Treatment measures for seasonal affective disorder: A network meta-analysis.

OBJECTIVE: The purpose of this study was to assess the potential effectiveness of several mainstream therapies, including phototherapy, antidepressants, cognitive-behavioral therapy, and negative ion generators, in the treatment of Seasonal Affective Disorder (SAD). METHODS: A systematic search of PubMed, Embase, Cochrane, and WOS databases was conducted from January 1975 to December 3, 2022. Randomized controlled trials meeting predefined selection criteria for the treatment of SAD using mainstream therapeutic approaches were identified. After reviewing abstracts, data were synthesized and categorized based on the type of intervention and the targeted disorder. RESULTS: A total of 21 randomized controlled trials, involving 1037 participants, were included. The standardized mean difference of depression scores and corresponding 95 % confidence intervals were calculated to assess the efficacy of phototherapy for Seasonal Affective Disorder. The meta-analysis revealed that phototherapy was significantly more effective than other intervention groups or control therapies, with an effect size of 4.64(2.38,7.03). Subgroup analysis demonstrated that no factors could explain the significant heterogeneity observed. Phototherapy exhibited statistically significant mild to moderate therapeutic effects in alleviating depressive symptoms and can be considered as a clinical therapy for treating Seasonal Affective Disorder. However, the quality of evidence remains low, and further well-designed, larger sample size, and high-quality studies are needed to confirm the efficacy of phototherapy in treating Seasonal Affective Disorder. CONCLUSION: In conclusion, our systematic review and meta-analysis indicate that bright light therapy is a promising first-line non-pharmacological treatment for Seasonal Affective Disorder (SAD), showing significant improvement in mood symptoms compared to placebo. The findings support the use of bright light therapy as an effective and well-tolerated intervention for SAD. However, further large-scale, multicenter randomized controlled trials with long-term follow-up are needed to assess the long-term efficacy and safety of different treatment approaches for SAD.

A decellularized nerve matrix scaffold inhibits neuroma formation in the stumps of transected peripheral nerve after peripheral nerve injury.

Traumatic painful neuroma is an intractable clinical disease characterized by improper extracellular matrix (ECM) deposition around the injury site. Studies have shown that the microstructure of natural nerves provides a suitable microenvironment for the nerve end to avoid abnormal hyperplasia and neuroma formation. In this study, we used a decellularized nerve matrix scaffold (DNM-S) to prevent against the formation of painful neuroma after sciatic nerve transection in rats. Our results showed that the DNM-S effectively reduced abnormal deposition of ECM, guided the regeneration and orderly arrangement of axon, and decreased the density of regenerated axons. The epineurium-perilemma barrier prevented the invasion of vascular muscular scar tissue, greatly reduced the invasion of α-smooth muscle actin-positive myofibroblasts into nerve stumps, effectively inhibited scar formation, which guided nerve stumps to gradually transform into a benign tissue and reduced pain and autotomy behaviors in animals. These findings suggest that DNM-S-optimized neuroma microenvironment by ECM remodeling may be a promising strategy to prevent painful traumatic neuromas.

Blockchain-Based Access Control and Behavior Regulation System for IoT.

With the development of 5G and the Internet of things (IoT), the multi-domain access of massive devices brings serious data security and privacy issues. At the same time, most access systems lack the ability to identify network attacks and cannot adopt dynamic and timely defenses against various security threats. To this end, we propose a blockchain-based access control and behavior regulation system for IoT. Relying on the attribute-based access control model, this system deploys smart contracts on the blockchain to achieve distributed and fine-grained access control and ensures that the identity and authority of access users can be trusted. At the same time, an inter-domain communication mechanism is designed based on the locator/identifier separation protocol and ensures the traffic of access users are authorized. A feedback module that combines traffic detection and credit evaluation is proposed, ensuring real-time detection and fast, proactive responses against malicious behavior. Ultimately, all modules are linked together through workflows to form an integrated security model. Experiments and analysis show that the system can effectively provide comprehensive security protection in IoT scenarios.

Dynamic changes in the thermal growing season and their association with atmospheric circulation in China.

Vegetation phenology is one of the key agroclimatic indices that is sensitive to climate change. Analyzing the variation in plant phenology under a changing environment can provide reference information to assess the impact of climate change on ecosystems and agricultural management. In this study, we focused on the thermal growth season, an important phenology index. We defined four growing season indices based on the surface temperature to quantify the changes in thermal growth season and analyze their association with atmospheric circulation in China. The results showed that the start date of the growing season exhibited a significant advanced trend (P < 0.001), while the end date exhibited a significant delayed trend (P < 0.001). The length of growing season and the number of ≥ 10℃ days increased significantly in China (P < 0.001) from 1960 to 2018. The variation in thermal growth season differed in different regions. The Qinghai-Tibet Plateau and the Loess Plateau were the regions in which thermal growing season was the most sensitive to climate changes. Atmospheric circulation was one of the main factors affected the change in thermal growing season indices. The West Pacific Subtropical High Intensity Index and the Arctic Oscillation Index significantly negatively correlated with the start date of the growing season (P < 0.05), and significantly positively correlated with the length of growing season and the number of ≥ 10℃ days (P < 0.01). Atmospheric circulation affected the change in temperature and subsequently affected the thermal growth season. These findings will provide useful information to assess the risk assessment of climate change and take action to reduce in the impact of climate change on ecosystems and agricultural management.

Bayesian Edge Detector Using Deformable Directivity-Aware Sampling Window.

Conventional image entropy merely involves the overall pixel intensity statistics which cannot respond to intensity patterns over spatial domain. However, spatial distribution of pixel intensity is definitely crucial to any biological or computer vision system, and that is why gestalt grouping rules involve using features of both aspects. Recently, the increasing integration of knowledge from gestalt research into visualization-related techniques has fundamentally altered both fields, offering not only new research questions, but also new ways of solving existing issues. This paper presents a Bayesian edge detector called GestEdge, which is effective in detecting gestalt edges, especially useful for forming object boundaries as perceived by human eyes. GestEdge is characterized by employing a directivity-aware sampling window or mask that iteratively deforms to probe or explore the existence of principal direction of sampling pixels; when convergence is reached, the window covers pixels best representing the directivity in compliance with the similarity and proximity laws in gestalt theory. During the iterative process based on the unsupervised Expectation-Minimization (EM) algorithm, the shape of the sampling window is optimally adjusted. Such a deformable window allows us to exploit the similarity and proximity among the sampled pixels. Comparisons between GestEdge and other edge detectors are shown to justify the effectiveness of GestEdge in extracting the gestalt edges.

Covering the proximal nerve stump with chondroitin sulfate proteoglycans prevents traumatic painful neuroma formation by blocking axon regeneration after neurotomy in Sprague Dawley rats.

OBJECTIVE: Neuropathic pain caused by traumatic neuromas is an extremely intractable clinical problem. Disorderly scar tissue accumulation and irregular and immature axon regeneration around the injury site mainly contribute to traumatic painful neuroma formation. Therefore, successfully preventing traumatic painful neuroma formation requires the effective inhibition of irregular axon regeneration and disorderly accumulation of scar tissue. Considering that chondroitin sulfate proteoglycans (CSPGs) can act on the growth cone and effectively inhibit axon regeneration, the authors designed and manufactured a CSPG-gelatin blocker to regulate the CSPGs' spatial distribution artificially and applied it in a rat model after sciatic nerve neurectomy to evaluate its effects in preventing traumatic painful neuroma formation. METHODS: Sixty female Sprague Dawley rats were randomly divided into three groups (positive group: no covering; blank group: covering with gelatin blocker; and CSPG group: covering with the CSPG-gelatin blocker). Pain-related factors were evaluated 2 and 8 weeks postoperatively (n = 30). Neuroma growth, autotomy behavior, and histological features of the neuromas were assessed 8 weeks postoperatively (n = 30). RESULTS: Eight weeks postoperatively, typical bulb-shaped neuromas did not form in the CSPG group, and autotomy behavior was obviously better in the CSPG group (p < 0.01) than in the other two groups. Also, in the CSPG group the regenerated axons showed a lower density and more regular and improved myelination (p < 0.01). Additionally, the distribution and density of collagenous fibers and the expression of α-smooth muscle actin were significantly lower in the CSPG group than in the positive group (p < 0.01). Regarding pain-related factors, c-fos, substance P, interleukin (IL)-17, and IL-1ß levels were significantly lower in the CSPG group than those in the positive and blank groups 2 weeks postoperatively (p < 0.05), while substance P and IL-17 remained lower in the CSPG group 8 weeks postoperatively (p < 0.05). CONCLUSIONS: The authors found that CSPGs loaded in a gelatin blocker can prevent traumatic neuroma formation and effectively relieve pain symptoms after sciatic nerve neurotomy by blocking irregular axon regeneration and disorderly collagenous fiber accumulation in the proximal nerve stump. These results indicate that covering the proximal nerve stump with CSPGs may be a new and promising strategy to prevent traumatic painful neuroma formation in the clinical setting.

Modulatory interactions of resting-state brain functional connectivity in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is mediated by chronic dysregulation of complex neural circuits, particularly the specific neurotransmitters or other neural substrates. Recently, both increases and decreases in resting-state functional connectivity have been observed in patients with MDD. However, previous research has only assessed the functional connectivity within a specific network or some regions of interests, without considering the modulatory effects of the entire brain regions. To fill in the research gap, this study employed PPI (physiophysiological interaction) to investigate the functional connectivity in the entire brain regions. Apart from the traditional PPI used for cognitive research, current PPI analysis is more suitable for exploring the neural mechanism in MDD patients. Besides, this PPI method does not require a new cognitive estimation task and can assess the modulatory effects on different part of brain without prior setting of regions of interest. METHODS: First, we recruited 76 outpatients with major depressive disorder, and conducted MRI scan to acquire structural and functional images. As referred to the previous study of resting-state networks, we identified eight well-defined intrinsic resting-state networks by using independent component analysis. Subsequently, we explored the regions that exhibited synchronous modulatory interactions within the network by executing PPI analysis. RESULTS: Our findings indicated that the modulatory effects between healthy crowed and patient are different. By using PPI analysis in neuroimaging can help us to understand the mechanisms of neural disruptions in MDD patients. In addition, this study provides new insight into the complicated relationships between three or more regions of brain, as well as different brain networks functions in external and internal. CONCLUSION: Furthermore, the functional connectivity may deepen our knowledge regarding the complex brain functions in MDD patients and suggest a new multimodality treatment for MDD including targeted therapy and transcranial magnetic stimulation.

Memory Impairment Induced by Borna Disease Virus 1 Infection is Associated with Reduced H3K9 Acetylation.

BACKGROUND/AIMS: Borna disease virus 1 (BoDV-1) infection induces cognitive impairment in rodents. Emerging evidence has demonstrated that Chromatin remodeling through histone acetylation can regulate cognitive function. In the present study, we investigated the epigenetic regulation of chromatin that underlies BoDV-1-induced cognitive changes in the hippocampus. METHODS: Immunofluorescence assay was applied to detect BoDV-1 infection in hippocampal neurons and Sprague-Dawley rats models. The histone acetylation levels both in vivo and vitro were assessed by western blots. The acetylation-regulated genes were identified by ChIP-seq and verified by RT-qPCR. Cognitive functions were evaluated with Morris Water Maze test. In addition, Golgi staining, and electrophysiology were used to study changes in synaptic structure and function. RESULTS: BoDV-1 infection of hippocampal neurons significantly decreased H3K9 histone acetylation level and inhibited transcription of several synaptic genes, including postsynaptic density 95 (PSD95) and brain-derived neurotrophic factor (BDNF). Furthermore, BoDV-1 infection of Sprague Dawley rats disrupted synaptic plasticity and caused spatial memory impairment. These rats also exhibited dysregulated hippocampal H3K9 acetylation and decreased PSD95 and BDNF protein expression. Treatment with the HDAC inhibitor, suberanilohydroxamic acid (SAHA), attenuated the negative effects of BoDV-1. CONCLUSION: Our results demonstrate that regulation of H3K9 histone acetylation may play an important role in BoDV-1-induced memory impairment, whereas SAHA may confer protection against BoDV-1-induced cognitive impairments. This study finds important mechanism of BoDV-1 infection disturbing neuronal synaptic plasticity and inducing cognitive dysfunction from the perspective of histone modification.

Fast Visual Tracking Based on Convolutional Networks.

Recently, an upsurge of deep learning has provided a new direction for the field of computer vision and visual tracking. However, expensive offline training time and the large number of images required by deep learning have greatly hindered progress. This paper aims to further improve the computational performance of CNT which is reported to deliver 5 fps performance in visual tracking, we propose a method called Fast-CNT which differs from CNT in three aspects: firstly, an adaptive k value (rather than a constant 100) is determined for an input video; secondly, background filters used in CNT are omitted in this work to save computation time without affecting performance; thirdly, SURF feature points are used in conjunction with the particle filter to address the drift problem in CNT. Extensive experimental results on land and undersea video sequences show that Fast-CNT outperforms CNT by 2~10 times in terms of computational efficiency.

Stochastic and superharmonic stochastic resonances of a confined overdamped harmonic oscillator.

The dynamics of many soft condensed matter and biological systems is affected by space limitations, which produce some peculiar effects on the systems' stochastic resonance (SR) behavior. In this study, we propose a model where SR can be observed: a confined overdamped harmonic oscillator that is subjected to a sinusoidal driving force and is under the influence of a multiplicative white noise. The output response of the system is a periodic signal with harmonic frequencies that are odd multiples of the driving frequency. We verify the amplitude resonances at the driving frequencies and superharmonic frequencies that are equal to three, five, and seven times the driving frequency, using a numerical method based on the stochastic Taylor expansion. The synergistic effect of the multiplicative white noise, constant boundaries, and periodic driving force that can induce a SR in the output amplitude at the driving and superharmonic frequencies is found. The SR phenomenon found in this paper is sensitive to the driving amplitude and frequency, inherent potential parameter, and boundary width, thus leading to various resonance conditions. Therefore, the mechanism found could be beneficial for the characterization of these confined systems and could constitute an important tool for controlling their basic properties.

Up-regulation of SIRT6 in the hippocampus induced rats with depression-like behavior via the block Akt/GSK3ß signaling pathway.

Major depression is the leading cause of disability worldwide, which is associated with diverse alterations in brain such as neuro-inflammation, synaptic dysfunction, and cognitive deficit. Accumulating evidences suggest sirtuins (SIRTs) are involved in brain developmental disorders, metabolic diseases and play a key role in cognition and synaptic plasticity, yet the role in mood regulation remains controversial. Hence, Western blotting and RT-qPCR were used to investigate whether SIRTs (SIRT1-7) expression levels were altered in the hippocampus of rats, which followed 5 weeks of chronic unpredictable mild stress (CUMS) treatment, the results showed depressive-like behaviors: like body weight, forced swim test and sucrose preference test and SIRT6 was a significant increase in the hippocampal of CUMS rats. Furthermore, via a lentivirus-mediated transfection in hippocampal neurons, we aimed to detect how SIRT6 influence the function of hippocampus. The SIRT6 overexpression significantly inhibited expressions of proteins and/or phosphoproteins (e.g AKT, p-AKT, P-GSK3ß), decreased the ratios of p-GSK3ß/GSK3ß and p-Akt/Akt in the primary hippocampus neurons. Thus, our data indicates that SIRT6 is involved in the modulation of depressive-like behaviors and affects the survival and synaptic plasticity of hippocampal neuron via inhibitory activation of Akt-GSK3ß signaling.