Hyperbaric oxygen therapy ameliorates intestinal and systematic inflammation by modulating dysbiosis of the gut microbiota in Crohn's disease.

BACKGROUND: Dysbiosis of the gut microbiota is pivotal in Crohn's disease (CD) and modulated by host physiological conditions. Hyperbaric oxygen therapy (HBOT) is a promising treatment for CD that can regulate gut microbiota. The relationship between HBOT and the gut microbiota in CD remains unknown. METHODS: CD patients were divided into an HBOT group (n = 10) and a control group (n = 10) in this open-label prospective interventional study. The fecal samples before and after HBOT were used for 16 S rRNA gene sequencing and fecal microbiota transplantation (FMT). A colitis mouse model was constructed using dextran sulfate sodium, and intestinal and systematic inflammation was evaluated. The safety and long-term effect of HBOT were observed. RESULTS: HBOT significantly reduced the level of C-reactive protein (CRP) (80.79 ± 42.05 mg/L vs. 33.32 ± 18.31 mg/L, P = 0.004) and the Crohn's Disease Activity Index (CDAI) (274.87 ± 65.54 vs. 221.54 ± 41.89, P = 0.044). HBOT elevated the declined microbial diversity and ameliorated the altered composition of gut microbiota in patients with CD. The relative abundance of Escherichia decreased, and that of Bifidobacterium and Clostridium XIVa increased after HBOT. Mice receiving FMT from donors after HBOT had significantly less intestinal inflammation and serum CRP than the group before HBOT. HBOT was safe and well-tolerated by patients with CD. Combined with ustekinumab, more patients treated with HBOT achieved clinical response (30%vs.70%, P = 0.089) and remission (20%vs.50%, P = 0.160) at week 4. CONCLUSIONS: HBOT modulates the dysbiosis of gut microbiota in CD and ameliorates intestinal and systematic inflammation. HBOT is a safe option for CD and exhibits a promising auxiliary effect to ustekinumab. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2200061193. Registered 15 June 2022, https://www.chictr.org.cn/showproj.html?proj=171605 .

Multi-Resolution Wavelet Fractal Analysis and Subtask Training for Enhancing Few-Shot Noisy Brainwave Recognition.

The integration of healthcare monitoring with Internet of Things (IoT) networks radically transforms the management and monitoring of human well-being. Portable and lightweight electroencephalography (EEG) systems with fewer electrodes have improved convenience and flexibility while retaining adequate accuracy. However, challenges emerge when dealing with real-time EEG data from IoT devices due to the presence of noisy samples, which impedes improvements in brainwave detection accuracy. Moreover, high inter-subject variability and substantial variability in EEG signals present difficulties for conventional data augmentation and subtask learning techniques, leading to poor generalizability. To address these issues, we present a novel framework for enhancing EEG-based recognition through multi-resolution data analysis, capturing features at different scales using wavelet fractals. The original data can be expanded many times after continuous wavelet transform (CWT) and recombination, alleviating insufficient training samples. In the transfer stage of deep learning (DL) models, we adopt a subtask learning approach to train the recognition model to generalize efficiently. This incorporates wavelets at various scales instead of exclusively considering average prediction performance across scales and paradigms. Through extensive experiments, we demonstrate that our proposed DL-based method excels at extracting features from small-scale and noisy EEG data. This significantly improves healthcare monitoring performance by mitigating the impact of noise introduced by the external environment.

Transcranial alternating current stimulation combined with sound stimulation improves the cognitive function of patients with Alzheimer's disease: A case report and literature review.

Transcranial alternating current stimulation (tACS) is a relatively new non-invasive brain electrical stimulation method for the treatment of patients with Alzheimer's disease (AD), but it has poor offline effects. Therefore, we applied a new combined stimulation method to observe the offline effect on the cognitive function of patients with AD. Here, we describe the clinical results of a case in which tACS combined with sound stimulation was applied to treat moderate AD. The patient was a 73-year-old woman with a 2-year history of persistent cognitive deterioration despite the administration of Aricept and Sodium Oligomannate. Therefore, the patient received tACS combined with sound stimulation. Her cognitive scale scores improved after 15 sessions and continued to improve at 4 months of follow-up. Although the current report may provide a new alternative therapy for patients with AD, more clinical data are needed to support its efficacy. Trial registration: Clinicaltrials.gov, NCT05251649.

Spatio-Frequency Decoupled Weak-Supervision for Face Reconstruction.

3D face reconstruction has witnessed considerable progress in recovering 3D face shapes and textures from in-the-wild images. However, due to a lack of texture detail information, the reconstructed shape and texture based on deep learning could not be used to re-render a photorealistic facial image since it does not work in harmony with weak supervision only from the spatial domain. In the paper, we propose a method of spatio-frequency decoupled weak-supervision for face reconstruction, which applies the losses from not only the spatial domain but also the frequency domain to learn the reconstruction process that approaches photorealistic effect based on the output shape and texture. In detail, the spatial domain losses cover image-level and perceptual-level supervision. Moreover, the frequency domain information is separated from the input and rendered images, respectively, and is then used to build the frequency-based loss. In particular, we devise a spectrum-wise weighted Wing loss to implement balanced attention on different spectrums. Through the spatio-frequency decoupled weak-supervision, the reconstruction process can be learned in harmony and generate detailed texture and high-quality shape only with labels of landmarks. The experiments on several benchmarks show that our method can generate high-quality results and outperform state-of-the-art methods in qualitative and quantitative comparisons.

Machine learning-based prediction and inverse design of 2D metamaterial structures with tunable deformation-dependent Poisson's ratio.

With the aid of recent efficient and prior knowledge-free machine learning (ML) algorithms, extraordinary mechanical properties such as negative Poisson's ratio have extensively promoted the diverse designs of metamaterials with distinctive cellular structures. However, most existing ML approaches applied to the design of metamaterials are primarily based on a single property value with the assumption that the Poisson's ratio of a material is stationary, neglecting the dynamic variability of Poisson's ratio, termed deformation-dependent Poisson's ratio, during the loading process that a metamaterial other than conventional materials may experience. This paper first proposes a crystallographic symmetry-based methodology to build 2D metamaterials with complex but patterned topological structures, and then converts them into computational models suitable for molecular dynamics simulations. Then, we employ an integrated approach, consisting of molecular dynamics simulations capable of generating and collecting a large dataset for training/validation, in addition to ML algorithms (CNN and Cycle-GAN) able to predict the dynamic characteristics of Poisson's ratio and offer the inverse design of a metamaterial structure based on a target quasi-continuous Poisson's ratio-strain curve, to eventually unravel the underlying mechanism and design principles of 2D metamaterial structures with tunable Poisson's ratio. The close match between the predefined Poisson's ratio response and that from the generated structure validates the feasibility of the proposed ML model. Owing to the high efficiency and complete independence from prior knowledge, our proposed approach offers a novel and robust technique for the prediction and inverse design of metamaterial structures with tailored deformation-dependent Poisson's ratio, an unprecedented property attractive in flexible electronics, soft robotics, and nanodevices.

Decision Fusion Networks for Image Classification.

Convolutional neural networks, in which each layer receives features from the previous layer(s) and then aggregates/abstracts higher level features from them, are widely adopted for image classification. To avoid information loss during feature aggregation/abstraction and fully utilize lower layer features, we propose a novel decision fusion module (DFM) for making an intermediate decision based on the features in the current layer and then fuse its results with the original features before passing them to the next layers. This decision is devised to determine an auxiliary category corresponding to the category at a higher hierarchical level, which can, thus, serve as category-coherent guidance for later layers. Therefore, by stacking a collection of DFMs into a classification network, the generated decision fusion network is explicitly formulated to progressively aggregate/abstract more discriminative features guided by these decisions and then refine the decisions based on the newly generated features in a layer-by-layer manner. Comprehensive results on four benchmarks validate that the proposed DFM can bring significant improvements for various common classification networks at a minimal additional computational cost and are superior to the state-of-the-art decision fusion-based methods. In addition, we demonstrate the generalization ability of the DFM to object detection and semantic segmentation.

PyraPVConv: Efficient 3D Point Cloud Perception with Pyramid Voxel Convolution and Sharable Attention.

Designing efficient deep learning models for 3D point cloud perception is becoming a major research direction. Point-voxel convolution (PVConv) Liu et al. (2019) is a pioneering research work in this topic. However, since with quite a few layers of simple 3D convolutions and linear point-voxel feature fusion operations, it still has considerable room for improvement in performance. In this paper, we propose a novel pyramid point-voxel convolution (PyraPVConv) block with two key structural modifications to address the above issues. First, PyraPVConv uses a voxel pyramid module to fully extract voxel features in the manner of feature pyramid, such that sufficient voxel features can be obtained efficiently. Second, a sharable attention module is utilized to capture compatible features between multi-scale voxels in pyramid and point cloud for aggregation, as well as to reduce the complexity via structure sharing. Extensive results on three point cloud perception tasks, i.e., indoor scene segmentation, object part segmentation and 3D object detection, validate that the networks constructed by stacking PyraPVConv blocks are efficient in terms of both GPU memory consumption and computational complexity, and are superior to the state-of-the-art methods.

LncRNA TUG1 functions as a ceRNA for miR-1-3p to promote cell proliferation in hepatic carcinogenesis.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterised by high malignancy, metastasis and recurrence, but the specific mechanism that drives these outcomes is unclear. Recent studies have shown that long noncoding RNAs (lncRNAs) can regulate the proliferation and apoptosis of hepatic cells. METHODS: We searched for lncRNAs and microRNAs (miRNAs), which can regulate IGF1 expression, through a bioinformatics website, and predicted that lncRNA taurine-upregulated gene 1 (TUG1) would have multiple targets for miR-1-3p binding, meaning that lncRNA TUG1 played an adsorption role. A double luciferase assay was used to verify the targeting relationship between lncRNA TUG1 and miR-1-3p. Western blotting and qPCR were used to verify the targeting relationship between miR-1-3p and IGF1, and qPCR was used to verify the regulatory relationship between the lncRNA TUG1-miR-1-3p-IGF1 axis. CCK-8 was used to detect the growth activity of miRNA-transfected L-O2 cells, and flow cytometry was used to detect cell cycle changes and apoptosis. RESULT: The proliferation cycle of L-O2 cells transfected with miR-1-3p mimics was significantly slowed. Flow cytometry showed that the proliferation of L-O2 cells was slowed, and the apoptosis rate was increased. In contrast, when L-O2 cells were transfected with miR-1-3p inhibitor, the expression of IGF1 was significantly upregulated, and the cell proliferation cycle was significantly accelerated. Flow cytometry showed that the cell proliferation rate was accelerated, and the apoptosis rate was reduced. CONCLUSION: LncRNA TUG1 can adsorb miR-1-3p as a competitive endogenous RNA (ceRNA) to promote the expression of IGF1 and promote cell proliferation in hepatic carcinogenesis.

Transcranial alternating current stimulation combined with sound stimulation improves cognitive function in patients with Alzheimer's disease: Study protocol for a randomized controlled trial.

Background: The number of patients with Alzheimer's disease (AD) worldwide is increasing yearly, but the existing treatment methods have poor efficacy. Transcranial alternating current stimulation (tACS) is a new treatment for AD, but the offline effect of tACS is insufficient. To prolong the offline effect, we designed to combine tACS with sound stimulation to maintain the long-term post-effect. Materials and methods: To explore the safety and effectiveness of tACS combined with sound stimulation and its impact on the cognition of AD patients. This trial will recruit 87 patients with mild to moderate AD. All patients were randomly divided into three groups. The change in Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) scores from the day before treatment to the end of treatment and 3 months after treatment was used as the main evaluation index. We will also explore the changes in the brain structural network, functional network, and metabolic network of AD patients in each group after treatment. Discussion: We hope to conclude that tACS combined with sound stimulation is safe and tolerable in 87 patients with mild to moderate AD under three standardized treatment regimens. Compared with tACS alone or sound alone, the combination group had a significant long-term effect on cognitive improvement. To screen out a better treatment plan for AD patients. tACS combined with sound stimulation is a previously unexplored, non-invasive joint intervention to improve patients' cognitive status. This study may also identify the potential mechanism of tACS combined with sound stimulation in treating mild to moderate AD patients. Clinical Trial Registration: Clinicaltrials.gov, NCT05251649. Registered on February 22, 2022.

Geometrical Consistency Modeling on B-Spline Parameter Domain for 3D Face Reconstruction From Limited Number of Wild Images.

A number of methods have been proposed for face reconstruction from single/multiple image(s). However, it is still a challenge to do reconstruction for limited number of wild images, in which there exists complex different imaging conditions, various face appearance, and limited number of high-quality images. And most current mesh model based methods cannot generate high-quality face model because of the local mapping deviation in geometric optics and distortion error brought by discrete differential operation. In this paper, accurate geometrical consistency modeling on B-spline parameter domain is proposed to reconstruct high-quality face surface from the various images. The modeling is completely consistent with the law of geometric optics, and B-spline reduces the distortion during surface deformation. In our method, 0th- and 1st-order consistency of stereo are formulated based on low-rank texture structures and local normals, respectively, to approach the pinpoint geometric modeling for face reconstruction. A practical solution combining the two consistency as well as an iterative algorithm is proposed to optimize high-detailed B-spline face effectively. Extensive empirical evaluations on synthetic data and unconstrained data are conducted, and the experimental results demonstrate the effectiveness of our method on challenging scenario, e.g., limited number of images with different head poses, illuminations, and expressions.

Oxytocin modulates neural processing of mitral/tufted cells in the olfactory bulb.

AIM: Oxytocin plays an important role in social recognition in rodents, which is mediated predominantly by the olfactory system. Although oxytocin modulates neural activity in the olfactory bulb, the underlying mechanism is largely unknown. Here, we studied how direct infusion of oxytocin into the olfactory bulb affect social interactions in mice and modulate the neural activity of mitral/tufted cells in the olfactory bulb. METHODS: A three-chamber social interaction test was used in the behavioural test. For in vivo studies, single unit recordings, local field potential recordings and fibre photometry recordings were used to record the neural activity of olfactory bulb. For in vitro studies, we performed patch clamp recordings in the slice of the olfactory bulb. RESULTS: Behaviourally, direct oxytocin infusion in olfactory bulb increased performance in a social interaction task. Moreover, odour-evoked responses of mitral/tufted cells and neural discrimination of odours were both enhanced by oxytocin, whereas the spontaneous firing rate of mitral/tufted cells was reduced. At the neural network level, oxytocin decreased the amplitude of odour-evoked high gamma responses. At the cell population level, oxytocin decreased odour-evoked calcium responses (reflecting neural activity) specifically in granule cells. Moreover, in vitro slice recordings revealed that the inhibitory effect of oxytocin on mitral cell activity is mediated mainly by modulation of ATP-sensitive potassium channels and involves the oxytocin receptor-Gq-PLC-IP3 signalling pathway. CONCLUSION: Oxytocin modulates social interaction, likely by increasing the signal-to-noise ratio of odour responses in mitral cells which is partly through ATP-sensitive potassium channel.

Leptin modulates olfactory discrimination and neural activity in the olfactory bulb.

AIM: Leptin is an important peptide hormone that regulates food intake and plays a crucial role in modulating olfactory function. Although a few previous studies have investigated the effect of leptin on odor perception and discrimination in rodents, research on the neural basis underlying the behavioral changes is lacking. Here we study how leptin affects behavioral performance during a go/no-go task and how it modulates neural activity of mitral/tufted cells in the olfactory bulb, which plays an important role in odor information processing and representation. METHODS: A go/no-go odor discrimination task was used in the behavioral test. For in vivo studies, single unit recordings, local field potential recordings and fiber photometry recordings were used. For in vitro studies, we performed patch clamp recordings in the slice of the olfactory bulb. RESULTS: Behaviorally, leptin affects performance and reaction time in a difficult odor-discrimination task. Leptin decreases the spontaneous firing of single mitral/tufted cells, decreases the odor-evoked beta and high gamma local field potential response, and has bidirectional effects on the odor-evoked responses of single mitral/tufted cells. Leptin also inhibits the population calcium activity in genetically identified mitral/tufted cells and granule cells. Furthermore, in vitro slice recordings reveal that leptin inhibits mitral cell activity through direct modulation of the voltage-sensitive potassium channel. CONCLUSIONS: The behavioral reduction in odor discrimination observed after leptin administration is likely due to decreased neural activity in mitral/tufted cells, caused by modulation of potassium channels in these cells.

Mechanical anisotropy of two-dimensional metamaterials: a computational study.

Metamaterials, rationally designed multiscale composite systems, have attracted extensive interest because of their potential for a broad range of applications due to their unique properties such as negative Poisson's ratio, exceptional mechanical performance, tunable photonic and phononic properties, structural reconfiguration, etc. Though they are dominated by an auxetic structure, the constituents of metamaterials also play an indispensable role in determining their unprecedented properties. In this vein, 2D materials such as graphene, silicene, and phosphorene with superior structural tunability are ideal candidates for constituents of metamaterials. However, the nanostructure-property relationship and composition-property relationship of these 2D material-based metamaterials remain largely unexplored. Mechanical anisotropy inherited from the 2D material constituents, for example, may substantially impact the physical stability and robustness of the corresponding metamaterial systems. Herein, classical molecular dynamics simulations are performed using a generic coarse-grained model to explore the deformation mechanism of these 2D material-based metamaterials with sinusoidally curved ligaments and the effect of mechanical anisotropy on mechanical properties, especially the negative Poisson's ratio. The results indicate that deformation under axial tensile load can be divided into two stages: bending-dominated and stretching-dominated, in which the rotation of junctions in the former stage results in auxetic behavior of the proposed metamaterials. In addition, the auxetic behavior depends heavily on both the amplitude/wavelength ratio of the sinusoidal ligament and the stiffness ratio between axial and transverse directions. The magnitude of negative Poisson's ratio increases from 0 to 0.625, with an associated increase of the amplitude/wavelength ratio from 0 to 0.225, and fluctuates at around 0.625, in good agreement with the literature, with amplitude/wavelength ratios greater than 0.225. More interestingly, the magnitude of negative Poisson's ratio increases from 0.47 to 0.87 with the increase of the stiffness ratio from 0.125 to 8, in good agreement with additional all-atom molecular dynamics simulations for phosphorene and molybdenum disulfide. Overall, these research findings shed light on the deformation mechanism of auxetic metamaterials, providing useful guidelines for designing auxetic 2D lattice structures made of 2D materials that can display a tunable negative Poisson's ratio.

[Relationship between CD4+ CD28null T cell and atherosclerosis progression in patients with type 2 diabetes].

OBJECTIVE: To explore the effect of CD4+ CD28null T cell on occurrence and progression of atherosclerosis in patients with type 2 diabetes. METHODS: A total of 188 patients who were diagnosed as type 2 diabetes in the department of endocrinology were selected in this study.The carotid atherosclerosis was detected using color Doppler ultrasound.The patients with intima-media thickness>1.1 mm or plaques were classified as the carotid atherosclerosis group (95 cases), the others were classified as the control group (93 cases). According to the intima-media thickening and plaques, carotid atherosclerosis group was divided into three subgroups: the thickening group (30 cases), the plaque group (28 cases) and the thickening+plaque group (37 cases). Percentage of CD4+ CD28null T cell in peripheral blood was detected using a flow cytometry, and thus compared and analyzed between the carotid atherosclerosis group and the control group.The relationships between percentage of CD4+ CD28null T cell and age, C-reactive protein (CRP), blood sugar, blood lipids, the body mass index (BMI), waist circumference, hip circumference, diastolic blood pressure, systolic blood pressure and other data were also analyzed. RESULTS: Percentage of CD4+ CD28null T cell of the carotid atherosclerosis group was significantly higher than that of the control group (4.07%±3.21% vs 2.99%±2.34%, P<0.01). Percentage of CD4+ CD28null T cell of the thickening+ plaque group was higher than that of the plaque group and thickening group (both P<0.05), and percentage of CD4+ CD28null T cell of the plaque group was higher than the thickening group (P<0.05). Logistic regression analysis indicated that CRP, FPG and percentage of CD4+ CD28null T cell were the independent risk factors of atherosclerosis in patients with type 2 diabetes.Furthermore, multiple linear regression analysis showed that percentage of CD4+ CD28null T cell was linear correlated to CRP (P<0.01). CONCLUSION: The type 2 diabetes patients with atherosclerosis had a higher percentage of CD4+ CD28null T cell, which was increased with the atherosclerosis progression.CD4+ CD28null T cell may affect arterial intimal thickening and plaque formation via mediating inflammatory response in the patients with type 2 diabetes.