóstico , Enfermedades Neurodegenerativas/diagnóstico por imagen , Estudios Retrospectivos , Atrofia/complicaciones , Cefalea/complicaciones , Trastornos Migrañosos/complicaciones , Epilepsia/complicacionesRESUMEN
Background: Early studies have demonstrated the potential of deep learning in bringing revolutionary changes in medical analysis. However, it is unknown which deep learning based diagnostic pattern is more effective for differentiating malignant and benign breast lesions (BLs) and can assist radiologists to reduce unnecessary biopsies. Methods: A total of 506 malignant BLs and 557 benign BLs were enrolled in this study after excluding incomplete ultrasound images. 396 malignant BLs and 447 benign BLs were included in the training cohort while 110 malignant and 110 benign BLs were included in the validation cohort. All BLs in the training and validation cohort were biopsy-proven. The most common convolutional neural networks (VGG-16 and VGG-19) were applied to identify malignant and benign BLs using grey-scale ultrasound images. Two radiologists determined the malignant (suggestion for biopsy) and benign (suggestion for follow-up) BLs with a 2-step reading session. The first step was based on conventional ultrasound (US) images alone to make a biopsy or follow-up decision. The second step was to take deep learning results into account for the decision adjustment. If a deep learning result of a first-classified benign BL was above the cut-off value, then it was re-classified as malignant. Results: In terms of area under the curve (AUC), the VGG-19 model yielded the best diagnostic performance in both training [0.939, 95% confidence interval (CI): 0.924-0.954] and testing dataset (0.959, 95% CI: 0.937-0.982). With the aid of deep learning models, the AUC of radiologists improved from 0.805 (95% CI: 0.744-0.865) to 0.827 (95% CI: 0.771-0.875, VGG-16) and 0.914 (95% CI: 0.871-0.957, VGG-19). The unnecessary biopsies decreased from 10.0% (11/110) to 8.2% (9/110) (assisted by VGG-16) and 0.9% (1/110) (assisted by VGG-19). Conclusions: The application of deep learning patterns in breast US may improve the diagnostic performance of radiologists by offering a second opinion. And thus, the assist of deep learning algorithm can considerably reduce the unnecessary biopsy rate in the clinical management of breast lesions.