Folding Index Research Articles

Network analysis of structural MRI predicts executive function in paediatric traumatic brain injury

IntroPaediatric traumatic brain injury (pTBI) is likely to result in cognitive impairment, specifically executive dysfunction. Evidence of the neuroanatomical correlates of this executive function (EF) impairment is derived from studies that treat morphometry of brain regions as distinct, independent features, rather than as a complex network of interrelationships. Morphometric similarity captures the meso-scale organisation of the cortex as the interrelatedness of multiple macro-architectural features and presents a novel tool with which to investigate the brain post pTBI. MethodsIn a retrospective sample (83 pTBI patients, 33 controls), we estimate morphometric similarity from structural MRI by correlating morphometric features between cortical regions. We compared the meso-scale organisation of the cortex between groups then, using partial least squares regression, assessed the predictive validity of morphometric similarity in understanding later executive functioning, two years post-injury. ResultsWe found that patients and controls did not differ in terms of the overall magnitude of morphometric similarity. However, a pattern of ROI-level morphometric similarity was predictive of day-to-day EF difficulties reported by parents two years post-injury. This prediction was validated using a leave-one-out, and 20-fold cross-validation approach. Prediction was driven by regions of the prefrontal cortex, typically important for healthy maturation of EF skills in childhood. The meso-scale organisation of the cortex also produced more accurate predictions than any one morphometric feature (i.e. cortical thickness or folding index) alone. ConclusionWe conclude that these methodologies show utility in predicting later executive functioning in this population.

47 Evolution of Brain Morphology and Cognitive Performance in Parkinson’s Disease with Impulse Control Disorder

Objective:Parkinson’s disease (PD) affects the person’s quality of life, but the comorbidity of PD and impulsive control disorder (ICD), which has an average prevalence of 23%, can enhance the disruption of quality of life for the patients and their caregivers. The effects of ICD in PD on brain morphology and cognition have been little studied. Thus, this study proposes to investigate the differences in the evolution of cognitive performance and brain structures between PD patients with ICD (PD-ICD) vs. without ICD (PD-no-ICD).Participants and Methods:Parkinson’s Progression Markers Initiative (PPMI) data of 58 patients with idiopathic PD, including their MRI data at baseline and three years later, were analyzed. The MRIs were processed with FreeSurfer (7.1.1) to extract cortical volumes, areas, thicknesses, curvatures and folding index as well as volumes of subcortical segmentations. All participants underwent cognitive evaluations. The Questionnaire for Impulsive-Compulsive Disorders in Parkinson’s Disease was used to differentiate those with at least one ICD from those without any ICD. 12 of the 58 patients had an ICD at their first visit and 19 had an ICD at their visit three years later. There was no significant difference between PD-ICD and PD-no-ICD with respect to sex, use of overall medication, age, age of onset, age at diagnosis, years of education and the Montreal cognitive assessment score. Two-way mixed ANOVAs were performed for each neuropsychological test and brain structure extracted from MRIs with the time of the visit as the repeated independent variable (within participants) and the presence or absence of an ICD as the other independent variable (between participants).Results:The mixed ANOVA revealed that PD-ICD had their performance decline after three years, for the Hopkins Verbal Learning Test delayed recall and the Symbol Digit Modalities Test while PD-no-ICD saw their performance increase. A whole brain analysis showed that PD-ICD had a significant decrease after three years of the right cortex area total brain volume in comparison to PD-no-ICD. Specific brain structures also underwent significant changes over three years. Cortical changes in PD-ICD were: (1) increased surface area in the left temporal parahippocampus and (2) decreased surface areas of the right insula, right middle and superior temporal regions, left occipital lingual as well as left cingulate isthmus. Furthermore, in the subcortical nuclei, PD-ICD showed (1) increased volumes of the paratenial thalamic nucleus and whole right amygdala and (2) decreased volumes of the right amygdalian basal nucleus and thalamic ventromedial nucleus.Conclusions:This study suggests that PD patients who also have ICD might be prone to develop over three years: (1) significant changes in cognitive performance (memory, attention), (2) morphological changes in the amygdala and thalamic nuclei and (3) significant atrophy and area shrinkage in the temporal and insula regions.

48 Longitudinal Study: Impact of Anxiety on the Evolution of Cognitive Performance and Brain Morphology in Patients with Parkinson’s Disease

Objective:Anxiety is very common in Parkinson’s disease (PD) where according to a systematic review, the average prevalence is 31%, surprisingly higher than the average 17% of depressive disorders found in PD. Only a few studies have investigated the impact of anxiety on cognitive performance and brain morphology in PD. They demonstrated anxiety to be a significant predictor of cognitive impairment, where PD patients with anxiety have shown to be twice more likely to have deficits in the memory domain compared to those without anxiety. Furthermore, poorer cognitive performance in all cognitive domains was reported to be a significant risk factor for increased anxiety the following year. Anxiety in PD has also shown reduced volume/thinning in the fronto-cingulate, anterior cingulate cortex, left parietal cortices and the precuneus, despite the scant number of studies on this topic. Hence, the objective of this study aims to determine the evolution of cognitive performance and brain morphology in PD patients with and without anxiety over a three-year span.Participants and Methods:We analyzed the baseline and three-year follow-up Parkinson’s Progression Markers Initiative (PPMI) data of 58 PD patients. MRI 3T was processed with FreeSurfer 7.1.1 on the Compute Canada cluster “Cedar” and we extracted cortical (Desikan-atlas-based volumes, thickness, area, folding index, curvature) and volumes of subcortical structures. Additionally, anxiety subscores from the State-trait anxiety inventory as well as neuropsychological tests were analyzed. PD patients were classified in two groups: PD-no-anxiety (n=46) and PD-anxiety (n=12) (subscore of > 40 on the State anxiety scale). Two-way mixed ANOVA models were established with presence/absence of anxiety as a between-subjects factor, time (baseline and three year) as a within-subjects factor and neuropsychological and MRI data were regarded as dependent variables.Results:Mixed ANOVA revealed that PD-anxiety saw a significantly greater decline in performance on the Montreal Cognitive Assessment test compared to PD-no-anxiety. In addition, PD-anxiety saw their performance decline over time in the Hopkins Verbal Learning test (HVLT) immediate recall, HVLT retention and HVLT delayed recall while PD-no-anxiety saw an increase in performance. In terms of brain morphology, over the three years, PD-anxiety had a greater decrease in the frontal precentral thickness, cingulate isthmus area and thickness, and temporal regions (transverse area and inferior folding) all in the left hemisphere compared to PD-no-anxiety. In subcortical regions, PD-anxiety had a greater decrease in volume of the hippocampal cornu ammonis-1 and pallidum compared to PD-no-anxiety. By contrast, PD-anxiety showed a greater increase in curvature of the frontal middle rostral, frontal pole, parietal supramarginal, and insula cortex as well as in the folding of the parietal superior and occipital pericalcarine of the right hemisphere in comparison to PD-no-anxiety.Conclusions:This study highlights the importance of taking into consideration anxiety symptoms in PD, as they contribute to poorer cognitive performance and frontal, parietal and temporal differences over time. More studies with a larger sample size are needed in order to confirm these results.

Genetic risks of Alzheimer's by APOE and MAPT on cortical morphology in young healthy adults.

Genetic risk factors such as APOE ε4 and MAPT (rs242557) A allele are associated with amyloid and tau pathways and grey matter changes at both early and established stages of Alzheimer's disease, but their effects on cortical morphology in young healthy adults remain unclear. A total of 144 participants aged from 18 to 24 underwent 3T MRI and genotyping for APOE and MAPT to investigate unique impacts of these genetic risk factors in a cohort without significant comorbid conditions such as metabolic and cardiovascular diseases. We segmented the cerebral cortex into 68 regions and calculated the cortical area, thickness, curvature and folding index for each region. Then, we trained machine learning models to classify APOE and MAPT genotypes using these morphological features. In addition, we applied a growing hierarchical self-organizing maps algorithm, which clustered the 68 regions into 4 subgroups representing different morphological patterns. Then, we performed general linear model analyses to estimate the interaction between APOE and MAPT on cortical patterns. We found that the classifiers using all cortical features could accurately classify individuals carrying genetic risks of dementia outperforming each individual feature alone. APOE ε4 carriers had a more convoluted and thinner cortex across the cerebral cortex. A similar pattern was found in MAPT A allele carriers only in the regions that are vulnerable for early tau pathology. With the clustering analysis, we found a synergetic effect between APOE ε4 and MAPT A allele, i.e. carriers of both risk factors showed the most deviation of cortical pattern from the typical pattern of that cluster. Genetic risk factors of dementia by APOE ε4 and MAPT (rs242557) A allele were associated with variations of cortical morphology, which can be observed in young healthy adults more than 30 years before Alzheimer's pathology is likely to occur and 50 years before dementia symptoms may begin.

Migraine with aura detection and subtype classification using machine learning algorithms and morphometric magnetic resonance imaging data.

Migraine with aura (MwA) is a neurological condition manifested in moderate to severe headaches associated with transient visual and somatosensory symptoms, as well as higher cortical dysfunctions. Considering that about 5% of the world's population suffers from this condition and manifestation could be abundant and characterized by various symptoms, it is of great importance to focus on finding new and advanced techniques for the detection of different phenotypes, which in turn, can allow better diagnosis, classification, and biomarker validation, resulting in tailored treatments of MwA patients. This research aimed to test different machine learning techniques to distinguish healthy people from those suffering from MwA, as well as people with simple MwA and those experiencing complex MwA. Magnetic resonance imaging (MRI) post-processed data (cortical thickness, cortical surface area, cortical volume, cortical mean Gaussian curvature, and cortical folding index) was collected from 78 subjects [46 MwA patients (22 simple MwA and 24 complex MwA) and 32 healthy controls] with 340 different features used for the algorithm training. The results show that an algorithm based on post-processed MRI data yields a high classification accuracy (97%) of MwA patients and precise distinction between simple MwA and complex MwA with an accuracy of 98%. Additionally, the sets of features relevant to the classification were identified. The feature importance ranking indicates the thickness of the left temporal pole, right lingual gyrus, and left pars opercularis as the most prominent markers for MwA classification, while the thickness of left pericalcarine gyrus and left pars opercularis are proposed as the two most important features for the simple and complex MwA classification. This method shows significant potential in the validation of MwA diagnosis and subtype classification, which can tackle and challenge the current treatments of MwA.

A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex.

Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical regression analysis, the structural index did not contribute to significant variance in the C1 latency after regressing out the effect of age. However, the age explained significant variance in the model after regressing out the effect of structural feature.

Sharing individualised template MRI data for MEG source reconstruction: A solution for open data while keeping subject confidentiality

The increasing requirements for adoption of FAIR data management and sharing original research data from neuroimaging studies can be at odds with protecting the anonymity of the research participants due to the person-identifiable anatomical features in the data. We propose a solution to this dilemma for anatomical MRIs used in MEG source analysis. In MEG analysis, the channel-level data is reconstructed to the source-level using models derived from anatomical MRIs. Sharing data, therefore, requires sharing the anatomical MRI to replicate the analysis. The suggested solution is to replace the individual anatomical MRIs with individualised warped templates that can be used to carry out the MEG source analysis and that provide sufficient geometrical similarity to the original participants’ MRIs.First, we demonstrate how the individualised template warping can be implemented with one of the leading open-source neuroimaging analysis toolboxes. Second, we compare results from four different MEG source reconstruction methods performed with an individualised warped template to those using the participant's original MRI. While the source reconstruction results are not numerically identical, there is a high similarity between the results for single dipole fits, dynamic imaging of coherent sources beamforming, and atlas-based virtual channel beamforming. There is a moderate similarity between minimum-norm estimates, as anticipated due to this method being anatomically constrained and dependent on the exact morphological features of the cortical sheet.We also compared the morphological features of the warped template to those of the original MRI. These showed a high similarity in grey matter volume and surface area, but a low similarity in the average cortical thickness and the mean folding index within cortical parcels.Taken together, this demonstrates that the results obtained by MEG source reconstruction can be preserved with the warped templates, whereas the anatomical and morphological fingerprint is sufficiently altered to protect the anonymity of research participants. In cases where participants consent to sharing anatomical MRI data, it remains preferable to share the original defaced data with an appropriate data use agreement. In cases where participants did not consent to share their MRIs, the individualised warped MRI template offers a good compromise in sharing data for reuse while retaining anonymity for research participants.

Brain morphology, harm avoidance, and the severity of excessive internet use.

As the previous studies have mainly focused on the reward system and the corresponding brain regions, the relationship between brain morphology and excessive internet use (EIU) were not clear; the purpose of the study was to investigate if the brain regions other than the reward system were associated with EIU. Data were acquired from 131 excessive internet users. Psychological measures included internet use, life quality, personality, mental illness symptoms, impulsivity, and thought suppression. The brain was scanned with 3T magnetic resonance imaging (MRI) and six types of brain morphological indexes were calculated. Lasso regression methods were used to select the predictors. Stepwise linear regression methods were used to build the models and verify the model. The variables remaining in the model were left precentral (curve), left superior temporal (surface area), right cuneus (folding index), right rostral anterior cingulate (folding index), and harm avoidance. The independent variable was the EIU score of the worst week in the past year. The study found that the brain morphological indexes other than the reward system, including the left precentral (curve), the left superior temporal (surface area), the right cuneus (folding index), and the right rostral anterior cingulate (folding index), can predict the severity of EIU, suggesting an extensive change in the brain. In this study, a whole‐brain data analysis was conducted and it was concluded that the changes in certain brain regions were more predictive than the reward system and psychological measures or more important for EIU.

Brain age estimation using multi-feature-based networks

Studying brain aging improves our understanding in differentiating typical and atypical aging. Directly utilizing traditional morphological features for brain age estimation did not show significant performance in healthy controls (HCs), which may be due to the negligence of the information of structural similarities among cortical regions. For this issue, the multi-feature-based network (MFN) built upon morphological features can be employed to describe these similarities. Based on this, we hypothesized that the MFN is more efficient and robust than traditional morphological features in brain age estimating. In this work, we used six different types of morphological features (i.e., cortical volume, cortical thickness, curvature index, folding index, local gyrification index, and surface area) to build individual MFN for brain age estimation. The efficacy of MFN was estimated on 2501 HCs with T1-weighted structural magnetic resonance imaging (sMRI) data and compared with traditional morphological features. We attained a mean absolute error (MAE) of 3.73 years using the proposed method on an independent test set, whereas a mean absolute error of 5.30 years was derived from morphological features. Our experimental results demonstrated that the MFN is an efficient and robust metric for estimating brain age.

Cortical thickness systematically varies with curvature and depth in healthy human brains.

Cortical thickness varies throughout the cortex in a systematic way. However, it is challenging to investigate the patterns of cortical thickness due to the intricate geometry of the cortex. The cortex has a folded nature both in radial and tangential directions which forms not only gyri and sulci but also tangential folds and intersections. In this article, cortical curvature and depth are used to characterize the spatial distribution of the cortical thickness with much higher resolution than conventional regional atlases. To do this, a computational pipeline was developed that is capable of calculating a variety of quantitative measures such as surface area, cortical thickness, curvature (mean curvature, Gaussian curvature, shape index, intrinsic curvature index, and folding index), and sulcal depth. By analyzing 501 neurotypical adult human subjects from the ABIDE‐I dataset, we show that cortex has a very organized structure and cortical thickness is strongly correlated with local shape. Our results indicate that cortical thickness consistently increases along the gyral–sulcal spectrum from concave to convex shape, encompassing the saddle shape along the way. Additionally, tangential folds influence cortical thickness in a similar way as gyral and sulcal folds; outer folds are consistently thicker than inner.

TransDIR: Deformable imaging registration network based on transformer to improve the feature extraction ability.

Imaging registration has a significant contribution to guide and support physicians in the process of decision-making for diagnosis, prognosis, and treatment. However, existing registration methods based on the convolutional neural network cannot extract global features effectively, which significantly influences registration performance. Moreover, the smoothness of the displacement vector field (DVF) fails to be ensured due to the miss folding penalty. In order to capture abundant global information as well as local information, we have proposed a novel 3D deformable image registration network based on Transformer (TransDIR). In the encoding phase, the transformer with the atrous reduction attention block is designed to capture the long-distance dependencies that are crucial for extracting global information. A zero-padding position encoder is embedded into the transformer to capture the local information. In the decoding phase, an up-sampling module based on an attention mechanism is designed to increase the significance of ROIs. Because of adding folding penalty term into loss function, the smoothness of DVF is improved. Finally, we carried out experiments on OASIS, LPBA40, MGH10, and MM-WHS open datasets to validate the effectiveness of TransDIR. Compared with LapIRN, the DSC score is improved by 1.1% and 0.9% on OASIS and LPBA40, separately. In addition, compared with VoxelMorph, the DSC score is improved by 2.8% on the basis of the folding index decreased by hundreds of times on MM-WHS. The results show that the TransDIR achieves robust registration and promising generalizability compared with LapIRN and VoxelMorph.

Period Determination in Cyclo-Stationary Signals by Autocorrelation and Ramanujan Subspaces

Period determination in a periodic-like signal is a challenging process, if the signal is contaminated with a noise or noise-like interference signals. In this work, multiple period determination was considered in aforementioned signals. Recently, cyclostationary properties of the periodic-like signals were utilized to determine the time-varying autocorrelation function (TVAC). First we proved that TVAC can be expressed in terms of Ramanujan sums, then we used TVAC in the periodicity metric to identify the periods. Periodicity metric provides energy distribution of each periodic component as a function of block folding index and reaches a maximum at the points representing the hidden periods in the signal. Proposed method was verified by artificial signals and mean estimation errors versus signal to noise ratio were illustrated. Finally, hidden periods in the noisy respiration signals were estimated by the proposed method successfully.

Formation mechanisms and rules of typical types of folding defects during die forging

Folding defect is one of the most important forging defects, which can deteriorate the surface quality, mechanical properties, and material utilization of forged parts. In this work, the common folding defects in die forging were classified into three typical types: local-loading-type folding, confluence-type folding, and bending-type folding. Three simple Eigen experiments were employed to analyze the formation mechanisms and rules of three typical types of folding accordingly. By FE simulation, the formation mechanisms of three typical types of folding defects were analyzed based on the evolution of the velocity field. In addition, the effects of geometric and forging parameters on each type of folding defect were investigated by uniform experiment design. Especially, a quantitative folding index was applied to uniformly evaluate the formation possibility and severity of folding defect for any samples whether producing folding or not. It is found that the local-loading-type folding is produced by the formation and collapse of a step, which is sensitive to the reduction amount but insensitive to the feed amount. The confluence-type folding is formed due to the local lack of material, which is sensitive to the reduction degree and insensitive to the rib width and billet height in this work. The bending-type folding is mainly formed by the geometric instability of workpiece during the forming process, which is sensitive to the reduction degree and insensitive to the geometric parameters of billet.

Study on the Core Groups of First Integrals and Folding Index for Mechanical Systems

In applying the Udwadia–Kalaba equation for constrained mechanical systems, a direct proof of the equivalence of first integrals and nonholonomic constraints is given, and it is demonstrated that the generalized force of the system is equivalent to the constraint force derived by all first integrals of the nonholonomic constraints. Furthermore, depending on whether complete information is included in the subsets of the first integrals or not, the concept of “multiple kernel” of the system is introduced, and then the core groups of the first integrals and the folding index, which reveals the “simplicity” of the system, are defined. Finally, the onefold system is discussed in detail, and the judgment method is given. To verify the feasibility of this method and illustrate the application of the multiple kernel theory, three examples are considered. The new concepts and results presented in this paper help reveal the inner structure of the general mechanical system, which forms the foundation of control theory of constraint motions, and the multiple kernel analysis of the complex systems can be a new research area of analytic mechanics in the future.

Preparation and properties of tungsten-doped VO2 microcapsule intelligent temperature-control packaging paper

Because of their insufficient temperature-control and waterproof property, traditional thermal-insulation materials cannot accurately control the temperature range and cannot be used for the protection of chemicals, precision instruments, and other items. In this study, waterborne acrylic resin was used as the main film former, and tungsten-doped vanadium dioxide microcapsules (PCMs/W-VO2) were used as the filler. The PCMs/W-VO2 intelligent temperature-control waterborne coating was prepared by supplementing with a flatting agent, organosilicon waterproofing agent, and other agents. The PCMs/W-VO2 intelligent temperature-control packaging paper was made by applying a waterborne coating on an ivory board. The morphology, structure, and phase-change properties of the samples were analyzed using SEM, FTIR, DSC, XRD, EDS and other techniques. And the thermal-insulation temperature difference, contact angle (CA), and mechanical properties were also tested. The results show that the prepared packaging paper had a phase-change temperature at 45 °C, the infrared light reflectance increased by 32%, and the thermal-insulation temperature difference reached 10.7 °C, showing excellent thermal-insulation temperature-control property. The XRD and EDS show that the surface of intelligent temperature-control packaging paper contains PCMs/W-VO2 microcapsules and organosilicon waterproofing agent. The SEM images show that the microcapsules were evenly distributed on the paper surface. CA analysis shows that the contact angle increased significantly, indicating that the paper sheet had good hydrophobicity. The physical properties of the paper sheet were also improved, and considering the economic factors of intelligent temperature-control coatings, the optimum tensile index, tearing index, burst index and folding index were 6.84 kN/m, 22.69 mN·m2/g, 3.60 kPa·m2 g−1 and 188 times (Resolation: 14.7 N), respectively.

Prediction of the folding defect in die forging: A versatile approach for three typical types of folding defects

The folding defect is one of the most common flow-induced defects in the die forging, and the prediction of folding defects is of great significance in product and processing design. To this end, a versatile approach for the prediction of three typical types of folding defects was developed in this work. Firstly, the folding defects in die forging are classified into three types: confluence-type, bending-type, and local-loading-type, according to the material flow characteristics during their development. Then, three simple Eigen experiments and the corresponding FE models are developed to capture the formation processes of these three typical of folding types. On these bases, a versatile prediction approach is established and verified for all three typical folding defect types. This approach is realized by combining a folding index, judging criteria, and a mathematical model relating the folding index and formation parameters. A folding index based on the integration of the strain rate over the free surface of workpiece is proposed, which can evaluate the risk of all three typical types of folding. The corresponding judging criteria for folding defects based on folding index are determined by multiple uniform experiments for each type of folding defects. The mathematical model relating the folding index and forging parameters can be developed by common metamodeling techniques based on FE simulation results; the response surface methodology is employed as an example in this work. Compared to informed folding prediction methods, the present approach presents the following main advantages: (1) wider application scope to all typical types of folding in die forging, (2) no geometrical parameter dependence, (3) the ability to apply the folding index not only to predict folding defects, but also to serve as an objective function to optimize forging parameters to minimize the risk of folding. The results will provide an important tool for the workpiece and processing design to improve the forming quality during die forging.

ФУНКЦІОНАЛЬНИЙ СТАН ЯЄЧНИКІВ НА ТРЕТЮ – ЧЕТВЕРТУ ДОБУ ПІСЛЯ ПОЛОГІВ

Мета дослідження – вивчення гормональної функції яєчників у здорових жінок на 3–4-ту добу після фізіологічних пологів шляхом визначення показників кольпоцитологічного дослідження.Матеріали та методи. Обстежено 100 жінок із необтяженим перебігом післяпологового періоду. Контролем слугували дані обстеження 30 здорових невагітних жінок у динаміці менструального циклу. Під час підрахунку в мазку епітеліальних клітин розраховували стандартні індекси і враховували фон мазка. Підраховували такі індекси: індекс дозрівання (ІД), каріопікнотичний індекс (КІ), еозинофільний індекс (ЕІ), індекс складчатості й індекс скупченості. Ми також враховували фон кольпоцитологічного мазка, а саме – наявність елементів, які можуть заважати дослідженню чи вказувати на порушення мікроекології піхви. До таких елементів ми зараховували лейкоцити, коки, палички, еритроцити, наявність цитолізу і фон мазка: слабо мутний, мутний.Результати дослідження та їх обговорення. Аналіз кольпоцитограм у здорових жінок на 3–4-ту добу після пологів показав, що в умовах різкого падіння рівня гормонів, пов’язаного з пологами і припиненням гормональної діяльності плаценти, з’являється новий тип піхвових мазків – післяпологовий. За кількістю проміжних і поверхневих клітин на 3–4-ту добу після пологів піхвовий мазок найбільш схожий на мазки у здорових невагітних жінок на 7-му добу менструального циклу. Показники ІД у пацієнток основної групи достовірно (р<0,05) різняться від кольпоцитологічних висновків у здорових невагітних жінок і вказують на низьку естрогенну насиченість жіночого організму на 3–4-ту добу після пологів. Для цього типу мазків характерна наявність клітин усіх шарів епітелію піхви, які підлягають у перші дні післяпологового періоду десквамації і деструкції. Для даного типу мазків характерні відсоткові показники кольпоцитологічних індексів у межах: ІД (3,4±1,8/69,0±4,7/27,6±4,5), КІ (29,7±4,6) і ЕІ (15,7±3,6). Таким жінкам властиве переважання слабкої («+») і помірної («++») вираженості індексу складчатості – 74,5 % й індексу скупченості – 71,0 %, що вказує на вкрай низький рівень прогестероної насиченості організму породіль у цей період.Висновки. 1. В умовах різкого падіння рівня гормонів, пов’язаного з пологами і припиненням гормональної діяльності плаценти, з’являється новий тип піхвових мазків – післяпологовий. 2. Для цього типу мазків характерна наявність клітин усіх шарів епітелію піхви, які підлягають у перші дні післяпологового періоду десквамації і деструкції. Для даного типу мазків характерні відсоткові показники кольпоцитологічних індексів у межах: ІД (3,4±1,8/69,0±4,7/27,6±4,5), КІ (29,7±4,6) і ЕІ (15,7±3,6). 3. У таких жінок переважає слабка («+») і помірна («++») вираженість індексу складчатості – 74,5 % й індексу скупченості – 71,0 %, що вказує на вкрай низький рівень прогестеронової насиченості організму породіль у цей період. 4. Для післяпологових кольпоцитологічних мазків характерний також такий фон мазка: підвищена кількість лейкоцитів, різке зниження представників нормальної флори (коки, палички). 5. Отримані результати вказують на незахищеність пологових шляхів жінки після пологів і наявний високий ризик гнійно-запальних ускладнень у цей період.

Neuroanatomical substrate of noise sensitivity

Recent functional studies suggest that noise sensitivity, a trait describing attitudes towards noise and predicting noise annoyance, is associated with altered processing in the central auditory system. In the present work, we examined whether noise sensitivity could be related to the structural anatomy of auditory and limbic brain areas. Anatomical MR brain images of 80 subjects were parcellated with FreeSurfer to measure grey matter volume, cortical thickness, cortical area and folding index of anatomical structures in the temporal lobe and insular cortex. The grey matter volume of amygdala and hippocampus was measured as well. According to our findings, noise sensitivity is associated with the grey matter volume in the selected structures. Among those, we propose and discuss particular areas, previously linked to auditory perceptual, emotional and interoceptive processing, in which larger grey matter volume seems to be related to higher noise sensitivity.

Formation mechanism, prediction and control of the forming defects in transitional region during local loading forming of Ti-alloy rib-web component

Abstract Predicting and controlling the forming defects in transitional region are two key problems needed to be solved in the isothermal local loading forming of Ti-alloy rib-web component. To this end, the authors have conducted systematic works, which are reviewed here. First, according to the structural features of large-scale rib-web component, the finite element (FE) model of transitional region was established and validated by physical experiment. Then, the material flow and deformation inhomogeneity of transitional region are quantitatively studied by the FE model. In addition, the formation mechanisms of forming defects were revealed. Subsequently, an adaptive folding index was proposed to measure the severity of folding defect, based on which a quick prediction model of the folding defect was developed. Finally, the forming limit considering the forming defects in transitional region was determined by the stepwise searching method combined with the defect prediction model.

Multi-parameter machine learning approach to the neuroanatomical basis of developmental dyslexia.

Despite decades of research, the anatomical abnormalities associated with developmental dyslexia are still not fully described. Studies have focused on between-group comparisons in which different neuroanatomical measures were generally explored in isolation, disregarding potential interactions between regions and measures. Here, for the first time a multivariate classification approach was used to investigate grey matter disruptions in children with dyslexia in a large (N = 236) multisite sample. A variety of cortical morphological features, including volumetric (volume, thickness and area) and geometric (folding index and mean curvature) measures were taken into account and generalizability of classification was assessed with both 10-fold and leave-one-out cross validation (LOOCV) techniques. Classification into control vs. dyslexic subjects achieved above chance accuracy (AUC = 0.66 and ACC = 0.65 in the case of 10-fold CV, and AUC = 0.65 and ACC = 0.64 using LOOCV) after principled feature selection. Features that discriminated between dyslexic and control children were exclusively situated in the left hemisphere including superior and middle temporal gyri, subparietal sulcus and prefrontal areas. They were related to geometric properties of the cortex, with generally higher mean curvature and a greater folding index characterizing the dyslexic group. Our results support the hypothesis that an atypical curvature pattern with extra folds in left hemispheric perisylvian regions characterizes dyslexia. Hum Brain Mapp 38:900-908, 2017. © 2016 Wiley Periodicals, Inc.