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ABSTRACT: Probiotics and synbiotics can mitigate the negative health consequences of early-life antibiotic exposure. This study aimed to determine whether supplementation with Bifidobacterium longum ssp. infantis 79 (B79) or synbiotics composed of B79 and 2′-fucosyllactose (2′-FL) could mitigate the negative impact of ceftriaxone exposure in early life. We found that antibiotic-treated mice exhibited lower BW, crypt depth, short-chain fatty acid content, and α-diversity indices at weaning, whereas they had increased relative abundance of opportunistic pathogens (such as Enterococcus and Staphylococcus) and decreased relative abundance of intestinal commensal bacteria. Supplementation with B79 and 2′-FL revived these antibiotic-induced negative effects and reduced the mRNA expression of IL-6, IL-12p40, and TNF-α in the spleen at weaning. Moreover, B79 and 2′-FL supplementation persistently improved crypt depth, propionic acid synthesis, and IgG and secretory IgA production, as well as revived the gut microbiota structure and composition in adulthood. Overall, our study suggests that early-life supplementation with B79 alone or in combination with 2′-FL can mitigate ceftriaxone-induced negative effects on the gut microbiota and intestinal and immune development of mice, and these improvements can partially last into adulthood.

Human pose estimation in sports training is a critical application within Internet of Things (IoT) environments, leveraging IoT devices to enhance performance analysis and injury prevention. Current methods struggle with real-time processing and accuracy in dynamic settings, especially with high-speed movements and diverse data. To address these challenges, we propose a novel dual-channel architecture combining Spatiotemporal Transformer and Temporal Convolutional Network (TCN), integrated into an IoT system. Our model collects real-time motion data through IoT devices, including videos, depth information, and sensor data, combining global spatiotemporal features with local temporal dependencies to enhance pose understanding and estimation accuracy. The Spatiotemporal Transformer uses multi-head self-attention to process global features, while the TCN captures local temporal dependencies across frames. A residual fusion mechanism integrates these features for comprehensive pose estimation. Extensive experiments on the Human3.6M and MPI-INF-3DHP datasets demonstrate that our model significantly outperforms existing methods, achieving Mean Per Joint Position Error (MPJPE) scores of 42.2 mm and 29.1 mm on Human3.6M. This research advances 3D human pose estimation and offers a practical tool for sports training through precise, efficient pose analysis, leveraging deep learning and IoT technologies to enhance athletic performance and prevent injuries.

Abstract Background Retinal nerve fiber layer thickness, as a new visual indicator that may help diagnose mental disorders, is gaining attention from researchers. However, the causal relationship between retinal nerve fiber layer thickness and mental disorders is still to be effectively proved. Methods A bidirectional Two-sample Mendelian randomization analysis was utilized to analyse aggregated data from large-scale genome-wide association studies, we selected genetic loci for retinal nerve fiber layer thickness in independent retinal abnormalities and three prevalent psychiatric disorders (schizophrenia, depression, bipolar disorder) as instrumental variables. The Two-sample Mendelian randomization analysis was mainly performed by inverse variance weighting and weighted median method. The Cochran Q test and leave-one-out sensitivity were used to ensure the robustness of the results. The Mendelian random polymorphism residuals and outliers were used to detect single nucleotide polymorphism outliers, and MR-Egger intercept test was used to test single nucleotide polymorphism horizontal pleiotropy. Results IVW showed that retinal nerve fiber layer thickness was positively associated with schizophrenia (OR = 1.057, 95%CI: 1.000-1.117, P

Abstract Liver fibrosis is a hepatic scar repair response associated with a wide range of liver injuries, which is mediated by an imbalance between extracellular matrix (ECM) synthesis and degradation, leading to massive ECM deposition and disruption of normal liver architecture. Hepatic stellate cells (HSCs) are the main source of ECM during liver fibrosis and are the first identified cell subpopulation associated with liver fibrosis formation. Various current studies on the mechanism and treatment of liver fibrosis require resting‐state HSCs as study subjects. However, spontaneous activation of primary HSCs occurs after 2–3 days of culture after isolation, and it is common that HSCs cell lines gradually differentiate into fibroblasts with culture time. This study provides an induction medium for quiescent HSCs‐containing all‐trans retinoic acid, sodium oleate, and S‐nitroso‐N‐acetyl penicillamine (SNAP)‐and an induction method. The induction method not only maintains the HSCs cell line in a quiescent state but also restores the activated HSCs to a quiescent state. The method has a good induction effect, short induction time, and convenient operation, which is worth being popularized and used in a wide range of laboratories.

Brucellosis is a global zoonotic infection caused by Brucella bacteria, which poses a significant burden on society. While transmission prevention is currently the most effective method, the absence of a licenced vaccine for humans necessitates the urgent development of a safe and effective vaccine. Recombinant protein-based subunit vaccines are considered promising options, and in this study, the Brucella BP26 protein is expressed using prokaryotic expression systems. The immune responses are evaluated using the well-established adjuvant CpG-ODN. The results demonstrate that rBP26 supplemented with a CpG adjuvant induces M1 macrophage polarization and stimulates cellular immune responses mediated by Th1 cells and CD8+ T cells. Additionally, it generates high levels of rBP26-specific antibodies in immunized mice. Furthermore, rBP26 immunization activates, proliferates, and produces cytokines in T lymphocytes while also maintaining immune memory for an extended period of time. These findings shed light on the potential biological function of rBP26, which is crucial for understanding brucellosis pathogenesis. Moreover, rBP26 holds promise as an effective subunit vaccine candidate for use in endemic areas.

Due to the significant threat to forest health posed by beetle infestations on pine trees, timely and accurate predictions are crucial for effective forest management. This study developed a pine tree stress probability prediction workflow based on monthly cloud-free Sentinel-2 composite images to address this challenge. First, representative pine tree stress samples were selected by combining long-term forest disturbance data using the Continuous Change Detection and Classification (CCDC) algorithm with high-resolution remote sensing imagery. Monthly cloud-free Sentinel-2 images were then composited using the Multifactor Weighting (MFW) method. Finally, a Random Forest (RF) algorithm was employed to build the pine tree stress probability model and analyze the importance of spectral, topographic, and meteorological features. The model achieved prediction precisions of 0.876, 0.900, and 0.883, and overall accuracies of 89.5%, 91.6%, and 90.2% for January, February, and March 2023, respectively. The results indicate that spectral features, such as band reflectance and vegetation indices, ranked among the top five in importance (i.e., SWIR2, SWIR1, Red band, NDVI, and NBR). They more effectively reflected changes in canopy pigments and leaf moisture content under stress compared with topographic and meteorological features. Additionally, combining long-term stress disturbance data with high-resolution imagery to select training samples improved their spatial and temporal representativeness, enhancing the model’s predictive capability. This approach provides valuable insights for improving forest health monitoring and uncovers opportunities to predict future beetle outbreaks and take preventive measures.

With the increasing share of renewable energy generation and the integration of large-scale electric vehicles (EVs) into the grid, the reasonable charging and discharging scheduling of electric vehicles is essential for the stable operation of power grid. Therefore, this paper proposes a bi-objective optimal scheduling strategy for microgrids based on the participation of electric vehicles in vehicle-to-grid technology (V2G) mode. Firstly, the system structure for electric vehicles participating in the charging and discharging schedule was established. Secondly, a bi-objective optimization model was formulated, considering load mean square error and user charging cost. A heuristic method was employed to handle constraints related to system energy balance and equipment output. Then, the Monte Carlo method was employed to simulate electric vehicle loads and to facilitate the generation of and reduction in scenario scenes. Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. The simulation results show that the proposed scheduling strategy has a lower charging cost (CNY 11,032.4) and lower load mean square error (12.84 × 105 kW2) than the strategy employed in the comparison experiment, which ensures the economic and stable operation of the microgrid.

In conventional message communication systems, the practice of multi-message multi-receiver signcryption communication encounters several challenges, including the vulnerability to Key Generation Center (KGC) attacks, privacy breaches and excessive communication data volume. The KGC necessitates a secure channel to transmit partial private keys, thereby rendering the security of these partial private keys reliant on the integrity of the interaction channel. This dependence introduces concerns regarding the confidentiality of the private keys. Our proposal advocates for the substitution of the KGC in traditional certificateless schemes with blockchain and smart contract technology. Parameters are publicly disclosed on the blockchain, leveraging its tamper-proof property to ensure security. Furthermore, this scheme introduces conventional encryption techniques to achieve user identity privacy in the absence of a secure channel, effectively resolving the issue of user identity disclosure inherent in blockchain-based schemes and enhancing communication privacy. Moreover, users utilize smart contract algorithms to generate a portion of the encrypted private key, thereby minimizing the possibility of third-party attacks. In this paper, the scheme exhibits resilience against various attacks, including KGC leakage attacks, internal privilege attacks, replay attacks, distributed denial of service attacks and Man-in-the-Middle (MITM) attacks. Additionally, it possesses desirable security attributes such as key escrow security and non-repudiation. The proposed scheme has been theoretically and experimentally analyzed under the random oracle model, based on the computational Diffie-Hellman problem and the discrete logarithm problem. It has been proven to possess confidentiality and unforgeability. Compared with similar schemes, our scheme has lower computational cost and shorter ciphertext length. It has obvious advantages in communication and time overhead.

Forest stands, crucial for inventory, planning, and management, traditionally rely on time-consuming visual analysis by forest managers. To enhance efficiency, there is a growing need for automated methods that take into account essential forest attributes. In response, we propose a novel approach utilizing airborne Light Detection and Ranging (LiDAR) and hyperspectral data for automated forest stand delineation. Our approach initiates with over-segmentation of the Canopy Height Model (CHM), followed by attribute calculation for each segment using both CHM and hyperspectral data. Two rules are applied to merge homogeneous segments and eliminate others based on calculated attributes. The effectiveness of our method was validated using three types of reference forest stands with two indices: the explained variance (R2) and Intersection over Union (IoU). Results from our study demonstrated notable accuracy, with a R2 of 97.35% and 97.86% for mean tree height and mean diameter at breast height (DBH), respectively. The R2 for mean canopy height is 81.80%, outperforming manual delineation by 7.31% and multi-scale segmentation results by 2.13%. Furthermore, our approach achieved high IoU values, which indicates a strong spatial agreement with manually delineated forest stands and leading to fewer manual adjustments when applied directly to forest management. In conclusion, our forest stand delineation method enhances both internal consistency and spatial accuracy. This method contributes to improving practical performance and forest management efficiency.

Abstract Retinoic acid (RA) serves as a metabolic intermediate of vitamin A. It plays a crucial physiological role in regulating cell proliferation, differentiation, apoptosis, embryonic development, and immunomodulation. Once vitamin A enters the body in the form of retinol, it undergoes conversion into RA through the intestinal epithelium and liver. Subsequently, it interacts with retinoic acid receptors and retinoid X receptors within the cell nucleus, thereby regulating gene expression. Throughout liver development, RA exerts precise temporal control, stimulating liver growth, inducing RALDH2 expression in liver somatic epithelial cells, and influencing hepatocyte differentiation. Recent studies have consistently demonstrated the indispensable connection between RA deficiency and the development of liver diseases, including nonalcoholic fatty liver disease, chronic hepatitis, liver fibrosis, and liver tumors. Studying the mechanisms underlying the relationship between RA and disease can enhance our understanding and improve disease treatment. This paper provides a comprehensive review of the role of RA signaling in liver development and liver diseases.

ABSTRACTForest Stock Volume (FSV) is one of the key indicators in forestry resource investigation and management on local, regional, and national scales. Limited by the saturation problems of optical satellite remote-sensing imagery in the retrieving of stock volume, and the high cost of Light Detection And Ranging (LiDAR) data, it is still challenging to estimate FSV in a large area using single-sensor remote-sensing data. In this paper, a method integrated multispectral satellite imagery and LiDAR data was developed to map stock volume in a large area. A random forest model was adopted to estimate the stock volume of larch forest in China based on the training samples from the Airborne Laser Scanning (ALS)-derived stock volume and corresponding Sentinel-2 imagery. Validation using National Forest Inventory (NFI) data, ALS-derived stock volume and ground investigation data demonstrated that the estimated stock volume had a high accuracy (R2 = 0.59, RMSE = 59.69 m3/ha, MD = 39.96 m3/ha when validated with NFI data; R2 ranged from 0.77 to 0.85, RMSE ranged from 38.68 m3/ha to 67.38 m3/ha, MD ranged from 24.90 m3/ha to 37.27 m3/ha when validated with ALS stock volume; R2 = 0.42, RMSE = 79.10 m3/ha, MD = 62.06 m3/ha when validated with field investigation data). Results of this paper indicated the applicability of estimating stock volume of larch forest in a large area by combining Sentinel-2 data and airborne LiDAR data.

Aims The objective of this study is to examine the impact of inhibiting Sphingosine 1-phosphate receptor 2 (S1PR2) on liver inflammation, fibrogenesis, and changes of gut microbiome in the context of cholestasis-induced conditions. Methods The cholestatic liver injury model was developed by common bile duct ligation (CBDL). Sprague-Dawley rats were randomly allocated to three groups, sham operation, CBDL group and JTE-013 treated CBDL group. Biochemical and histological assessments were conducted to investigate the influence of S1PR2 on the modulation of fibrogenic factors and inflammatory infiltration. We conducted an analysis of the fecal microbiome by using 16S rRNA sequencing. Serum bile acid composition was evaluated through the utilization of liquid chromatography-mass spectrometry techniques. Results In the BDL rat model, the study findings revealed a significant increase in serum levels of conjugated bile acids, accompanied by an overexpression of S1PR2. Treatment with the specific inhibitor of S1PR2, known as JTE-013, resulted in a range of specific effects on the BDL rats. These effects included the improvement of liver function, reduction of liver inflammation, inhibition of hepatocyte apoptosis, and suppression of NETosis. These effects are likely mediated through the TCA/S1PR2/NOX2/NLRP3 pathway. Furthermore, the administration of JTE-013 resulted in an augmentation of the diversity of the bacterial community’s diversity, facilitating the proliferation of advantageous species while concurrently inhibiting the prevalence of detrimental bacteria. Conclusions The results of our study suggest that the administration of JTE-013 may have a beneficial effect in alleviating cholestatic liver disease and restoring the balance of intestinal flora.

Background: Current evidence shows that systemic dexamethasone administration starting after the first week of age reduces bronchopulmonary dysplasia for very preterm (VPT) infants, but its neurological effects remain obscure. Using resting-state functional magnetic resonance imaging (rs-fMRI), we assessed the changes in functional network connectivity (FNC) in very preterm infants treated with late systemic dexamethasone (≥7 days of age). Methods: VPT infants (GA ≤ 32 weeks) who needed to rely on mechanical ventilation for more than 7 days but fewer than 14 days to maintain vital signs were included in the study. The cohort was divided into two groups according to whether they were given systemic dexamethasone. In addition, 26 healthy term infants were recruited as controls. At term-equivalent age (TEA), rs-fMRI and 3D-T1 data from eligible infants were acquired with a 3.0-T MRI scanner. After the MRI data were preprocessed, group-level independent component analysis (ICA), a technique used for blind source separation, was used to identify the components of resting-state networks (RSNs). Then, the functional connectivity between components and RSNs was compared among different groups. Upon follow-up at 3 months of corrected age, the neurodevelopmental outcomes of enrolled infants were assessed with the Bayley Scales of Infant Development–Chinese Revision (BSID-CR), and the Motor Development Index (MDI) and Psychomotor Development Index (PDI) were measured. Finally, the correlations between resting-state FNC and BSID scores were analysed. Results: Ultimately, 59 infants were included in the final analysis, including 19 preterm infants who received dexamethasone, 20 who did not, and 20 healthy term infants as controls. Based on their data, 11 components were identified, belonging to 5 RSNs: the visual network (VN), the dorsal attention network (DAN), the auditory network (AN), the primary sensorimotor network (SMN), and the default-mode network (DMN). Compared with the term infants, the preterm infants showed significantly weakened functional connectivity between the DAN and VN, as well as the VN and AN (P

From the perspective of food packaging design, the interaction between packaging and consumer behaviors was explored through the analysis of their demand trends. This review analyzed the performance characteristics of consumer experience at instinct level, behavior level and reflection level between users and packaging, and discussed the design strategies of food packaging at different levels. In view of the multi-dimensional needs of consumers, the emotional responses to products from visual and non-visual sensory experience at the instinct level can be responded and thereby attract their attentions. At the behavioral level, it starts from interesting, humanized and intelligent interaction, prompt and feedback to expand the use function of the product and create a good use experience. On the reflection level, starting from creating interactive experience to stimulate users' creativity. The creation of interactive experience and stimulation of user creativity were focused on to systematically shape deep emotional experience at the reflection level. Integrating user experience into food packaging design effectively and exploring the process of information experience will be a new idea and direction of food packaging design in the future.

Chromium from industrial wastewater, waste, pesticides, fertilizers, etc., always causes serious environmental problems. High levels of chromium pollution can have adverse effects on environments and living organisms. In this study, titanium salt was used to react with green tea extract to form a composite material, and the material was further used to remove hexavalent chromium in solution. The removal effect of hexavalent chromium was investigated under different reaction conditions, namely temperature, time, pH, and initial chromium concentration. The results showed that the chromium removal effect was the best under the conditions of acid to neutral pH, 45℃, reaction time of 24 h, and initial chromium concentration of 80 mg/L. This study provides a feasible method to solve the problem of chromium pollution and has high application value in wastewater treatment.

Abstract Background Necrotizing enterocolitis (NEC) is one of serious gastrointestinal inflammatory diseases in newborn infants, with a high morbidity and mortality. Red blood cell transfusion (RBCT) plays a controversial and doubtful role in the treatment of NEC. In present study, we aim to analyze the association between RBCT and the deterioration of NEC. Methods This was a retrospective cohort study of near-term and full-term infants with a confirmed diagnosis of Bell’s stage II NEC between Jan 1, 2010 and Jan 31, 2020. The maternal and infant baseline characteristics, treatment information and laboratory test for each case were collected. The eligible subjects were divided into two groups based on receiving RBCT post NEC diagnosis or not. The propensity score was used to eliminate potential bias and baseline differences. A multivariate logistic regression model was used to adjust the propensity score and calculate the odds ratio (OR) and 95% confidential interval (CI) of RBCT for the deterioration of NEC. Results A total of 242 infants were included in this study, 60 infants had a history of RBCT post NEC diagnosis, and 40 infants deteriorated from Bell’s stage II to stage III. By adjusting the propensity score, RBCT post NEC diagnosis was associated with an increased risk for NEC deteriorating from stage II to III (adjusted OR 6.06, 95%CI 2.94–12.50, P = 0.000). Conclusions NEC infants who required RBCT post NEC diagnosis were more likely to deteriorate from stage II to III in full-term and near-term infants.

At present, deep learning is a hot topic in the field of the classification of hyperspectral image (HSI), and it has aroused wide attention. However, in fine-grained classification tasks, such as tree species classification, the uncertain spectrum remains the major factor restraining the classification performance. In order to solve the dilemma of forest tree species classification, a dual-concentrated network with morphological features (DNMF) is proposed. First, mathematical morphology is used to extract the morphological features of HSI. Then, coarse-grained information is extracted from the original hyperspectral data, and fine-grained information is extracted from morphological features. After that, both morphological representations and spectral inputs are fed into DNMF, and the overall evaluation index and visual image are obtained. The advantage of DNMF is that it decouples the spatial and spectral information, and a multisource information fusion process is then simulated. Accordingly, DNMF obtains high tree species classification accuracy. In order to verify the superiority of DNMF, we choose Gaofeng State-owned Forest Farm in Guangxi Province and the Belgium dataset, which was collected near the western part of Belgium as the research area. Related experiments demonstrate that the DNMF model achieves clearly better classification performance over other competitive baselines.

BackgroundNecrotizing enterocolitis (NEC) is a devastating intestinal complication that occurs mainly in very-low-birth-weight infants (VLBWI). The study's aim was to investigate the possibility of early prediction of NEC on postnatal day 1 based on superior mesenteric artery (SMA) doppler ultrasonograpy.MethodsA prospective, observational, nested case control study (ChiCTR1900026197) was conducted to enroll VLBWIs (birth weight

BackgroundImpairment in cognitive function is a recognized outcome of traumatic brain injury (TBI). However, the degree of impairment has variable relationship with TBI severity and time post injury. The underlying pathology is often due to diffuse axonal injury that has been found even in mild TBI. In this study, we examine the state of white matter putative connectivity in patients with non-severe TBI in the subacute phase, i.e., within 10 weeks of injury and determine its relationship with neuropsychological scores.MethodsWe conducted a case-control prospective study involving 11 male adult patients with non-severe TBI and an age-matched control group of 11 adult male volunteers. Diffusion MRI scanning and neuropsychological tests were administered within 10 weeks post injury. The difference in fractional anisotropy (FA) values between the patient and control groups was examined using tract-based spatial statistics. The FA values that were significantly different between patients and controls were then correlated with neuropsychological tests in the patient group.ResultsSeveral clusters with peak voxels of significant FA reductions (p < 0.05) in the white matter skeleton were seen in patients compared to the control group. These clusters were located in the superior fronto-occipital fasciculus, superior longitudinal fasciculus, uncinate fasciculus, and cingulum, as well as white matter fibers in the area of genu of corpus callosum, anterior corona radiata, superior corona radiata, anterior thalamic radiation and part of inferior frontal gyrus. Mean global FA magnitude correlated significantly with MAVLT immediate recall scores while matrix reasoning scores correlated positively with FA values in the area of right superior fronto-occipital fasciculus and left anterior corona radiata.ConclusionThe non-severe TBI patients had abnormally reduced FA values in multiple regions compared to controls that correlated with several measures of executive function during the sub-acute phase of TBI.

Graphene aerogels/epoxy composites were prepared by vacuum-impregnated process with graphene aerogels as the functional filler and epoxy resin as polymer matrix. The changes in chemical structure of graphene aerogels during the preparation process and carbonization treatment were investigated by FT-IR, XPS and XRD. The results show that GO@PAA aerogel is prepared by the physical interaction between graphene oxide (GO) and polyamide acid (PAA). PAA will be transformed to polyimide by imidization and graphene oxide is partially reduced during the 300 ℃ thermal treatment. With the carbonation temperature increases, reduction degree of graphene sheets and the carbonation degree of polyimide are increased gradually. Meanwhile, SEM images and OM images show that graphene aerogels can also maintain the good three-dimensional network structure after carbonation treatment and vacuum impregnation. On this basis, graphene aerogels, which serve as the functional filler, taking advantage of the good three-dimensional network structure,can improve the corresponding composites with good electrical property and electromagnetic interference shielding performance. With only 6.23%(mass fraction) graphene aerogels (G@C-1100), the corresponding composites exhibit high electrical conductivity of 252 S·m-1 and an excellent electromagnetic interference shielding effectiveness of 70 dB.

Graphene/carbon fiber/epoxy composites were prepared by autoclave co-curing molding process with graphene prepregs as the functional layer, which were paved on the surface of carbon fiber perform. The effect of graphene prepregs on the internal quality, electromagnetic interference shielding performance and mechanical properties of the composites was investigated by ultrasound scanner, metallograph, four-probe instrument, vector network analyzer and electronic universal material testing machine. The results show that the internal quality of the graphene/carbon fiber/epoxy composites will not be influenced by the addition of graphene prepregs, and there are a good interfacial compatibility between graphene functional layer and carbon fiber structural layer. On this basis, graphene prepregs, which serves as the functional layer, taking advantage of excellent electrical conductivity, can improve the electromagnetic interference shielding performance of the corresponding composites rapidly. With only one layer of graphene prepreg (G105/3234), electromagnetic interference shielding efficiency of carbon fiber/epoxy composites is improved from 27.7 dB to 64.7 dB. Meanwhile, the obtained composites still maintain satisfactory mechanical properties.

Abstract Background Diagnosis and follow-up of retinal diseases may be improved if the thickness of the various retinal layers, in addition to the total retinal thickness, is taken into account. Here we measured the thickness of the macular retinal layers in a population-based study group to assess the normative values and their associations. Methods Using spectral-domain optical coherence tomographic images (Spectralis®, wavelength: 870 nm; Heidelberg Engineering Co, Heidelberg, Germany), we measured the thickness of the macular retinal layers in participants of the population-based Beijing Eye Study without ocular diseases and without systematic diseases, such as arterial hypertension, hyperlipidemia, diabetes mellitus, cardiovascular diseases, previous myocardial infarction, cerebral trauma and stroke. Segmentation and measurement of the retinal layers was performed automatically in each of the horizontal scans. Results The study included 384 subjects (mean age:60.0 ± 8.0 years). The mean thickness of the whole retina, outer plexiform layer, outer nuclear layer,retinal pigment epithelium, inner retinal layer and photoreceptor layer was 259.8 ± 18.9 μm, 19.4 ± 3.9 μm, 93.4 ± 9.6 μm, 17.6 ± 1.9 μm, 169.8 ± 18.6 μm, and 90.0 ± 4.2 μm, respectively. In multivariable analysis, the thickness of the foveola and of all retinal layers in the foveal, parafoveal and perifoveal region decreased with older age (all P

The debilitating effect of traumatic brain injury (TBI) extends years after the initial injury and hampers the recovery process and quality of life. In this study, we explore the functional reorganization of the default mode network (DMN) of those affected with non-severe TBI. Traumatic brain injury (TBI) is a wide-spectrum disease that has heterogeneous effects on its victims and impacts everyday functioning. The functional disruption of the default mode network (DMN) after TBI has been established, but its link to causal effective connectivity remains to be explored. This study investigated the differences in the DMN between healthy participants and mild and moderate TBI, in terms of functional and effective connectivity using resting-state functional magnetic resonance imaging (fMRI). Nineteen non-severe TBI (mean age 30.84 ± 14.56) and twenty-two healthy (HC; mean age 27.23 ± 6.32) participants were recruited for this study. Resting-state fMRI data were obtained at the subacute phase (mean days 40.63 ± 10.14) and analyzed for functional activation and connectivity, independent component analysis, and effective connectivity within and between the DMN. Neuropsychological tests were also performed to assess the cognitive and memory domains. Compared to the HC, the TBI group exhibited lower activation in the thalamus, as well as significant functional hypoconnectivity between DMN and LN. Within the DMN nodes, decreased activations were detected in the left inferior parietal lobule, precuneus, and right superior frontal gyrus. Altered effective connectivities were also observed in the TBI group and were linked to the diminished activation in the left parietal region and precuneus. With regard to intra-DMN connectivity within the TBI group, positive correlations were found in verbal and visual memory with the language network, while a negative correlation was found in the cognitive domain with the visual network. Our results suggested that aberrant activities and functional connectivities within the DMN and with other RSNs were accompanied by the altered effective connectivities in the TBI group. These alterations were associated with impaired cognitive and memory domains in the TBI group, in particular within the language domain. These findings may provide insight for future TBI observational and interventional research.

The epithelial-mesenchymal transition (EMT) is a cellular process critical for wound healing, cancer metastasis and embryonic development. Recent efforts have identified the role of hybrid epithelial/mesenchymal states, having both epithelial and mesehncymal traits, in enabling cancer metastasis and resistance to various therapies. Also, previous work has suggested that NRF2 can act as phenotypic stability factor to help stablize such hybrid states. Here, we incorporate a phenomenological epigenetic feedback effect into our previous computational model for EMT signaling. We show that this type of feedback can stabilize the hybrid state as compared to the fully mesenchymal phenotype if NRF2 can influence SNAIL at an epigenetic level, as this link makes transitions out of hybrid state more difficult. However, epigenetic regulation on other NRF2-related links do not significantly change the EMT dynamics. Finally, we considered possible cell division effects in our epigenetic regulation model, and our results indicate that the degree of epigenetic inheritance does not appear to be a critical factor for the hybrid E/M state stabilizing behavior of NRF2.

BackgroundTakayasu’s arteritis (TA) is a type of primary large vessel vasculitis. Th1, Th17, and Tfh cells have been reported to be associated with TA relapse. However, the relationship between regulatory T cells (Tregs) and TA remains unclear.ObjectiveTo analyze the levels of circulating lymphocytes, especially Treg cells (CD4+CD25+FOXP3+ T cells) and serum cytokines in TA patients and explore their relationship with their changes and TA disease activity.MethodsA total of 57 TA patients and 43 sex- and age-matched healthy controls (HCs) were enrolled. According to NIH standards, 36 patients had active disease status. Flow cytometry combined with counting was used to detect the absolute numbers and ratios of Th1, Th2, Th17, and Treg cells in the peripheral blood of all the subjects. Magnetic bead-based multiplex immunoassay was used to detect cytokines.ResultsCompared to HCs, the absolute number and proportion of peripheral Treg cells in TA patients was significantly decreased, while Th17 cells were significantly increased. Furthermore, compared to the inactive group, the TA active group had significantly increased levels of interleukin (IL)-6, IL-10, and tumor necrosis factor (TNF)-α, but lower IL-10 levels. The absolute number of Th2 cells was negatively associated with platelet (PLT) and NIS scores in TA patients. The proportion of Th2 cells was negatively associated with the erythrocyte sedimentation rate in TA patients. After treatment, Treg cells were markedly increased.ConclusionThere was a Th17-Treg cell imbalance with a significant reduction in peripheral Treg cells and an increase in Th17 cells in TA patients compared to the HCs. The levels of IL-6, IL-10, IL-17, and TNF-α appeared to be related to disease activity.

Many concrete structures in use have safety problems due to material deterioration, actual construction defects, structural damage, etc. Therefore, nondestructive testing is required to determine the presence of defects. Ultrasonic technology is an important tool in nondestructive testing, which can detect defects in concrete and be combined with other methods or models to make it more accurate. At present, ultrasonic inspection technology has been more research at home and abroad, both in theory and in engineering, and there has been great progress. This paper summarizes the latest progress of ultrasonic inspection technology for concrete structures at home and abroad respectively, and points out the future development trend.

This paper presents a smartphone-based binaural hearing aid architecture for improving the speech intelligibility of hearing aid users. The proposed system consists of an earpiece, a smartphone and an application that performs real-time speech enhancement. The speaker's voice, which is picked up by the microphone of the earpiece that is worn on the ear, is transmitted to the smartphone via wireless technology. After the speech intelligibility is improved in real time by the deep learning speech enhancement application, it is returned to the earpiece and generates sound. Deep learning speech enhancement algorithms can be used without performing burdensome calculations on the processors in the hearing aid. The results showed that the average usage of the central processing unit in the smartphone was approximately 26%, and the signal-to-noise ratios improve by at least 20%. The presented objective and subjective results show that the proposed method achieves comparatively more noise suppression without distorting the audio.

In this article, we set up a novel audio dataset named Gastrointestinal (GI) Sound Set which includes 6 kinds of body sounds Bowel sound, Speech, Snore, Cough, Groan, and Rub. We do sound event detection (SED) based on it, and can accurately detect 6 types of sound events. First, the GI Sound Set is collected by wearable auscultation devices. To ensure generalization, patients from five different hospital departments are recruited for data collection, along with a group of healthy subjects. GI Sound Set refers to Google AudioSet in data format but varies in audio length and sampling rate. Second, we extract Mel-filter features from the recordings and investigate the performance of different activation functions and neural network architectures for detecting sound events. We use data augmentation, class balance to deal with the problem of quantitative imbalance between classes on the dataset. We apply multiple instances learning(MIL) to give out not only bag-level results but also frame-level results. In this work, GI Sound Set is the largest body sound dataset to date, and our approach shows state-of-the-art performance with an average score of F1=81.06% evaluated on the test set. Due to its simple network and conventional processing method, our CRNN system has high universality, which can be used in other audio datasets, such as respiratory sound and heart sound.

Abstract Background Hepatitis B e antigen (HBeAg) seroconversion represents an endpoint of treatment of chronic hepatitis B virus (HBV) infections. Methods We have studied whether levels of serum hepatitis B virus ribonucleic acid (HBV RNA) during pegylated interferon alfa-2a treatment might be helpful for predicting HBeAg seroconversion. 61 HBeAg-positive chronic hepatitis B (CHB) patients treated with pegylated interferon alfa-2a alone or in combination with adefovir (10 mg/day) for 48 weeks were included in this retrospective analysis. Response was defined as HBeAg seroconversion at 24 weeks posttreatment. Receiver operating characteristic analyses were used to identify baseline and on-treatment HBV RNA levels associated with response. Results Twenty-two of 61 (36.1%) patients achieved a response. Baseline HBV RNA levels were lower in responders than in nonresponders (4.55 ± 1.19 and 5.90 ± 1.13 copies/mL, respectively, P = 0.001). Baseline HBV RNA cut off level (200,000 copies/mL) provided a positive predictive value (PPV) of 56.0% and a negative predictive value (NPV) of 77.8%. HBV RNA level (3000 copies/mL) at week 12 provide a PPV of 75.0% and a NPV of 82.8%. Moreover, HBeAg seroconversion rates at 24 weeks posttreatment were significantly higher in patients with HBV RNA ≤ 200,000 copies/mL at baseline and HBV RNA ≤ 3000 copies/mL at week 12 (92.9%) versus others (12.5%) (All P

Photosynthetic light use efficiency (LUE) determines the ability of a plant to assimilate atmospheric carbon dioxide to biomass and is known to be controlled by environmental conditions, light regimes and forest age. The photochemical reflectance index (PRI), derived from leaf or canopy remotely sensed spectra, has been shown to be an effective and accurate estimator of LUE. In this study, we propose a new LUE estimation method that separates the PRI into daily maximal PRI (PRI0) for indicating daily maximal light use efficiency (LUEmax) and ΔPRI, defined as the difference between PRI0 and instantaneous PRI, for estimating the diurnal physiological stress (fstress). We develop and apply the method across three temperate pine stands and a deciduous stand of different ages, in Southern Ontario, Canada. Half hourly canopy level spectra were acquired from a tower-based spectro-radiometer system (AMSPEC-III) over the growing season at the four stands. Results show that the PRI0 predicted well LUEmax (R2 > 0.6, p

Approximately one in five children worldwide suffers from childhood malnutrition and its complications, including increased susceptibility to inflammation and infectious diseases. Due to improved early interventions, most of these children now survive early malnutrition, even in low-resource settings (LRS). However, many continue to exhibit neurodevelopmental deficits, including low IQ, poor school performance, and behavioral problems over their lifetimes. Most studies have relied on neuropsychological tests, school performance, and mental health and behavioral measures. Few studies, in contrast, have assessed brain structure and function, and to date, these have mainly relied on low-cost techniques, including electroencephalography (EEG) and evoked potentials (ERP). The use of more advanced methods of neuroimaging, including magnetic resonance imaging (MRI) and functional near-infrared spectroscopy (fNIRS), has been limited by cost factors and lack of availability of these technologies in developing countries, where malnutrition is nearly ubiquitous. This report summarizes the current state of knowledge and evidence gaps regarding childhood malnutrition and the study of its impact on neurodevelopment. It may help to inform the development of new strategies to improve the identification, classification, and treatment of neurodevelopmental disabilities in underserved populations at the highest risk for childhood malnutrition.

Abstract Background It has been suggested that mild hypothermia treatment of hypoxia-ischemic encephalopathy (HIE) should start within 6 h after HIE, but many children are admitted to the hospital > 6 h, particularly in developing areas. We aimed to determine whether hypothermia treatment could remain effective within 12 h after birth. Methods According to their admission, 152 newborns were enrolled in the 0.05). Hypothermia improved the rates of neonatal death and 18-month disability (all P

Since genotype imputation was introduced, researchers have been relying on the estimated imputation quality from imputation software to perform post-imputation quality control (QC). However, this quality estimate (denoted as Rsq) performs less well for lower-frequency variants. We recently published MagicalRsq, a machine-learning-based imputation quality calibration, which leverages additional typed markers from the same cohort and outperforms Rsq as a QC metric. In this work, we extended the original MagicalRsq to allow cross-cohort model training and named the new model MagicalRsq-X. We removed the cohort-specific estimated minor allele frequency and included linkage disequilibrium scores and recombination rates as additional features. Leveraging whole-genome sequencing data from TOPMed, specifically participants in the BioMe, JHS, WHI, and MESA studies, we performed comprehensive cross-cohort evaluations for predominantly European and African ancestral individuals based on their inferred global ancestry with the 1000 Genomes and Human Genome Diversity Project data as reference. Our results suggest MagicalRsq-X outperforms Rsq in almost every setting, with 7.3%-14.4% improvement in squared Pearson correlation with true R2, corresponding to 85-218 K variant gains. We further developed a metric to quantify the genetic distances of a target cohort relative to a reference cohort and showed that such metric largely explained the performance of MagicalRsq-X models. Finally, we found MagicalRsq-X saved up to 53 known genome-wide significant variants in one of the largest blood cell trait GWASs that would be missed using the original Rsq for QC. In conclusion, MagicalRsq-X shows superiority for post-imputation QC and benefits genetic studies by distinguishing well and poorly imputed lower-frequency variants.

This paper proposes a method for the passive positioning of sound target based on the Hanbury and Brown-Twiss (HBT) interference that is commonly used in ultra-sensitive optical measurements. The method based on HBT interference is first theoretically analyzed to determine the relation between the coherence of the signal and the position of the target. A model of target positioning based on HBT interference in the sound field is then formulated to simulate the position of the target at different frequencies and positions, and the positioning performance of the proposed method is analyzed. Experiments were carried out to verify the feasibility and accuracy of the proposed method based on HBT interference, and the results were in good agreement with those of the simulation and positioning errors were smaller than 0.1 m. The proposed method based on HBT interference positioning is thus reliable and viable for passive positioning of the source of sound.