Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI ...data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were as follows: (1) Propose an ADHD classification model using the extreme learning machine (ELM) algorithm for automatic, efficient and objective clinical ADHD diagnosis. (2) Assess the computational efficiency and the effect of sample size on both ELM and support vector machine (SVM) methods and analyze which brain segments are involved in ADHD.
High-resolution three-dimensional MR images were acquired from 55 ADHD subjects and 55 healthy controls. Multiple brain measures (cortical thickness, etc.) were calculated using a fully automated procedure in the FreeSurfer software package. In total, 340 cortical features were automatically extracted from 68 brain segments with 5 basic cortical features. F-score and SFS methods were adopted to select the optimal features for ADHD classification. Both ELM and SVM were evaluated for classification accuracy using leave-one-out cross-validation.
We achieved ADHD prediction accuracies of 90.18% for ELM using eleven combined features, 84.73% for SVM-Linear and 86.55% for SVM-RBF. Our results show that ELM has better computational efficiency and is more robust as sample size changes than is SVM for ADHD classification. The most pronounced differences between ADHD and healthy subjects were observed in the frontal lobe, temporal lobe, occipital lobe and insular.
Our ELM-based algorithm for ADHD diagnosis performs considerably better than the traditional SVM algorithm. This result suggests that ELM may be used for the clinical diagnosis of ADHD and the investigation of different brain diseases.
Multimodal medical image fusion plays a vital role in different clinical imaging sensor applications. This paper presents a novel multimodal medical image fusion method that adopts a multiscale ...geometric analysis of the nonsubsampled contourlet transform (NSCT) with type-2 fuzzy logic techniques. First, the NSCT was performed on preregistered source images to obtain their high- and low-frequency subbands. Next, an effective type-2 fuzzy logic-based fused rule is proposed for fusion of the high-frequency subbands. In the presented fusion approach, the local type-2 fuzzy entropy is introduced to automatically select high-frequency coefficients. However, for the low-frequency subbands, they were fused by a local energy algorithm based on the corresponding image's local features. Finally, the fused image was constructed by the inverse NSCT with all composite subbands. Both subjective and objective evaluations showed better contrast, accuracy, and versatility in the proposed approach compared with state-of-the-art methods. Besides, an effective color medical image fusion scheme is also given in this paper that can inhibit color distortion to a large extent and produce an improved visual effect.
An unprecedented Ir/f‐amphox‐catalyzed asymmetric hydrogenation of racemic 2,3‐syn‐dihydroxy‐1,4‐diones is presented involving dynamic kinetic resolution, which produces (1R,2R,3R,4R)‐tetraols. This ...protocol constitutes an efficient and straightforward approach to accessing sugar alcohols bearing four contiguous stereocenters. The strategy exhibits various advantages over existing methods, including excellent yields (up to 98 %), exceptional stereoselectivities (up to 99:1 dr, 99.9 % ee), operational simplicity and substrate generality. Moreover, the nature of the reaction was revealed as a stepwise transformation by in situ Fourier‐transform infrared spectroscopy and isolation of intermediates.
An Ir/f‐amphox‐catalyzed asymmetric hydrogenation of racemic 2,3‐syn‐dihydroxy‐1,4‐diones is presented, involving dynamic kinetic resolution to produce 1,2,3,4‐tetraols. This protocol constitutes an efficient and straightforward approach to accessing chiral sugar alcohols. The nature of the reaction was revealed as a stepwise transformation by in situ Fourier‐transform infrared spectroscopy and isolation of intermediates.
Key points
μ‐Opioid receptors (MORs) are expressed peripherally and centrally, but the loci of MORs responsible for clinically relevant opioid analgesia are uncertain.
Crossing Oprm1flox/flox and ...AdvillinCre/+ mice completely ablates MORs in dorsal root ganglion neurons and reduces the MOR expression level in the spinal cord.
Presynaptic MORs expressed at primary afferent central terminals are essential for synaptic inhibition and potentiation of sensory input by opioids.
MOR ablation in primary sensory neurons diminishes analgesic effects produced by systemic and intrathecal opioid agonists and abolishes chronic opioid treatment‐induced hyperalgesia.
These findings demonstrate a critical role of MORs expressed in primary sensory neurons in opioid analgesia and suggest new strategies to increase the efficacy and reduce adverse effects of opioids.
The pain and analgesic systems are complex, and the actions of systemically administered opioids may be mediated by simultaneous activation of μ‐opioid receptors (MORs, encoded by the Oprm1 gene) at multiple, interacting sites. The loci of MORs and circuits responsible for systemic opioid‐induced analgesia and hyperalgesia remain unclear. Previous studies using mice in which MORs are removed from Nav1.8‐ or TRPV1‐expressing neurons provided only an incomplete and erroneous view about the role of peripheral MORs in opioid actions in vivo. In the present study, we determined the specific role of MORs expressed in primary sensory neurons in the analgesic and hyperalgesic effects produced by systemic opioid administration. We generated Oprm1 conditional knockout (Oprm1‐cKO) mice in which MOR expression is completely deleted from dorsal root ganglion neurons and substantially reduced in the spinal cord, which was confirmed by immunoblotting and immunocytochemical labelling. Both opioid‐induced inhibition and potentiation of primary sensory input were abrogated in Oprm1‐cKO mice. Remarkably, systemically administered morphine potently inhibited acute thermal and mechanical nociception and persistent inflammatory pain in control mice but had little effect in Oprm1‐cKO mice. The analgesic effect of intrathecally administered morphine was also profoundly reduced in Oprm1‐cKO mice. Additionally, chronic morphine treatment‐induced hyperalgesia was absent in Oprm1‐cKO mice. Our findings directly challenge the notion that clinically relevant opioid analgesia is mediated mostly by centrally expressed MORs. MORs in primary sensory neurons, particularly those expressed presynaptically at the first sensory synapse in the spinal cord, are crucial for both opioid analgesia and opioid‐induced hyperalgesia.
Key points
μ‐Opioid receptors (MORs) are expressed peripherally and centrally, but the loci of MORs responsible for clinically relevant opioid analgesia are uncertain.
Crossing Oprm1flox/flox and AdvillinCre/+ mice completely ablates MORs in dorsal root ganglion neurons and reduces the MOR expression level in the spinal cord.
Presynaptic MORs expressed at primary afferent central terminals are essential for synaptic inhibition and potentiation of sensory input by opioids.
MOR ablation in primary sensory neurons diminishes analgesic effects produced by systemic and intrathecal opioid agonists and abolishes chronic opioid treatment‐induced hyperalgesia.
These findings demonstrate a critical role of MORs expressed in primary sensory neurons in opioid analgesia and suggest new strategies to increase the efficacy and reduce adverse effects of opioids.
A straightforward synthesis of optically active trifluoromethyl dihydropyranones and spirocyclic oxindole‐dihydropyranones has been realized by the chiral N‐heterocyclic carbenes‐catalyzed ...cyclization of α,β‐unsaturated β‐methylacyl chlorides with activated trifluoromethyl ketones or isatin derivatives.
Multisensor image fusion technologies, which convey image information from different sensor modalities to a single image, have been a growing interest in recent research. In this paper, we propose a ...novel multisensor image fusion method based on multiple visual features measurement with gradient domain guided filtering. First, a Gaussian smoothing filter is employed to decompose each source image into two components: approximate component formed by homogeneous regions and detail component with sharp edges. Second, an effective decision map construction model is presented by measuring three key visual features of the input sensor image: contrast saliency, sharpness, and structure saliency. Third, a gradient domain guided filtering-based decision map optimization technique is proposed to make full use of spatial consistency and generate weight maps. Finally, the resultant image is fused with the weight maps and then is experimentally verified through multifocus image, multimodal medical image, and infrared-visible image fusion. The experimental results demonstrate that the proposed method can achieve better performance than state-of-the-art methods in terms of subjective visual effect and objective evaluation.
Single-cell RNA sequencing offers a promising opportunity for probing cell types mediating specific behavioral functions and the underlying molecular programs. However, this has been hampered by a ...long-standing issue in transcriptional profiling of dissociated cells, specifically the transcriptional perturbations that are artificially induced during conventional whole-cell dissociation procedures. Here, we develop Act-seq, which minimizes artificially induced transcriptional perturbations and allows for faithful detection of both baseline transcriptional profiles and acute transcriptional changes elicited by behavior/experience-driven activity. Using Act-seq, we provide the first detailed molecular taxonomy of distinct cell types in the amygdala. We further show that Act-seq robustly detects seizure-induced acute gene expression changes in multiple cell types, revealing cell-type-specific activation profiles. Furthermore, we find that acute stress preferentially activates neuronal subpopulations that express the neuropeptide gene Cck. Act-seq opens the way for linking physiological stimuli with acute transcriptional dynamics in specific cell types in diverse complex tissues.
•Act-seq minimizes artificial transcriptional changes during tissue dissociation•Act-seq enables unbiased characterization of cell types and their acute activation•Application of Act-seq provides the first molecular taxonomy in the amygdala•Application of Act-seq identifies neuronal subpopulations activated by stress
Wu et al. develop Act-seq, which minimizes artificially induced transcriptional changes during single-cell dissociation and thus enables faithful characterization of baseline transcriptional profiles and detection of specific cell populations activated by physiological stimuli using single-cell sequencing.
Objective
To evaluate the influence of supportive treatment (SPT) during a maintenance period after implant placement on implant survival rate (SR) and incidence of peri‐implant diseases.
Material ...and methods
A systemic literature search for studies published up to June 2018 was conducted by two independent reviewers using Pubmed/MEDLINE, EMBASE, and Cochrane Central databases. Clinical controlled trials (CCT) involved in SPT protocol with more than 1‐year follow‐up were included. Quantitative meta‐analyses were carried out to analyze the risk ratio (RR) of SR, the incidence of peri‐implantitis, and peri‐implant mucositis between SPT and non‐SPT groups. Any potential confounding factors were investigated using meta‐regression.
Results
Nine CCTs fulfilled the criteria. To evaluate the influence of SPT on SR, peri‐implantitis, and peri‐implant mucositis, six of nine, three of nine, and three of nine articles were included in further meta‐analysis, respectively. SPT group significantly showed higher SR (RR: 1.10; p < 0.001), lower prevalence of peri‐implantitis (RR: 0.25; p < 0.001) and peri‐implant mucositis (RR: 0.57; p < 0.001) than the non‐SPT group. Meta‐regression of the selected studies failed to find an association between SR, peri‐implantitis, and peri‐implant mucositis and confounding factors: application of chemical agents and the frequency of SPT.
Conclusion
SPT can potentially improve peri‐implant health in terms of SR, peri‐implantitis, and peri‐implant mucositis. Additionally, the correlation in recall interval and adjunctive use of chemical agents during SPT to peri‐implant diseases and implant loss could not be found.
NCEP‐NCAR reanalysis data from 1948 to 2001 are used to examine the relationship between the North Atlantic Oscillation (NAO) and the North Atlantic sea surface temperature anomaly (SSTA) tripole. It ...is demonstrated that the atmospheric anomalies associated with NAO produce tripole‐like sea surface temperature (SST) anomalies; in turn, the SSTA tripole produces NAO‐like atmospheric anomalies. Therefore, a positive feedback between the NAO and the SSTA tripole is suggested. The results are statistically significant; they clarify prior uncertainties associated with the relationship between the NAO and the North Atlantic SSTA tripole.
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