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In order to study the influence of moisture on seepage characteristics of coal during the complete stress-strain process, the complete stress-strain process with seepage experiment of dry coal sample and full-water coal sample were carried out, and the complete stress-strain characteristics and permeability evolution laws of two coal samples were analyzed. The experimental results showed that the complete stress-strain curve of dry coal sample had five stages, while the full-water coal sample had only four stages. After the peak stress destruction, the axial stress of full-water coal sample fell by 36.82%, and the strain softening phase disappeared in the full stress-strain curve. Compared with dry coal samples, the compressive strength, elastic modulus and peak stress of saturated coal samples decreased by 8.95%, 8.54%, 8.90% and 10.87% respectively. The permeability of dry coal sample increases with the increase of axial strain, and the relationship is linear. The relationship between permeability and strain of saturated coal sample has obvious stages, which can be divided into stable seepage stage and rapid seepage stage. The existence of water will inhibit the gas seepage process of coal body, so the drainage of coal seam should be paid attention to in the gas extraction project.

Abstract INTRODUCTION The development and progression of Alzheimer's disease (AD) is a complex process, during which genetic influences on phenotypes may also change. Incorporating longitudinal phenotypes in genome‐wide association studies (GWAS) could unmask these genetic loci. METHODS We conducted a longitudinal GWAS using a varying coefficient test to identify age‐dependent single nucleotide polymorphisms (SNPs) in AD. Data from 1877 Alzheimer's Neuroimaging Data Initiative participants, including impairment status and amyloid positron emission tomography (PET) scan standardized uptake value ratio (SUVR) scores, were analyzed using a retrospective varying coefficient mixed model association test (RVMMAT). RESULTS RVMMAT identified 244 SNPs with significant time‐varying effects on AD impairment status, with 12 SNPs on chromosome 19 validated using National Alzheimer's Coordinating Center data. Age‐stratified analyses showed these SNPs’ effects peaked between 70 and 80 years. Additionally, 73 SNPs were linked to longitudinal amyloid accumulation changes. Pathway analyses implicated immune and neuroinflammation‐related disruptions. DISCUSSION Our findings demonstrate that longitudinal GWAS models can uncover time‐varying genetic signals in AD. Highlights Identify time‐varying genetic effects using a longitudinal GWAS model in AD. Illustrate age‐dependent genetic effects on both diagnoses and amyloid accumulation. Replicate time‐varying effect of APOE in a second dataset.

Steam pretreatment at high temperatures enables fresh bamboo to possess antifungal and antiseptic properties. The process produces a large amount of wastewater that urgently needs to be recycled. Soluble bio-tars derived from wastewater under low-temperature (LTS-tar) and high-temperature (HTS-tar) steam pretreatments of moso bamboo were studied with a thermogravimetric analyzer coupled with Fourier transform infrared spectroscopy (TG–FTIR) and pyrolysis–gas-chromatography/mass spectrometry (Py–GC/MS). Thermogravimetric analysis showed that in the three stages of the thermal decomposition process, the final residue of the bamboo and HTS-tar had two main peaks of 0.88 wt% and 6.85 wt%. The LTS-tar had much more complicated thermal decomposition behavior, with six steps and a high residue yield of 23.86 wt%. A large quantity of CH4 was observed at the maximum mass loss rates of the bamboo and bio-tars. Acids, aldehydes, ketones, esters, and phenolic compounds were found in the pyrolysis products of the bamboo and soluble bio-tars. Both bio-tars contained carbohydrates and lignin fragments, but the LTS-tar under mild steam conditions had more saccharides and was much more sensitive to temperature. The lignin in the bamboo degraded under harsh steam conditions, resulting in high aromatic and polymeric features for the HTS-tar. The significant differences between LTS-tar and HTS-tar require different techniques to achieve the resource utilization of wastewater in the bamboo industry.

We present a protocol that combines the support vector machine (SVM) model with accurate 13C chemical shift calculations at the xOPBE/6-311+G­(2d,p) level of theory, denoted as SVM-M (i.e., SVM for magnetic property). We show here that this SVM-M protocol is a versatile tool for identifying the structural and stereochemical assignment of complex organic compounds with high confidence. Of particular significance is that, by utilizing the dual role of the decision values in SVM, the present SVM-M protocol provides an accurate yet efficient solution to simultaneously handle the classification issue (i.e., “is a given structure correct or incorrect?”) and the comparison-based problem (i.e., “which structure is more likely to be correct or wrong among several candidate structures?”). A significantly high success rate has been reached (i.e., ∼100% on a set of 760 sample molecules with 15928 13C chemical shifts), which makes the SVM-M protocol a powerful tool for routine applications in structural and stereochemical assignments, as well as in detecting mis-assignments, for complex organic compounds, including natural products.

Wood is an abundant biomaterial and widely used in construction and furniture. Timber processing produces large amounts of residues and byproducts, which are of low value. In this study, we proposed a new strategy for the recycle of wood residues to prepare a wood porous molding material. A hydrated thermochemical grinding process followed by high-temperature and high-pressure refining was developed to convert wood powder into high-viscosity suspension. Lignocellulosic raw materials, including pine wood, beech wood, and bamboo, were compared with different grinding time. A porous material without the addition of synthetic adhesive was obtained with a density in the range of 0.28–0.67 g/cm3. The porous molding material was characterized based on fiber morphology, volume, and porosity and mechanical performance. Pores of different sizes were distributed in the samples randomly after curing and drying. The wood’s own bindings were released through the hydrated thermochemical grinding process. The porous sample made from bamboo with a grinding time of 6 h showed a high Young’s modulus (681.1 MPa), compactness (166.8 N/Sec), and hardness (517.6 N). Woody materials were more readily made into moldings since most of the cellulose crystal structure remained intact. The wood porous moldings are fully composed of lignocellulosic components and easy to recycle. This porous green material has great potential to be applied to insulation, ceiling, cabinet, and packaging.

In neurons the membrane-associated periodic skeleton (MPS) consists of actin, spectrin, and associated molecules. Here the authors use proteomic analysis and super-resolution imaging to provide insight into the molecular composition and organization of the MPS, and its functions in axon-diameter regulation and neurite-neurite interactions.

Abstract Background An aging society has increased rates of late onset Alzheimer disease dementia (ADD), the most common form of age-related dementia. This neurodegenerative disease disproportionately affects women. Methods We use data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to examine sex differences in cortical thickness (CT) and memory performance. Analyses of covariance (ANCOVA) models were used to examine effects of sex and diagnosis (DX) on CT and verbal memory. For regions demonstrating significant interaction effects of sex and DX, we tested whether sex moderated cognition-thickness relationships. We used machine learning as a complementary method to explore multivariate CT differences between women and men. Results Women demonstrated greater CT in many brain regions. More specifically, men showed relatively consistent CT declines in all stages, from normal control (NC) to ADD in the bilateral cingulate cortex, bilateral temporal regions, and left precuneus; women had more stable CT in these regions between NC and mild cognitive impairment (MCI) stages, but sharper declines from MCI to ADD. Similarly, for the Rey Auditory Verbal Learning Test (RAVLT), ANCOVA analyses showed that women had significantly better immediate and delayed recall scores than men, at NC and MCI stages, but greater differences, cross-sectionally, from MCI to ADD than men. We found significant sex moderation effects between RAVLT-immediate scores and CT of right isthmus-cingulate for all subjects across DX. Partial correlation analyses revealed that increased CT of right isthmus-cingulate was associated with better verbal learning in women, driven by positron emission tomography defined amyloid positive (Aβ+) subjects. Significant sex-moderation effects in cognition-thickness relationships were further found in the right middle-temporal, left precuneus, and left superior temporal regions in Aβ+ subjects. Using a machine learning approach, we investigated multivariate CT differences between women and men, showing an accuracy in classification of 75% for Aβ+ cognitively NC participants. Conclusions Sex differences in memory and CT can play a key role in the different vulnerability and progression of ADD in women compared to men. Machine learning indicates sex differences in CT are most relevant early in the ADD neurodegeneration.

Abstract The accuracy of expansion microscopy (ExM) depends on the structural preservation of samples embedded in a hydrogel. However, it has been unknown to what extent gel embedding alters the molecular positions of individual labeled sites. Here, we quantified the accuracy of gel embedding by using stochastic optical reconstruction microscopy (STORM) to image DNA origami with well-defined structures. We found that embedding in hydrogels based on polyacrylamide, the most widely used chemistry in ExM, resulted in random displacements of labeled sites with a standard deviation of ~ 16 nm. In contrast, we found that embedding in tetra-gel, a hydrogel that does not depend on free-radical chain-growth polymerization, preserved labeled sites with a standard deviation of less than 5 nm. By combining tetra-gel ExM with STORM, we were able to resolve 11-nm structural features without the loss in accuracy seen with polyacrylamide gels. Our study thus provides direct measurements of the single-molecule distortions resulting from hydrogel embedding, and presents a way to improve super-resolution microscopy through combination with tetra-gel ExM.

Traditionally, functional networks in resting-state data were investigated with linear Fourier and wavelet-related methods to characterize their frequency content by relying on pre-specified frequency bands. In this study, Empirical Mode Decomposition (EMD), an adaptive time-frequency method, is used to investigate the naturally occurring frequency bands of resting-state data obtained by Group Independent Component Analysis. Specifically, energy-period profiles of Intrinsic Mode Functions (IMFs) obtained by EMD are created and compared for different resting-state networks. These profiles have a characteristic distribution for many resting-state networks and are related to the frequency content of each network. A comparison with the linear Short-Time Fourier Transform (STFT) and the Maximal Overlap Discrete Wavelet Transform (MODWT) shows that EMD provides a more frequency-adaptive representation of different types of resting-state networks. Clustering of resting-state networks based on the energy-period profiles leads to clusters of resting-state networks that have a monotone relationship with frequency and energy. This relationship is strongest with EMD, intermediate with MODWT, and weakest with STFT. The identification of these relationships suggests that EMD has significant advantages in characterizing brain networks compared to STFT and MODWT. In a clinical application to early Parkinson’s disease (PD) vs. normal controls (NC), energy and period content were studied for several common resting-state networks. Compared to STFT and MODWT, EMD showed the largest differences in energy and period between PD and NC subjects. Using a support vector machine, EMD achieved the highest prediction accuracy in classifying NC and PD subjects among STFT, MODWT, and EMD.

Neural complexity and brain entropy (BEN) have gained greater interest in recent years. The dynamics of neural signals and their relations with information processing continue to be investigated through different measures in a variety of noteworthy studies. The BEN of spontaneous neural activity decreases during states of reduced consciousness. This evidence has been showed in primary consciousness states, such as psychedelic states, under the name of “the entropic brain hypothesis.” In this manuscript we propose an extension of this hypothesis to physiological and pathological aging. We review this particular facet of the complexity of the brain, mentioning studies that have investigated BEN in primary consciousness states, and extending this view to the field of neuroaging with a focus on resting-state functional Magnetic Resonance Imaging. We first introduce historic and conceptual ideas about entropy and neural complexity, treating the mindbrain as a complex nonlinear dynamic adaptive system, in light of the free energy principle. Then, we review the studies in this field, analyzing the idea that the aim of the neurocognitive system is to maintain a dynamic state of balance between order and chaos, both in terms of dynamics of neural signals and functional connectivity. In our exploration we will review studies both on acute psychedelic states and more chronic psychotic states and traits, such as those in schizophrenia, in order to show the increase of entropy in those states. Then we extend our exploration to physiological and pathological aging, where BEN is reduced. Finally, we propose an interpretation of these results, defining a general trend of BEN in primary states and cognitive aging.

Chromatin remodelling enzymes (remodellers) regulate DNA accessibility of eukaryotic genomes, which rely in large part on an ability to reposition nucleosomes. Here the authors use three-colour single-molecule FRET to simultaneously monitor remodeller-induced DNA movements on both sides of the nucleosome in real-time.

Light is one of the most adverse factors for bamboo deterioration and causes surface degradation and discoloration. The study was carried out to initiate efficient and effective photodiscoloration to modify and enrich bamboo colors that may be applied to bamboo dyeing. Different types of bamboo samples commonly used in the industry were studied experimentally under two types of ultraviolet (UV) light. Effects of light sources, radiation time, and distances on discoloration and discoloration mechanism were systematically studied. For both UV 313 and high-pressure mercury light, the bamboo surface turned red-yellow, and color parameters including ΔE, Δa, Δb, and C rapidly increased first and then stabilized for long time, while ΔL showed a similar trend, except for the final decrease. Compared with UV 313, high-pressure mercury lamp light was highly efficient and took less time to induce discoloration. Heat treatments darkened the bamboo color and slowed down photodiscoloration, and the higher temperature led to more photostability. The color change of bamboo scrimber under UV radiation was less and slower than that of untreated bamboo due to high density and heat treatment, and the dark carbonized scrimber changed less than that of the light carbonized scrimber. Relatively high contents of isovanillin, syringaldehyde, β-hydroxypropiovanillone, p-hydroxybenzaldehyde, and syringic acid were identified by GC-MS, and syringaldehyde, 2,6-dimethylbenzoquinone, and 3-hydroxy-4-methoxybenzoic acid were identified by HPLC-MS from a bamboo discoloration layer after high-pressure mercury lamp radiation. These products all contained a conjugated double bond and were conjectured to be degraded from lignin or aromatic extracts. Particularly, 2,6-dimethylbenzoquinone which contained a cyclohexenedione structure without benzene rings, was more chemically stable than other conjugated double bonds with benzene rings, and was supposed to be the final product (chromogenic group) during bamboo photodegradation. Untreated or light-colored bamboo under high-energy UV light initiated highly efficient and effective photodiscoloration, and UV light is recommended for being applied to industrial bamboo dyeing. Compared with traditional chemical dyeing, the photoinduced dyeing method has no chemical addition and is easy to operate and environmental-friendly.

Bamboo timber (BT) is a kind of natural porous material, and usually bamboo cracking and deformation are caused by the change of humidity in the environment. Inspired by the natural structure of the shell, a multilayer structure was designed to fabricate a kind of graphene/silica composite coating on the BT surface. The multilayer bamboo composite (FAS-RGO@SiO2BT) was prepared by using the self-assembly process of nanospherical silica on graphene followed by hydrophobic modification. A possible formation mechanism of FAS-RGO@SiO2BT was discussed by X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy. The FAS-RGO@SiO2BT has excellent hydrophobic properties for tea, orange juice, milk, coffee, blue ink, red wine, and green juice. Also, the FAS-RGO@ SiO2BT has an obvious hydrophobic effect on any of the various solutions with a pH of 1 to 14. In addition, after a 90-day immersion test, the water absorption rate of FAS-RGO@ SiO2BT is 9.7% and the thickness swelling rate is 0.5%. The wettability and dimensional stability of the FAS-RGO@SiO2BT are significantly improved compared to those of BT.

Previous neuroimaging studies have identified structural brain abnormalities in active professional fighters with repetitive head trauma and correlated these changes with fighters' neuropsychological impairments. However, functional brain changes in these fighters derived using neuroimaging techniques remain unclear. In this study, both static and dynamic functional connectivity alterations were investigated (1) between healthy normal control subjects (NC) and fighters and (2) between non-impaired and impaired fighters. Resting-state fMRI data were collected on 35 NC and 133 active professional fighters, including 68 impaired fighters and 65 non-impaired fighters, from the Professional Fighters Brain Health Study at our center. Impaired fighters performed worse on processing speed (PSS) tasks with visual-attention and working-memory demands. The static functional connectivity (sFC) matrix was estimated for every pair of regions of interest (ROI) using a subject-specific parcellation. The dynamic functional connectivity (dFC) was estimated using a sliding-window method, where the variability of each ROI pair across all windows represented the temporal dynamics. A linear regression model was fitted for all 168 subjects, and different t-contrast vectors were used for between-group comparisons. An association analysis was further conducted to evaluate FC changes associated with PSS task performances without creating artificial impairment group-divisions in fighters. Following corrections for multiple comparisons using network-based statistics, our study identified significantly reduced long-range frontal-temporal, frontal-occipital, temporal-occipital, and parietal-occipital sFC strengths in fighters than in NCs, corroborating with previously observed structural damages in corresponding white matter tracts in subjects experiencing repetitive head trauma. In impaired fighters, significantly decreased sFC strengths were found among key regions involved in visual-attention, executive and cognitive process, as compared to non-impaired fighters. Association analysis further reveals similar sFC deficits to worse PSS task performances in all 133 fighters. With our choice of dFC indices, we were not able to observe any significant dFC changes beyond a trend-level increased temporal variability among similar regions with weaker sFC strengths in impaired fighters. Collectively, our functional brain findings supplement previously reported structural brain abnormalities in fighters and are important to comprehensively understand brain changes in fighters with repetitive head trauma.

Functional MRI (fMRI) is a prominent imaging technique to probe brain function, however, a substantial proportion of noise from multiple sources influences the reliability and reproducibility of fMRI data analysis and limits its clinical applications. Extensive effort has been devoted to improving fMRI data quality, but in the last two decades, there is no consensus reached which technique is more effective. In this study, we developed a novel deep neural network for denoising fMRI data, named denoising neural network (DeNN). This deep neural network is 1) applicable without requiring externally recorded data to model noise; 2) spatially and temporally adaptive to the variability of noise in different brain regions at different time points; 3) automated to output denoised data without manual interference; 4) trained and applied on each subject separately and 5) insensitive to the repetition time (TR) of fMRI data. When we compared DeNN with a number of nuisance regression methods for denoising fMRI data from Alzheimer's Disease Neuroimaging Initiative (ADNI) database, only DeNN had connectivity for functionally uncorrelated regions close to zero and successfully identified unbiased correlations between the posterior cingulate cortex seed and multiple brain regions within the default mode network or task positive network. The whole brain functional connectivity maps computed with DeNN-denoised data are approximately three times as homogeneous as the functional connectivity maps computed with raw data. Furthermore, the improved homogeneity strengthens rather than weakens the statistical power of fMRI in detecting intrinsic functional differences between cognitively normal subjects and subjects with Alzheimer's disease.

During the past ten years, dynamic functional connectivity (FC) has been extensively studied using the sliding-window method. A fixed window-size is usually selected heuristically, since no consensus exists yet on choice of the optimal window-size. Furthermore, without a known ground-truth, the validity of the computed dynamic FC remains unclear and questionable. In this study, we computed single-scale time-dependent (SSTD) window-sizes for the sliding-window method. SSTD window-sizes were based on the frequency content at every time point of a time series and were computed without any prior information. Therefore, they were time-dependent and data-driven. Using simulated sinusoidal time series with frequency shifts, we demonstrated that SSTD window-sizes captured the time-dependent period (inverse of frequency) information at every time point. We further validated the dynamic FC values computed with SSTD window-sizes with both a classification analysis using fMRI data with a low sampling rate and a regression analysis using fMRI data with a high sampling rate. Specifically, we achieved both a higher classification accuracy in predicting cognitive impairment status in fighters and a larger explained behavioral variance in healthy young adults when using dynamic FC matrices computed with SSTD window-sizes as features, as compared to using dynamic FC matrices computed with the conventional fixed window-sizes. Overall, our study computed and validated SSTD window-sizes in the sliding-window method for dynamic FC analysis. Our results demonstrate that dynamic FC matrices computed with SSTD window-sizes can capture more temporal dynamic information related to behavior and cognitive function.

In this study, we developed a multi-scale Convolutional neural network based Automated hippocampal subfield Segmentation Toolbox (CAST) for automated segmentation of hippocampal subfields. Although training CAST required approximately three days on a single workstation with a high-quality GPU card, CAST can segment a new subject in less than 1 ​min even with GPU acceleration disabled, thus this method is more time efficient than current automated methods and manual segmentation. This toolbox is highly flexible with either a single modality or multiple modalities and can be easily set up to be trained with a researcher’s unique data. A 3D multi-scale deep convolutional neural network is the key algorithm used in the toolbox. The main merit of multi-scale images is the capability to capture more global structural information from down-sampled images without dramatically increasing memory and computational burden. The original images capture more local information to refine the boundary between subfields. Residual learning is applied to alleviate the vanishing gradient problem and improve the performance with a deeper network. We applied CAST with the same settings on two datasets, one 7T dataset (the UMC dataset) with only the T2 image and one 3T dataset (the MNI dataset) with both T1 and T2 images available. The segmentation accuracy of both CAST and the state-of-the-art automated method ASHS, in terms of the dice similarity coefficient (DSC), were comparable. CAST significantly improved the reliability of segmenting small subfields, such as CA2, CA3, and the entorhinal cortex (ERC), in terms of the intraclass correlation coefficient (ICC). Both ASHS and manual segmentation process some subfields (e.g. CA2 and ERC) with high DSC values but low ICC values, consequently increasing the difficulty of judging segmentation quality. CAST produces very consistent DSC and ICC values, with a maximal discrepancy of 0.01 (DSC-ICC) across all subfields. The pre-trained model, source code, and settings for the CAST toolbox are publicly available.

Women are more likely to have Alzheimer's disease (AD) and decline more rapidly once diagnosed despite greater verbal memory early in the disease compared to men—an advantage that has been termed “memory reserve.” Resting state functional MRI (fMRI) investigations demonstrate interactions between sex and AD risk factors in default mode network (DMN) connectivity, a network of brain regions showing progressive dysfunction in AD. Separate work suggests connectivity of left prefrontal cortex (PFC) may correlate with more general cognitive reserve in healthy aging. It is unknown whether left prefrontal functional connectivity with anterior and posterior default mode network (aDMN, pDMN) might differ by sex in AD. This study employed group independent component analysis (ICA) to analyze resting state fMRI data from 158 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with baseline diagnoses of normal cognition or early mild cognitive impairment (eMCI). pDMN and aDMN were defined on a subject-specific basis; prefrontal areas were selected from the Brodmann atlas (BA 6, 44, 8, and 9). Moderation regression analyses examined whether sex and amyloid PET positivity (A+/–) moderated effects of apolipoprotein ε4 (APOE ε4) on connectivity between left PFC, aDMN, and pDMN; and between aDMN and pDMN. Significant analyses were followed up with partial correlations assessing relationship of connectivity to verbal memory on the Rey Auditory Verbal Learning Test (RAVLT), and with preliminary analyses within NC and eMCI groups separately. Results showed no sex moderation of effects of A+ and APOE ε4 on left prefrontal/DMN connectivity in the full sample. However, sex significantly moderated impact of A+ and APOE ε4 on connectivity between aDMN and pDMN (p < 0.01). Women with an APOE allele (ε4+) and A+ showed greater aDMN/pDMN connectivity than their ε4- counterparts. No significant results were observed in men. Subgroup analyses suggested the aDMN/pDMN finding was true for those with NC, not eMCI. Partial correlations controlling for age and education showed increased aDMN/pDMN connectivity related to better verbal learning in women (p < 0.01) and not men (p = 0.18). In women at risk for AD or in early symptomatic stages who also have evidence of amyloid burden, stronger aDMN/pDMN connectivity may support verbal learning.

Repeated head trauma experienced by active professional fighters results in various structural, functional and perfusion damage. However, whether there are common regions of structural and perfusion damage due to fighting and whether these structural and perfusion differences are associated with neuropsychological measurements in active professional fighters is still unknown. To that end, T1-weighted and pseudocontinuous arterial spin labeling MRI on a group of healthy controls and active professional fighters were acquired. Voxelwise group comparisons, in a univariate and multivariate sense, were performed to investigate differences in gray and white matter density (GMD, WMD) and cerebral blood flow (CBF) between the two groups. A significantly positive association between global GMD and WMD was obtained with psychomotor speed and reaction time, respectively, in our cohort of active professional fighters. In addition, regional WMD deficit was observed in a cluster encompassing bilateral pons, hippocampus, and thalamus in fighters (0.49±0.04 arbitrary units (a.u.)) as compared to controls (0.51±0.05a.u.). WMD in the cluster of active fighters was also significantly associated with reaction time. Significantly lower CBF was observed in right inferior temporal lobe with both partial volume corrected (46.9±14.93ml/100g/min) and non-partial volume corrected CBF maps (25.91±7.99ml/100g/min) in professional fighters, as compared to controls (65.45±22.24ml/100g/min and 35.22±12.18ml/100g/min respectively). A paradoxical increase in CBF accompanying right cerebellum and fusiform gyrus in the active professional fighters (29.52±13.03ml/100g/min) as compared to controls (19.43±12.56ml/100g/min) was observed with non-partial volume corrected CBF maps. Multivariate analysis with both structural and perfusion measurements found the same clusters as univariate analysis in addition to a cluster in right precuneus. Both partial volume corrected and non-partial volume corrected CBF of the cluster in the thalamus had a significantly positive association with the number of fights. In addition, GMD of the cluster in right precuneus was significantly associated with psychomotor speed in our cohort of active professional fighters. Our results suggest a heterogeneous pattern of structural and CBF deficits due to repeated head trauma in active professional fighters. This finding indicates that investigating both structural and CBF changes in the same set of participants may help to understand the pathophysiology and progression of cognitive decline due to repeated head trauma. Keywords: Repeated head trauma, Cerebral blood flow, Cognitive impairment, Neurovascular coupling, Brain morphology

Abstract The resolution of super-resolution microscopy based on single molecule localization is in part determined by the accuracy of the localization algorithm. In most published approaches to date this localization is done by fitting an analytical function that approximates the point spread function (PSF) of the microscope. However, particularly for localization in 3D, analytical functions such as a Gaussian, which are computationally inexpensive, may not accurately capture the PSF shape leading to reduced fitting accuracy. On the other hand, analytical functions that can accurately capture the PSF shape, such as those based on pupil functions, can be computationally expensive. Here we investigate the use of cubic splines as an alternative fitting approach. We demonstrate that cubic splines can capture the shape of any PSF with high accuracy and that they can be used for fitting the PSF with only a 2–3x increase in computation time as compared to Gaussian fitting. We provide an open-source software package that measures the PSF of any microscope and uses the measured PSF to perform 3D single molecule localization microscopy analysis with reasonable accuracy and speed.

Collecting multiple modalities of neuroimaging data on the same subject is increasingly becoming the norm in clinical practice and research. Fusing multiple modalities to find related patterns is a challenge in neuroimaging analysis. Canonical correlation analysis (CCA) is commonly used as a symmetric data fusion technique to find related patterns among multiple modalities. In CCA-based data fusion, principal component analysis (PCA) is frequently applied as a preprocessing step to reduce data dimension followed by CCA on dimension-reduced data. PCA, however, does not differentiate between informative voxels from non-informative voxels in the dimension reduction step. Sparse PCA (sPCA) extends traditional PCA by adding sparse regularization that assigns zero weights to non-informative voxels. In this study, sPCA is incorporated into CCA-based fusion analysis and applied on neuroimaging data. A cross-validation method is developed and validated to optimize the parameters in sPCA. Different simulations are carried out to evaluate the improvement by introducing sparsity constraint to PCA. Four fusion methods including sPCA+CCA, PCA+CCA, parallel ICA and sparse CCA were applied on structural and functional magnetic resonance imaging data of mild cognitive impairment subjects and normal controls. Our results indicate that sPCA significantly can reduce the impact of non-informative voxels and lead to improved statistical power in uncovering disease-related patterns by a fusion analysis.

Axon degeneration sculpts neuronal connectivity patterns during development and is an early hallmark of several adult-onset neurodegenerative disorders. Substantial progress has been made in identifying effector mechanisms driving axon fragmentation, but less is known about the upstream signaling pathways that initiate this process. Here, we investigate the behavior of the actin-spectrin-based Membrane-associated Periodic Skeleton (MPS), and effects of actin and spectrin manipulations in sensory axon degeneration. We show that trophic deprivation (TD) of mouse sensory neurons causes a rapid disassembly of the axonal MPS, which occurs prior to protein loss and independently of caspase activation. Actin destabilization initiates TD-related retrograde signaling needed for degeneration; actin stabilization prevents MPS disassembly and retrograde signaling during TD. Depletion of βII-spectrin, a key component of the MPS, suppresses retrograde signaling and protects axons against degeneration. These data demonstrate structural plasticity of the MPS and suggest its potential role in early steps of axon degeneration.

Diffusion tensor imaging (DTI) studies in early Parkinson's disease (PD) to understand pathologic changes in white matter (WM) organization are variable in their findings. Evaluation of different analytic techniques frequently employed to understand the DTI-derived change in WM organization in a multisite, well-characterized, early stage PD cohort should aid the identification of the most robust analytic techniques to be used to investigate WM pathology in this disease, an important unmet need in the field. Thus, region of interest (ROI)-based analysis, voxel-based morphometry (VBM) analysis with varying spatial smoothing, and the two most widely used skeletonwise approaches (tract-based spatial statistics, TBSS, and tensor-based registration, DTI-TK) were evaluated in a DTI dataset of early PD and Healthy Controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) cohort. Statistical tests on the DTI-derived metrics were conducted using a nonparametric approach from this cohort of early PD, after rigorously controlling for motion and signal artifacts during DTI scan which are frequent confounds in this disease population. Both TBSS and DTI-TK revealed a significantly negative correlation of fractional anisotropy (FA) with disease duration. However, only DTI-TK revealed radial diffusivity (RD) to be driving this FA correlation with disease duration. HC had a significantly positive correlation of MD with cumulative DaT score in the right middle-frontal cortex after a minimum smoothing level (at least 13mm) was attained. The present study found that scalar DTI-derived measures such as FA, MD, and RD should be used as imaging biomarkers with caution in early PD as the conclusions derived from them are heavily dependent on the choice of the analysis used. This study further demonstrated DTI-TK may be used to understand changes in DTI-derived measures with disease progression as it was found to be more accurate than TBSS. In addition, no singular region was identified that could explain both disease duration and severity in early PD. The results of this study should help standardize the utilization of DTI-derived measures in PD in an effort to improve comparability across studies and time, and to minimize variability in reported results due to variation in techniques.

Resting-state functional magnetic resonance imaging (rs-fMRI) based on the blood-oxygen-level-dependent (BOLD) signal has been widely used in healthy individuals and patients to investigate brain functions when the subjects are in a resting or task-negative state. Head motion considerably confounds the interpretation of rs-fMRI data. Nuisance regression is commonly used to reduce motion-related artifacts with six motion parameters estimated from rigid-body realignment as regressors. To further compensate for the effect of head movement, the first-order temporal derivatives of motion parameters and squared motion parameters were proposed previously as possible motion regressors. However, these additional regressors may not be sufficient to model the impact of head motion because of the complexity of motion artifacts. In addition, while using more motion-related regressors could explain more variance in the data, the neural signal may also be removed with increasing number of motion regressors. To better model how in-scanner motion affects rs-fMRI data, a robust and automated convolutional neural network (CNN) model is developed in this study to obtain optimal motion regressors. The CNN network consists of two temporal convolutional layers and the output from the network are the derived motion regressors used in the following nuisance regression. The temporal convolutional layer in the network can non-parametrically model the prolonged effect of head motion. The set of regressors derived from the neural network is compared with the same number of regressors used in a traditional nuisance regression approach. It is demonstrated that the CNN-derived regressors can more effectively reduce motion-related artifacts.

Polycomb Group (PcG) proteins regulate gene expression and genome architecture. Using super-resolution microscopy and molecular simulations, Waniet al. describe the organization of PcG proteins into hundreds of nano-scale protein clusters and suggest these clusters shape genome architecture.

Bamboo is susceptible to mould and attack by fungi because of its high content of starch and sugar. To make bamboo-based outdoor materials, a new type of bamboo timber with improved mould resistance and antibacterial activity, coated with reduced graphene oxide and nanocrystal ZnO (abbreviated as RGO@ZnOBT), was fabricated by a two-step dip-dry and hydrothermal process. A possible synthesis mechanism for RGO@ZnOBT was investigated by X-ray diffraction, scanning electron microscopy, transmission electron microscope, energy-dispersal X-ray analysis, X-ray photoelectron spectroscopy and Fourier-transform infrared spectroscopy. According to the China standard test method, the Aspergillus niger mould resistance of RGO@ZnOBT is grade 2, whereas the Trichoderma viride and Penicillium citrinum mould resistance of RGO@ZnOBT is grade 0, both of which are better than the grade 4 of original bamboo timber. The Escherichia coli resistance test showed that the antibacterial circle of RGO@ZnOBT is 3 mm, which is significantly higher than that of original bamboo timber (0 mm). The antibacterial activity of treated bamboo is significantly improved compared with that of untreated bamboo.

Picornaviruses are non-enveloped RNA viruses that enter cells via receptor-mediated endocytosis. Because they lack an envelope, picornaviruses face the challenge of delivering their RNA genomes across the membrane of the endocytic vesicle into the cytoplasm to initiate infection. Currently, the mechanism of genome release and translocation across membranes remains poorly understood. Within the enterovirus genus, poliovirus, rhinovirus 2, and rhinovirus 16 have been proposed to release their genomes across intact endosomal membranes through virally induced pores, whereas one study has proposed that rhinovirus 14 releases its RNA following disruption of endosomal membranes. For the more distantly related aphthovirus genus (e.g. foot-and-mouth disease viruses and equine rhinitis A virus) acidification of endosomes results in the disassembly of the virion into pentamers and in the release of the viral RNA into the lumen of the endosome, but no details have been elucidated as how the RNA crosses the vesicle membrane. However, more recent studies suggest aphthovirus RNA is released from intact particles and the dissociation to pentamers may be a late event. In this study we have investigated the RNase A sensitivity of genome translocation of poliovirus using a receptor-decorated-liposome model and the sensitivity of infection of poliovirus and equine-rhinitis A virus to co-internalized RNase A. We show that poliovirus genome translocation is insensitive to RNase A and results in little or no release into the medium in the liposome model. We also show that infectivity is not reduced by co-internalized RNase A for poliovirus and equine rhinitis A virus. Additionally, we show that all poliovirus genomes that are internalized into cells, not just those resulting in infection, are protected from RNase A. These results support a finely coordinated, directional model of viral RNA delivery that involves viral proteins and cellular membranes.

We report that the Gm7068 (CatSpere) and Tex40 (CatSperz) genes encode novel subunits of a 9-subunit CatSper ion channel complex. Targeted disruption of CatSperz reduces CatSper current and sperm rheotactic efficiency in mice, resulting in severe male subfertility. Normally distributed in linear quadrilateral nanodomains along the flagellum, the complex lacking CatSperζ is disrupted at ~0.8 μm intervals along the flagellum. This disruption renders the proximal flagellum inflexible and alters the 3D flagellar envelope, thus preventing sperm from reorienting against fluid flow in vitro and efficiently migrating in vivo. Ejaculated CatSperz-null sperm cells retrieved from the mated female uterus partially rescue in vitro fertilization (IVF) that failed with epididymal spermatozoa alone. Human CatSperε is quadrilaterally arranged along the flagella, similar to the CatSper complex in mouse sperm. We speculate that the newly identified CatSperζ subunit is a late evolutionary adaptation to maximize fertilization inside the mammalian female reproductive tract.

Our experiences, even as adults, shape our brains. Regional differences have been found in experts, with the regions associated with their particular skill-set. Functional differences have also been noted in brain activation patterns in some experts. This study uses multimodal techniques to assess structural and functional patterns that differ between experts and nonexperts. Sommeliers are experts in wine and thus in olfaction. We assessed differences in Master Sommeliers’ brains, compared with controls, in structure and also in functional response to olfactory and visual judgment tasks. MRI data were analyzed using voxel-based morphometry as well as automated parcellation to assess structural properties, and group differences between tasks were calculated. Results indicate enhanced volume in the right insula and entorhinal cortex, with the cortical thickness of the entorhinal correlating with experience. There were regional activation differences in a large area involving the right olfactory and memory regions, with heightened activation specifically for sommeliers during an olfactory task. Our results indicate that sommeliers’ brains show specialization in the expected regions of the olfactory and memory networks, and also in regions important in integration of internal sensory stimuli and external cues. Overall, these differences suggest that specialized expertise and training might result in enhancements in the brain well into adulthood. This is particularly important given the regions involved, which are the first to be impacted by many neurodegenerative diseases.

Spatial organization of the transcriptome has emerged as a powerful means for regulating the post-transcriptional fate of RNA in eukaryotes; however, whether prokaryotes use RNA spatial organization as a mechanism for post-transcriptional regulation remains unclear. Here we used super-resolution microscopy to image the E. coli transcriptome and observed a genome-wide spatial organization of RNA: mRNAs encoding inner-membrane proteins are enriched at the membrane, whereas mRNAs encoding outer-membrane, cytoplasmic and periplasmic proteins are distributed throughout the cytoplasm. Membrane enrichment is caused by co-translational insertion of signal peptides recognized by the signal-recognition particle. Time-resolved RNA-sequencing revealed that degradation rates of inner-membrane-protein mRNAs are on average greater that those of the other mRNAs and that this selective destabilization of inner-membrane-protein mRNAs is abolished by dissociating the RNA degradosome from the membrane. Together, these results demonstrate that the bacterial transcriptome is spatially organized and suggest that this organization shapes the post-transcriptional dynamics of mRNAs.

The SWI/SNF-family remodelers regulate chromatin structure by coupling the free energy from ATP hydrolysis to the repositioning and restructuring of nucleosomes, but how the ATPase activity of these enzymes drives the motion of DNA across the nucleosome remains unclear. Here, we used single-molecule FRET to monitor the remodeling of mononucleosomes by the yeast SWI/SNF remodeler, RSC. We observed that RSC primarily translocates DNA around the nucleosome without substantial displacement of the H2A-H2B dimer. At the sites where DNA enters and exits the nucleosome, the DNA moves largely along or near its canonical wrapping path. The translocation of DNA occurs in a stepwise manner, and at both sites where DNA enters and exits the nucleosome, the step size distributions exhibit a peak at approximately 1–2 bp. These results suggest that the movement of DNA across the nucleosome is likely coupled directly to DNA translocation by the ATPase at its binding site inside the nucleosome.

Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM) still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM) and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets.

Actin, spectrin, and associated molecules form a periodic sub-membrane lattice structure in axons. How this membrane skeleton is developed and why it preferentially forms in axons are unknown. Here, we studied the developmental mechanism of this lattice structure. We found that this structure emerged early during axon development and propagated from proximal regions to distal ends of axons. Components of the axon initial segment were recruited to the lattice late during development. Formation of the lattice was regulated by the local concentration of βII spectrin, which is higher in axons than in dendrites. Increasing the dendritic concentration of βII spectrin by overexpression or by knocking out ankyrin B induced the formation of the periodic structure in dendrites, demonstrating that the spectrin concentration is a key determinant in the preferential development of this structure in axons and that ankyrin B is critical for the polarized distribution of βII spectrin in neurites.

As an obligatory pathogen, influenza virus co-opts host cell machinery to harbor infection and to produce progeny viruses. In order to characterize the virus-host cell interactions, several genome-wide siRNA screens and proteomic analyses have been performed recently to identify host factors involved in influenza virus infection. CD81 has emerged as one of the top candidates in two siRNA screens and one proteomic study. The exact role played by CD81 in influenza infection, however, has not been elucidated thus far. In this work, we examined the effect of CD81 depletion on the major steps of the influenza infection. We found that CD81 primarily affected virus infection at two stages: viral uncoating during entry and virus budding. CD81 marked a specific endosomal population and about half of the fused influenza virus particles underwent fusion within the CD81-positive endosomes. Depletion of CD81 resulted in a substantial defect in viral fusion and infection. During virus assembly, CD81 was recruited to virus budding site on the plasma membrane, and in particular, to specific sub-viral locations. For spherical and slightly elongated influenza virus, CD81 was localized at both the growing tip and the budding neck of the progeny viruses. CD81 knockdown led to a budding defect and resulted in elongated budding virions with a higher propensity to remain attached to the plasma membrane. Progeny virus production was markedly reduced in CD81-knockdown cells even when the uncoating defect was compensated. In filamentous virus, CD81 was distributed at multiple sites along the viral filament. Taken together, these results demonstrate important roles of CD81 in both entry and budding stages of the influenza infection cycle.

The connectivity among neurons holds the key to understanding brain function. Mapping neural connectivity in brain circuits requires imaging techniques with high spatial resolution to facilitate neuron tracing and high molecular specificity to mark different cellular and molecular populations. Here, we tested a three-dimensional (3D), multicolor super-resolution imaging method, stochastic optical reconstruction microscopy (STORM), for tracing neural connectivity using cultured hippocampal neurons obtained from wild-type neonatal rat embryos as a model system. Using a membrane specific labeling approach that improves labeling density compared to cytoplasmic labeling, we imaged neural processes at 44 nm 2D and 116 nm 3D resolution as determined by considering both the localization precision of the fluorescent probes and the Nyquist criterion based on label density. Comparison with confocal images showed that, with the currently achieved resolution, we could distinguish and trace substantially more neuronal processes in the super-resolution images. The accuracy of tracing was further improved by using multicolor super-resolution imaging. The resolution obtained here was largely limited by the label density and not by the localization precision of the fluorescent probes. Therefore, higher image resolution, and thus higher tracing accuracy, can in principle be achieved by further improving the label density.

Dengue virus (DENV) is an enveloped RNA virus that causes the most common arthropod-borne infection worldwide. The mechanism by which DENV infects the host cell remains unclear. In this work, we used live-cell imaging and single-virus tracking to investigate the cell entry, endocytic trafficking, and fusion behavior of DENV. Simultaneous tracking of DENV particles and various endocytic markers revealed that DENV enters cells exclusively via clathrin-mediated endocytosis. The virus particles move along the cell surface in a diffusive manner before being captured by a pre-existing clathrin-coated pit. Upon clathrin-mediated entry, DENV particles are transported to Rab5-positive endosomes, which subsequently mature into late endosomes through acquisition of Rab7 and loss of Rab5. Fusion of the viral membrane with the endosomal membrane was primarily detected in late endosomal compartments.

Viruses initiate infection by transferring their genetic material across a cellular membrane and into the appropriate compartment of the cell. The mechanisms by which animal viruses, especially nonenveloped viruses, deliver their genomes are only poorly understood. This is due in part to technical difficulties involved in direct visualization of viral gene delivery and to uncertainties in distinguishing productive and nonproductive pathways caused by the high particle-to-plaque forming unit ratio of most animal viruses. Here, we combine an imaging assay that simultaneously tracks the viral capsid and genome in live cells with an infectivity-based assay for RNA release to characterize the early events in the poliovirus (PV) infection. Effects on RNA genome delivery from inhibitors of cell trafficking pathways were probed systematically by both methods. Surprisingly, we observe that genome release by PV is highly efficient and rapid, and thus does not limit the overall infectivity or the infection rate. The results define a pathway in which PV binds to receptors on the cell surface and enters the cell by a clathrin-, caveolin-, flotillin-, and microtubule-independent, but tyrosine kinase- and actin-dependent, endocytic mechanism. Immediately after the internalization of the virus particle, genome release takes place from vesicles or tightly sealed membrane invaginations located within 100-200 nm of the plasma membrane. These results settle a long-lasting debate of whether PV directly breaks the plasma membrane barrier or relies on endocytosis to deliver its genome into the cell. We expect this imaging assay to be broadly applicable to the investigation of entry mechanisms for nonenveloped viruses.