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Heterogeneous integration of single-crystal materials offers great opportunities for advanced device platforms and functional systems1. Although substantial efforts have been made to co-integrate active device layers by heteroepitaxy, the mismatch in lattice polarity and lattice constants has been limiting the quality of the grown materials2. Layer transfer methods as an alternative approach, on the other hand, suffer from the limited availability of transferrable materials and transfer-process-related obstacles3. Here, we introduce graphene nanopatterns as an advanced heterointegration platform that allows the creation of a broad spectrum of freestanding single-crystalline membranes with substantially reduced defects, ranging from non-polar materials to polar materials and from low-bandgap to high-bandgap semiconductors. Additionally, we unveil unique mechanisms to substantially reduce crystallographic defects such as misfit dislocations, threading dislocations and antiphase boundaries in lattice- and polarity-mismatched heteroepitaxial systems, owing to the flexibility and chemical inertness of graphene nanopatterns. More importantly, we develop a comprehensive mechanics theory to precisely guide cracks through the graphene layer, and demonstrate the successful exfoliation of any epitaxial overlayers grown on the graphene nanopatterns. Thus, this approach has the potential to revolutionize the heterogeneous integration of dissimilar materials by widening the choice of materials and offering flexibility in designing heterointegrated systems.

The concept of remote epitaxy involves a two-dimensional van der Waals layer covering the substrate surface, which still enable adatoms to follow the atomic motif of the underlying substrate. The mode of growth must be carefully defined as defects, e.g., pinholes, in two-dimensional materials can allow direct epitaxy from the substrate, which, in combination with lateral epitaxial overgrowth, could also form an epilayer. Here, we show several unique cases that can only be observed for remote epitaxy, distinguishable from other two-dimensional material-based epitaxy mechanisms. We first grow BaTiO 3 on patterned graphene to establish a condition for minimizing epitaxial lateral overgrowth. By observing entire nanometer-scale nuclei grown aligned to the substrate on pinhole-free graphene confirmed by high-resolution scanning transmission electron microscopy, we visually confirm that remote epitaxy is operative at the atomic scale. Macroscopically, we also show variations in the density of GaN microcrystal arrays that depend on the ionicity of substrates and the number of graphene layers.

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability.

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine ou

BackgroundIn prior work we observed differences in morphology features in placentas from an autism-enriched cohort as compared to those from a general population sample. Here we sought to examine whether these differences associate with ASD-related outcomes in the child.MethodsParticipants (n = 101) were drawn from the Early Autism Risk Longitudinal Investigation (EARLI), a cohort following younger siblings of children with autism spectrum disorder (ASD). ASD-related outcomes, including the Social Responsiveness Scale (SRS), Mullen Scales of Early Learning (MSEL) Early Learning Composite, and ASD diagnosis, were assessed at age 3. Crude and adjusted linear regression was used to examine associations between placental morphological features (parametrized continuously and in quartiles) and SRS and MSEL scores; comparisons by ASD case status were explored as secondary analyses due to the small number of cases (n = 20).ResultsIn adjusted analyses, we observed a modest positive association between umbilical cord eccentricity, defined as the ratio of the maximum:minimum radius from the cord insertion point, and SRS scores (Beta = 1.68, 95%CI = 0.45, 2.9). Positive associations were also suggested between placental maximum thickness and cord centrality and SRS scores, though these were estimated with little precision. Associations between other placental morphological features and outcomes were not observed.ConclusionsOur analyses suggested a potential association between umbilical cord features and ASD-related traits, of interest as non-central cord insertion may reflect reduced placenta efficiency. Future studies with larger sample sizes are needed to further examine these and other placental features in association with ASD-related outcomes.

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings, SCOPUS: ar.j, info:eu-repo/semantics/published

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability.

Temporal lobe epilepsy, a common drug-resistant epilepsy in adults, is primarily a limbic network disorder associated with predominant unilateral hippocampal pathology. Structural MRI has provided an in vivo window into whole-brain grey matter structural alterations in temporal lobe epilepsy relative to controls, by either mapping (i) atypical inter-hemispheric asymmetry; or (ii) regional atrophy. However, similarities and differences of both atypical asymmetry and regional atrophy measures have not been systematically investigated. Here, we addressed this gap using the multisite ENIGMA-Epilepsy dataset comprising MRI brain morphological measures in 732 temporal lobe epilepsy patients and 1418 healthy controls. We compared spatial distributions of grey matter asymmetry and atrophy in temporal lobe epilepsy, contextualized their topographies relative to spatial gradients in cortical microstructure and functional connectivity calculated using 207 healthy controls obtained from Human Connectome Project and an independent dataset containing 23 temporal lobe epilepsy patients and 53 healthy controls and examined clinical associations using machine learning. We identified a marked divergence in the spatial distribution of atypical inter-hemispheric asymmetry and regional atrophy mapping. The former revealed a temporo-limbic disease signature while the latter showed diffuse and bilateral patterns. Our findings were robust across individual sites and patients. Cortical atrophy was significantly correlated with disease duration and age at seizure onset, while degrees of asymmetry did not show a significant relationship to these clinical variables. Our findings highlight that the mapping of atypical inter-hemispheric asymmetry and regional atrophy tap into two complementary aspects of temporal lobe epilepsy-related pathology, with the former revealing primary substrates in ipsilateral limbic circuits and the latter capturing bilateral disease effects. These findings refine ou

BackgroundPerinatal exposure to air pollution and immune system dysregulation are two factors consistently associated with autism spectrum disorders (ASD) and other neurodevelopmental outcomes. However, little is known about how air pollution may influence maternal immune function during pregnancy.ObjectivesTo assess the relationship between mid-gestational circulating levels of maternal cytokines/chemokines and previous month air pollution exposure across neurodevelopmental groups, and to assess whether cytokines/chemokines mediate the relationship between air pollution exposures and risk of ASD and/or intellectual disability (ID) in the Early Markers for Autism (EMA) study.MethodsEMA is a population-based, nested case-control study which linked archived maternal serum samples collected during weeks 15-19 of gestation for routine prenatal screening, birth records, and Department of Developmental Services (DDS) records. Children receiving DDS services for ASD without intellectual disability (ASD without ID; n = 199), ASD with ID (ASD with ID; n = 180), ID without ASD (ID; n = 164), and children from the general population (GP; n = 414) with no DDS services were included in this analysis. Serum samples were quantified for 22 cytokines/chemokines using Luminex multiplex analysis technology. Air pollution exposure for the month prior to maternal serum collection was assigned based on the Environmental Protection Agency's Air Quality System data using the maternal residential address reported during the prenatal screening visit.ResultsPrevious month air pollution exposure and mid-gestational maternal cytokine and chemokine levels were significantly correlated, though weak in magnitude (ranging from - 0.16 to 0.13). Ten pairs of mid-pregnancy immune markers and previous month air pollutants were significantly associated within one of the child neurodevelopmental groups, adjusted for covariates (p < 0.001). Mid-pregnancy air pollution was not associated with any neurod

Here we report the miscibility gap of CuSb1-xBixS2 (CABS), a promising photo energy conversion material for band gap engineered solar cells, and evaluate its applicability via a combination of theoretical predictions and experimental verifications. Our ab initio calculations and thermodynamic modeling revealed that the CABS random alloy system has optimal band gap values in the range of 1.1-1.5 eV when synthesized at room temperature. The CABS system, synthesized by mechanochemical methods, exhibited optical band gap values in very good agreement with theoretical predictions, as well as lowered kinetic energy barriers for enhanced nucleation. (C) 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

BackgroundPerinatal exposure to air pollution and immune system dysregulation are two factors consistently associated with autism spectrum disorders (ASD) and other neurodevelopmental outcomes. However, little is known about how air pollution may influence maternal immune function during pregnancy.ObjectivesTo assess the relationship between mid-gestational circulating levels of maternal cytokines/chemokines and previous month air pollution exposure across neurodevelopmental groups, and to assess whether cytokines/chemokines mediate the relationship between air pollution exposures and risk of ASD and/or intellectual disability (ID) in the Early Markers for Autism (EMA) study.MethodsEMA is a population-based, nested case-control study which linked archived maternal serum samples collected during weeks 15-19 of gestation for routine prenatal screening, birth records, and Department of Developmental Services (DDS) records. Children receiving DDS services for ASD without intellectual disability (ASD without ID; n = 199), ASD with ID (ASD with ID; n = 180), ID without ASD (ID; n = 164), and children from the general population (GP; n = 414) with no DDS services were included in this analysis. Serum samples were quantified for 22 cytokines/chemokines using Luminex multiplex analysis technology. Air pollution exposure for the month prior to maternal serum collection was assigned based on the Environmental Protection Agency's Air Quality System data using the maternal residential address reported during the prenatal screening visit.ResultsPrevious month air pollution exposure and mid-gestational maternal cytokine and chemokine levels were significantly correlated, though weak in magnitude (ranging from - 0.16 to 0.13). Ten pairs of mid-pregnancy immune markers and previous month air pollutants were significantly associated within one of the child neurodevelopmental groups, adjusted for covariates (p < 0.001). Mid-pregnancy air pollution was not associated with any neurod

BackgroundPrenatal exposure to increased androgens has been suggested as a risk factor for autism spectrum disorder (ASD). This hypothesis has been examined by measurement of steroids in amniotic fluid, cord blood, saliva, and blood with mixed results.MethodsTo provide an orthogonal measure of fetal exposure, this study used meconium, the first stool of a newborn, to measure prenatal androgen exposure from infants in the Early Autism Risk Longitudinal Investigation (EARLI). EARLI is a familial-enriched risk cohort that enrolled pregnant mothers who already had a child with an ASD diagnosis. In the younger child, we investigated the association between meconium unconjugated (u) and total (t) concentrations of major androgens testosterone (T), dehydroepiandrosterone (DHEA), and androstenedione (A4), and ASD-related traits at 12 and 36 months of age. Traits were measured at 12 months with Autism Observation Scale for Infants (AOSI) and at 36 months with total score on the Social Responsiveness Scale (SRS). One hundred and seventy children had meconium and AOSI, 140 had meconium and SRS, and 137 had meconium and both AOSI and SRS.ResultsSeparate robust linear regressions between each of the log-transformed androgens and log-transformed SRS scores revealed three-way interaction between sex of the child, sex of the proband, and testosterone concentration. In the adjusted analyses, t-T, u-A4, and u-DHEA (P ≤ 0.01) were positively associated with AOSI scores, while u-T (P = 0.004) and u-DHEA (P = 0.007) were positively associated with SRS total score among females with female probands (n = 10). Additionally, higher concentrations of u-T (P = 0.01) and t-T (P = 0.01) predicted higher SRS total score in males with male probands (n = 63). Limitations Since we explored three-way interactions, this resulted in a limited sample size for some analyses. This study was from an enriched-risk cohort which may limit generalizability, and this study used ASD-assessment sc

Here we report the miscibility gap of CuSb1-xBixS2 (CABS), a promising photo energy conversion material for band gap engineered solar cells, and evaluate its applicability via a combination of theoretical predictions and experimental verifications. Our ab initio calculations and thermodynamic modeling revealed that the CABS random alloy system has optimal band gap values in the range of 1.1-1.5 eV when synthesized at room temperature. The CABS system, synthesized by mechanochemical methods, exhibited optical band gap values in very good agreement with theoretical predictions, as well as lowered kinetic energy barriers for enhanced nucleation. (C) 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

BackgroundAutism spectrum disorder (ASD) affects more than 1% of children in the USA. The male-to-female prevalence ratio of roughly 4:1 in ASD is a well-recognized but poorly understood phenomenon. An explicit focus on potential etiologic pathways consistent with this sex difference, such as those involving prenatal androgen exposure, may help elucidate causes of ASD. Furthermore, the multi-threshold liability model suggests that the genetic mechanisms in females with ASD may be distinct and may modulate ASD risk in families with female ASD in the pedigree.MethodsWe examined umbilical cord blood from 137 children in the Early Autism Risk Longitudinal Investigation (EARLI) cohort. EARLI is an ASD-enriched risk cohort with all children having an older sibling already diagnosed with ASD. Fetal testosterone (T), androstenedione (A4), and dehyroepiandrosterone (DHEA) levels were measured in cord blood using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Robust linear regression models were used to determine associations between cord blood androgen levels and 12-month Autism Observation Scales for Infants (AOSI) scores and 36-month Social Responsiveness Scale (SRS) scores adjusting for potential confounders.ResultsIncreasing androgens were not associated with increasing 12-month AOSI score or 36-month total SRS score in either boys or girls. However, the association between T and autistic traits among subjects with a female older affected sibling was greater at 12 months (test of interaction, P = 0.008) and deficits in reciprocal social behavior at 36 months were also greater (test of interaction, P = 0.006) than in subjects whose older affected sibling was male.ConclusionsWhile increased prenatal testosterone levels were not associated with autistic traits at 12 or 36 months, our findings of a positive association in infants whose older ASD-affected siblings were female suggests an androgen-related mechanism that may be dependent on, or relate

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder that affects more than 1% of children in the USA. ASD risk is thought to arise from both genetic and environmental factors, with the perinatal period as a critical window. Understanding early transcriptional changes in ASD would assist in clarifying disease pathogenesis and identifying biomarkers. However, little is known about umbilical cord blood gene expression profiles in babies later diagnosed with ASD compared to non-typically developing and non-ASD (Non-TD) or typically developing (TD) children.MethodsGenome-wide transcript levels were measured by Affymetrix Human Gene 2.0 array in RNA from cord blood samples from both the Markers of Autism Risk in Babies-Learning Early Signs (MARBLES) and the Early Autism Risk Longitudinal Investigation (EARLI) high-risk pregnancy cohorts that enroll younger siblings of a child previously diagnosed with ASD. Younger siblings were diagnosed based on assessments at 36 months, and 59 ASD, 92 Non-TD, and 120 TD subjects were included. Using both differential expression analysis and weighted gene correlation network analysis, gene expression between ASD and TD, and between Non-TD and TD, was compared within each study and via meta-analysis.ResultsWhile cord blood gene expression differences comparing either ASD or Non-TD to TD did not reach genome-wide significance, 172 genes were nominally differentially expressed between ASD and TD cord blood (log2(fold change) > 0.1, p < 0.01). These genes were significantly enriched for functions in xenobiotic metabolism, chromatin regulation, and systemic lupus erythematosus (FDR q < 0.05). In contrast, 66 genes were nominally differentially expressed between Non-TD and TD, including 8 genes that were also differentially expressed in ASD. Gene coexpression modules were significantly correlated with demographic factors and cell type proportions.LimitationsASD-associated gene expression differences identified in

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder that affects more than 1% of children in the USA. ASD risk is thought to arise from both genetic and environmental factors, with the perinatal period as a critical window. Understanding early transcriptional changes in ASD would assist in clarifying disease pathogenesis and identifying biomarkers. However, little is known about umbilical cord blood gene expression profiles in babies later diagnosed with ASD compared to non-typically developing and non-ASD (Non-TD) or typically developing (TD) children.MethodsGenome-wide transcript levels were measured by Affymetrix Human Gene 2.0 array in RNA from cord blood samples from both the Markers of Autism Risk in Babies-Learning Early Signs (MARBLES) and the Early Autism Risk Longitudinal Investigation (EARLI) high-risk pregnancy cohorts that enroll younger siblings of a child previously diagnosed with ASD. Younger siblings were diagnosed based on assessments at 36 months, and 59 ASD, 92 Non-TD, and 120 TD subjects were included. Using both differential expression analysis and weighted gene correlation network analysis, gene expression between ASD and TD, and between Non-TD and TD, was compared within each study and via meta-analysis.ResultsWhile cord blood gene expression differences comparing either ASD or Non-TD to TD did not reach genome-wide significance, 172 genes were nominally differentially expressed between ASD and TD cord blood (log2(fold change) > 0.1, p < 0.01). These genes were significantly enriched for functions in xenobiotic metabolism, chromatin regulation, and systemic lupus erythematosus (FDR q < 0.05). In contrast, 66 genes were nominally differentially expressed between Non-TD and TD, including 8 genes that were also differentially expressed in ASD. Gene coexpression modules were significantly correlated with demographic factors and cell type proportions.LimitationsASD-associated gene expression differences identified in

Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are often still obtained from manual segmentations on brain MR images, which is a laborious procedure. Automatic WMH segmentation methods exist, but a standardized comparison of the performance of such methods is lacking. We organized a scientific challenge, in which developers could evaluate their method on a standardized multi-center/-scanner image dataset, giving an objective comparison: the WMH Segmentation Challenge (https://wmh.isi.uu.nl/). Sixty T1+FLAIR images from three MR scanners were released with manual WMH segmentations for training. A test set of 110 images from five MR scanners was used for evaluation. Segmentation methods had to be containerized and submitted to the challenge organizers. Five evaluation metrics were used to rank the methods: (1) Dice similarity coefficient, (2) modified Hausdorff distance (95th percentile), (3) absolute log-transformed volume difference, (4) sensitivity for detecting individual lesions, and (5) F1-score for individual lesions. Additionally, methods were ranked on their inter-scanner robustness. Twenty participants submitted their method for evaluation. This paper provides a detailed analysis of the results. In brief, there is a cluster of four methods that rank significantly better than the other methods, with one clear winner. The inter-scanner robustness ranking shows that not all methods generalize to unseen scanners. The challenge remains open for future submissions and provides a public platform for method evaluation., Comment: Accepted for publication in IEEE Transactions on Medical Imaging

Prenatal metabolism exerts profound effects on development. The first stool of the newborn, meconium, provides a window into the prenatal metabolic environment. The objective of this study was to examine the feasibility of meconium as a novel matrix to quantify prenatal steroid levels. We quantified parameters of analytical interest regarding the use of meconium, including sample stability. We hypothesized that meconium steroid content would differ by sex, prompting analysis of meconium to test effects of prenatal steroid metabolism. Meconium from 193 newborns enrolled in the Early Autism Risk Longitudinal Investigation (EARLI) study, including 107 males, and 86 females, were analyzed by isotope dilution-liquid chromatography-high resolution mass spectrometry (ID-LC-HRMS) while blinded to identity for testosterone (T), androstenedione (AD), and dehydroepiandrosterone (DHEA). Steroid levels were compared by sex, and investigations of potential trends resulting from sample storage or processing was conducted. The unconjugated steroid content of meconium in ng/g (mean, standard deviation) was for males: T (2.67, 8.99), AD (20.01, 28.12), DHEA (13.96, 23.57) and for females: T (0.82, 1.63), AD (22.32, 24.38), DHEA (21.06, 43.49). T was higher in meconium from males (p=0.0333), and DHEA was higher in meconium from females (p=0.0202). 6 female and 3 male T values were below the limit of detection. No extreme variability in hydration or trend in steroid levels by storage time was detected. Sexually dimorphic levels of hormones may reflect gestational differentiation, and future studies should consider meconium analysis.

Isocontour mapping is efficient for extracting meaningful information from a biomedical image in a topographic analysis. Isocontour extraction from real world medical images is difficult due to noise and other factors. As such, adaptive selection of contour generation parameters is needed. This paper proposes an algorithm for generating an adaptive contour map that is spatially adjusted. It is based on the modified active contour model, which imposes successive spatial constraints on the image domain. The adaptability of the proposed algorithm is governed by the energy term of the model. This work focuses on mammograms and the analysis of their intensity. Our algorithm employs the Mumford-Shah energy functional, which considers an image's intensity distribution. In mammograms, the brighter regions generally contain significant information. Our approach exploits this characteristic to address the initialization and local optimum problems of the active contour model. Our algorithm starts from the darkest region; therefore, local optima encountered during the evolution of contours are populated in less important regions, and the important brighter regions are reserved for later stages. For an unrestricted initial contour, our algorithm adopts an existing technique without re-initialization. To assess its effectiveness and robustness, the proposed algorithm was tested on a set of mammograms.