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Apis cerana is the original host of Vairimorpha (Nosema) ceranae, a widespread fungal parasite that causes bee nosemosis, which severely threatens the health of bee colonies and the sustainable development of the apiculture industry. To evaluate the impact of V. ceranae infection on A. c. cerana workers, V. ceranae spores were purified and used to inoculate newly emerged workers to evaluate the effects of V. ceranae infection. This was followed by an in-depth investigation of V. ceranae spore load and host sucrose solution consumption. Activities of four major antioxidant enzymes (SOD, PPO, CAT, and GST) were determined. Paraffin sections of the host midgut tissue were prepared and subjected to microscopic observation. The survival rates of V. ceranae-inoculated and uninoculated workers were analyzed. The results showed that spore load gradually increased and peaked at 12 dpi. The consumption of workers in the V. ceranae-inoculated group was extremely significant higher (P < 0.0001) than that of workers in the un-inoculated group. The results of antioxidant enzyme activity were suggestive of positive host defense via catalase (CAT) and glutathione-S-transferase (GST) in the middle stage of infection, as well as the negative fungal impact on superoxide dismutase (SOD) and polyphenol oxidase (PPO) at the whole stage of infection, reflecting the complex host-parasite interaction. Additionally, we observed a disruption in the structure of the host midgut epithelial cells. Moreover, the survival rate of workers in V. ceranae-inoculated groups was nearly always lower than that of workers in the uninoculated groups. These results demonstrate a consistent increase in spore load with the proliferation of V. ceranae, leading to persistent energetic stress and midgut epithelial cell structural damage to the host, ultimately resulting in a shortened lifespan for the host. Our findings enhance the current understanding of the interactions between A. cerana and V. ceranae as well as provide a solid basis for exploring the mechanisms underlying host response and V. ceranae infection.

Abstract Background Multicenter non-small cell lung cancer (NSCLC) patient data is information-rich. However, its direct integration becomes exceptionally challenging due to constraints involving different healthcare organizations and regulations. Traditional centralized machine learning methods require centralizing these sensitive medical data for training, posing risks of patient privacy leakage and data security issues. In this context, federated learning (FL) has attracted much attention as a distributed machine learning framework. It effectively addresses this contradiction by preserving data locally, conducting local model training, and aggregating model parameters. This approach enables the utilization of multicenter data with maximum benefit while ensuring privacy safeguards. Based on pre-radiotherapy planning target volume images of NSCLC patients, a multicenter treatment response prediction model is designed by FL for predicting the probability of remission of NSCLC patients. This approach ensures medical data privacy, high prediction accuracy and computing efficiency, offering valuable insights for clinical decision-making. Methods We retrospectively collected CT images from 245 NSCLC patients undergoing chemotherapy and radiotherapy (CRT) in four Chinese hospitals. In a simulation environment, we compared the performance of the centralized deep learning (DL) model with that of the FL model using data from two sites. Additionally, due to the unavailability of data from one hospital, we established a real-world FL model using data from three sites. Assessments were conducted using measures such as accuracy, receiver operating characteristic curve, and confusion matrices. Results The model’s prediction performance obtained using FL methods outperforms that of traditional centralized learning methods. In the comparative experiment, the DL model achieves an AUC of 0.718/0.695, while the FL model demonstrates an AUC of 0.725/0.689, with real-world FL model achieving an AUC of 0.698/0.672. Conclusions We demonstrate that the performance of a FL predictive model, developed by combining convolutional neural networks (CNNs) with data from multiple medical centers, is comparable to that of a traditional DL model obtained through centralized training. It can efficiently predict CRT treatment response in NSCLC patients while preserving privacy.

Abstract Background The total-body positron emission tomography/computed tomography (PET/CT) system, with a long axial field of view, represents the state-of-the-art PET imaging technique. Recently, the total-body PET/CT system has been commercially available. The total-body PET/CT system enables high-resolution whole-body imaging, even under extreme conditions such as ultra-low dose, extremely fast imaging speed, delayed imaging more than 10 h after tracer injection, and total-body dynamic scan. The total-body PET/CT system provides a real-time picture of the tracers of all organs across the body, which not only helps to explain normal human physiological process, but also facilitates the comprehensive assessment of systemic diseases. In addition, the total-body PET/CT system may play critical roles in other medical fields, including cancer imaging, drug development and immunology. Main body Therefore, it is of significance to summarize the existing studies of the total-body PET/CT systems and point out its future direction. This review collected research literatures from the PubMed database since the advent of commercially available total-body PET/CT systems to the present, and was divided into the following sections: Firstly, a brief introduction to the total-body PET/CT system was presented, followed by a summary of the literature on the performance evaluation of the total-body PET/CT. Then, the research and clinical applications of the total-body PET/CT were discussed. Fourthly, deep learning studies based on total-body PET imaging was reviewed. At last, the shortcomings of existing research and future directions for the total-body PET/CT were discussed. Conclusion Due to its technical advantages, the total-body PET/CT system is bound to play a greater role in clinical practice in the future.

The miRNA plays a key role in the regulation of hormone signaling in insects. The pathways by which miRNAs affect hormone levels are unclear in the honeybee (Apis mellifera), an indispensable pollinator in nature. In this study, ame-miR-5119 was overexpressed and knocked down in larvae by feeding mimics and inhibitors, respectively, and we determined that ame-miR-5119 regulates hormone signaling through the target gene ecdysis triggering hormone (Eth), which affects the larval-pupal transition of workers. The results showed that ame-miR-5119 with a length of 19 nt targets six genes related to the hormone pathway. We focused on Eth and found that ame-miR-5119 and Eth exhibited reverse expression patterns during the transition from larval to pupal stages in workers. Dual luciferase assay confirmed the negative regulatory between ame-miR-5119 and Eth. Overexpression of ame-miR-5119 decreased the mRNA level of Eth, and the Eth receptor (Ethr) expression was not significantly affected, but the expression levels of juvenile hormone (JH) pathway related genes juvenile hormone acid methyltransferase (Jhamt) and Krüppel homolog 1 (Kr-h1) were significantly reduced. In contrast, knockdown of ame-miR-5119 increased the mRNA level of Eth, and the expression of Ethr, Jhamt and Kr-h1 was significantly upregulated. ame-miR-5119 did not affect larval body weight. The number of larvae overexpressing ame-miR-5119 survived in the prepupal stage was lower than that in the control group, and the number of pupations reduced at 11-day-old. The number of larvae that knocked down ame-miR-5119 survived in the prepupal stage was significantly higher than that in the control group, and the number of pupations increased at 11-day-old. These results indicated that ame-miR-5119 negatively regulates the expression of Eth, indirectly inhibits the expression of Ethr, Jhamt, and Kr-h1, and affects the JH biosynthesis, thereby preventing the metamorphic transition from larva to pupa in worker bees. These findings provide evidence that the miRNA regulation of hormone levels in honey bees.

Insufficient reactive oxygen species originating from hypoxia and high glutathione (GSH) in the tumor microenvironment (TME) is an important reason for radiotherapy (RT) resistance. Currently, radiosensitizers that remodel TME are widely investigated to enhance RT. However, developing an effective nano‐radiosensitization system that removes radiotherapy‐resistant factors from TME to boost RT effect while visualizing tumor imaging to aid therapy remains a challenge. Herein, MnO2 nanosheets are grown on the surface of ultrasmall Eu‐doped NaGdF4 (NaGdF4:Eu3+) nanoparticles and modified by biocompatible DSPE‐PEG2000 to prepare NaGdF4:Eu3+@MnO2@PEG nanoparticles (denoted as GMP NPs) as a radiosensitizer, which not only can reverse the TME by degrading H2O2 to produce oxygen and consuming high GSH but also achieve computed tomography (CT)and magnetic resonance (MR) imaging. When GMP NPs synergize with X‐ray, a better antitumor effect is achieved in both HeLa cells and tumor‐bearing mice, compared with X‐ray alone. In addition, both paramagnetic Mn2+ ionsproduced by decomposing MnO2 in TME and NaGdF4:Eu3+ nanoparticles enhance T1‐weighted MR imaging. NaGdF4:Eu3+ nanoparticles containing high atomic number of Gd/Eu effectively attenuate X‐ray to enhance CT imaging. The work provides new insights for developing an efficient RT sensitization platform integrating antitumor therapeutic effect as well as CT/MR dual‐modal imaging.

Abstract Background For some ICU patients, an artificial airway must be established with an endotracheal tube, but Candida albicans can easily adhere to the tube surface and form a biofilm, leading to potentially life threatening fungal infections. Therefore, it is urgent to prevent and reduce C. albicans infections introduced by the endotracheal tube. However, there are few antifungal drugs effective against C. albicans, and each of these drugs may have adverse effects on human cells. Saccharomyces boulardii is regarded as an alternative strategy to inhibit the adhesion of C. albicans, but it is affected by environmental stress. We hypothesized that it is feasible to strengthen the antagonistic ability of S. boulardii via encapsulating and genetically modification. Methods In this study, a bioactive material carrying the overexpressed MCP1 gene of Saccharomyces boulardii was constructed based on one-step photo-crosslinking. This material achieved spatial growth control of S. boulardii by encapsulating each S. boulardii cell within a hydrogel pore. The bioactive material was coated on an endotracheal tube and tested for its ability to inhibit the adhesion of C. albicans. Additionally, the material’s antagonistic activity towards C. albicans was evaluated by detecting intracellular Adenosine-triphosphate content, reactive oxygen species level and the activity of antioxidative enzymes. Tissue invasion experiment was executed to further evaluate the anti-adhesion ability of S. boulardii bio-coating. Results Encapsulating the overexpression of MCP1 by S. boulardii in hydrogel pores enhanced the viability of probiotics in the presence of high salt and oxidation stress. When used as the coating of an endotracheal tube, the S. boulardii bioactive material efficiently inhibited the adhesion of C. albicans by impairing the activities of superoxide dismutase and catalase and disturbing mitochondrial functions. In vivo, the S. boulardii bioactive material coating displayed good biocompatibility and reduced the host tissue invasion and virulence of C. albicans. Conclusions The integration of genetic modification and immobilization model breaks the bottleneck of previous application of microorganisms, and provides a new way to prevent fungal infections introduced by endotracheal tubes. Graphical Abstract

Abstract Background Brain entropy reveals complexity and irregularity of brain, and it has been proven to reflect brain complexity alteration in disease states. Previous studies found that bipolar disorder adolescents showed cognitive impairment. The relationship between complexity of brain neural activity and cognition of bipolar II disorder (BD-II) adolescents remains unclear. Methods Nineteen BD-II patients (14.63 ±1.57 years old) and seventeen age-gender matched healthy controls (HCs) (14.18 ± 1.51 years old) were enlisted. Entropy values of all voxels of the brain in resting-state functional MRI data were calculated and differences of them between BD-II and HC groups were evaluated. After that, correlation analyses were performed between entropy values of brain regions showing significant entropy differences and clinical indices in BD-II adolescents. Results Significant differences were found in scores of immediate visual reproduction subtest (VR-I, p = 0.003) and Stroop color-word test (SCWT-1, p = 0.015; SCWT-2, p = 0.004; SCWT-3, p = 0.003) between the two groups. Compared with HCs, BD-II adolescents showed significant increased brain entropy in right parahippocampal gyrus and right inferior occipital gyrus. Besides, significant negative correlations between brain entropy values of right parahippocampal gyrus, right inferior occipital gyrus and immediate visual reproduction subtest scores were observed in BD-II adolescents. Conclusions The findings of the present study suggested that the disrupted function of corticolimbic system is related with cognitive abnormality of BD-II adolescents. And from the perspective temporal dynamics of brain system, the current study, brain entropy may provide available evidences for understanding the underlying neural mechanism in BD-II adolescents.

Abstract A growing number of studies have demonstrated that the skeleton is an endocrine organ that is involved in glucose metabolism and plays a significant role in human glucose homeostasis. However, there is still a limited understanding of the in vivo glucose uptake and distribution across the human skeleton. To address this issue, we aimed to elucidate the detailed profile of glucose uptake across the skeleton using a total-body positron emission tomography (PET) scanner. A total of 41 healthy participants were recruited. Two of them received a 1-hour dynamic total-body 18F-fluorodeoxyglucose (18F-FDG) PET scan, and all of them received a 10-minute static total-body 18F-FDG PET scan. The net influx rate (Ki) and standardized uptake value normalized by lean body mass (SUL) were calculated as indicators of glucose uptake from the dynamic and static PET data, respectively. The results showed that the vertebrae, hip bone and skull had relatively high Ki and SUL values compared with metabolic organs such as the liver. Both the Ki and SUL were higher in the epiphyseal, metaphyseal and cortical regions of long bones. Moreover, trends associated with age and overweight with glucose uptake (SULmax and SULmean) in bones were uncovered. Overall, these results indicate that the skeleton is a site with significant glucose uptake, and skeletal glucose uptake can be affected by age and dysregulated metabolism.

Abstract Background Brain metastases are frequent complications for lung cancer patients. However, changes in the brain of lung cancer patients have received little attention. We aimed to explore whether alterations in brain glucose uptake and brain texture occur in non‐small cell lung cancer (NSCLC) patients and to investigate associations between brain alterations and NSCLC via the uEXPLORER positron emission tomography/computed tomography (PET/CT) system. Methods In total, 105 participants were enrolled, including 55 healthy controls and 50 NSCLC patients. Images were acquired using the PET/CT system. Standardized uptake values normalized by lean body mass were calculated as indicators of glucose uptake. Correlation analysis was conducted between aberrant brain glucose uptake, glucose uptake of cancer lesions, and concentrations of serum lung cancer markers. Radiomics was used to investigate whether features extracted from regions with altered brain glucose uptake could serve as biomarkers of lung cancer progression. Results Compared with healthy controls, NSCLC patients showed decreased standardized uptake values normalized by lean body mass in the left insula, medial frontal gyrus, and anterior cingulate. Correlation analysis demonstrated that glucose uptake of the anterior cingulate was negatively correlated with serum lung cancer marker concentrations. Radiomic features on PET/CT images of the above brain regions could classify NSCLC patients and healthy controls with an accuracy of 79%. Conclusions NSCLC patients exhibited altered brain glucose uptake and changes in brain textures. These alterations may reflect alterations in behavioral domains in NSCLC and may be related to altered lung‐brain interactions and potential brain metastasis of NSCLC.

Abstract Background The activation of the cyclic guanosine monophosphate-adenosine monophosphate synthase-stimulator of interferon genes (cGAS-STING) signaling pathway has attracted great attention for its ability to up-regulate innate immune response and thus enhance cancer immunotherapy. However, many STING agonists limit the further advancement of immunotherapy due to weak tumor responsiveness or low activation efficiency. The responsive and effective activation of cGAS-STING signaling in tumors is a highly challenging process. Methods In this study, a manganese-based nanoplatform (MPCZ NPs) was constructed that could responsively and efficiently generate more manganese ions (Mn2+) and reactive oxygen species (ROS) to activate cGAS-STING signaling pathway. Briefly, manganese dioxide (MnO2) was loaded with zinc protoporphyrin IX (ZPP) molecule and coated by polydopamine (PDA) embedded with NH4HCO3 to obtain MPCZ NPs. Additionally, MPCZ NPs were evaluated in vitro and in vivo for their antitumor effects by methyl thiazolyl tetrazolium (MTT) assay and TUNEL assays, respectively. Results In this system, tumor responsiveness was achieved by exogenous (laser irradiation) and endogenous (high levels GSH) stimulation, which triggered the collapse or degradation of PDA and MnO2. Moreover, the release of Mn2+ augmented the cGAS-STING signaling pathway and enhanced the conversion of hydrogen peroxide (H2O2) to hydroxyl radical (·OH) under NIR laser irradiation. Furthermore, the release of ZPP and the elimination of GSH by MPCZ NPs inhibited HO-1 activity and prevented ROS consumption, respectively. Conclusions This adopted open source and reduce expenditure strategy to effectively generate more ROS and Mn2+ to responsively activate cGAS-STING signaling pathway, providing a new strategy for improving immunotherapy.

BackgroundTo predict treatment response and 2 years overall survival (OS) of radio-chemotherapy in patients with esophageal cancer (EC) by radiomics based on the computed tomography (CT) images.MethodsThis study retrospectively collected 171 nonsurgical EC patients treated with radio-chemotherapy from Jan 2010 to Jan 2019. 80 patients were randomly divided into training (n=64) and validation (n=16) cohorts to predict the radiochemotherapy response. The models predicting treatment response were established by Lasso and logistic regression. A total of 156 patients were allocated into the training cohort (n=110), validation cohort (n=23) and test set (n=23) to predict 2-year OS. The Lasso Cox model and Cox proportional hazards model established the models predicting 2-year OS.ResultsTo predict the radiochemotherapy response, WFK as a radiomics feature, and clinical stages and clinical M stages (cM) as clinical features were selected to construct the clinical-radiomics model, achieving 0.78 and 0.75 AUC (area under the curve) in the training and validation sets, respectively. Furthermore, radiomics features called WFI and WGI combined with clinical features (smoking index, pathological types, cM) were the optimal predictors to predict 2-year OS. The AUC values of the clinical-radiomics model were 0.71 and 0.70 in the training set and validation set, respectively.ConclusionsThis study demonstrated that planning CT-based radiomics showed the predictability of the radiochemotherapy response and 2-year OS in nonsurgical esophageal carcinoma. The predictive results prior to treatment have the potential to assist physicians in choosing the optimal therapeutic strategy to prolong overall survival.

Recently, germanium (Ge) was also considered as the two-dimensional (2D) material saturable absorber (SA) because of its excellent nonlinear saturable absorption properties. However, the research of Ge SA Er-doped fiber laser is still rare. In this work, bound state solitons were demonstrated in Ge SA Er-doped fiber laser. To be best of our knowledge, no previous work has ever achieved that. Three kinds of bound state solitons with 9.77 MHz fundamental frequency were investigated, indicating that Ge has excellent nonlinear optical characteristics to promote the development of bound state soliton.

Aqueous electrochemical energy storage devices have attracted tremendous attention because of its high safety, low cost, and environmental friendliness. However, their low‐temperature operation is plagued by the freeze of electrolytes. Herein, a 3 mol kg−1 Zn(ClO4)2 electrolyte without adding any organic solvents or antifreezing additives is proposed, which yields a high ionic conductivity of 9.4 mS cm−1 even at ultralow temperatures of −60 °C. The strong electrostatic interaction between Zn2+ ion and water molecules and the structure breaking effect of ClO4− ions to destroy the hydrogen bond network between water molecules in Zn(ClO4)2 electrolyte is revealed by spectroscopic characterization and theoretical simulation. This low‐temperature electrolyte renders the zinc‐ion hybrid capacitor to exhibit a high energy density of 40.91 Wh kg−1 at −60 °C and a long‐cycle life (over 200 days) at −30 °C. This study provides a new path to develop low‐concentration antifreezing electrolytes for aqueous electrochemical energy storage devices.

Abstract In recent years, neural architecture search (NAS) has achieved unprecedented development because of its ability to automatically achieve high-performance neural networks in various tasks. Among these, the evolutionary neural architecture search (ENAS) has impressed the researchers due to the excellent heuristic exploration capability. However, the evolutionary algorithm-based NAS are prone to the loss of population diversity in the search process, causing that the structure of the surviving individuals is exceedingly similar, which will lead to premature convergence and fail to explore the search space comprehensively and effectively. To address this issue, we propose a novel indicator, named architecture entropy, which is used to measure the architecture diversity of population. Based on this indicator, an effective sampling strategy is proposed to select the candidate individuals with the potential to maintain the population diversity for environmental selection. In addition, an unified encoding scheme of topological structure and computing operation is designed to efficiently express the search space, and the corresponding population update strategies are suggested to promote the convergence. The experimental results on several image classification benchmark datasets CIFAR-10 and CIFAR-100 demonstrate the superiority of our proposed method over the state-of-the-art comparison ones. To further validate the effectiveness of our method in real applications, our proposed NAS method is applied in the identification of lumbar spine X-ray images for osteoporosis diagnosis, and can achieve a better performance than the commonly used methods. Our source codes are available at https://github.com/LabyrinthineLeo/AEMONAS.

Abstract Background Clinical and etiological varieties remain major obstacles to decompose heterogeneity in autism spectrum disorders (ASD). Recently, neuroimaging raised new hope to identify neurosubtypes of ASD for further understanding the biological mechanisms behind the disorder. Methods In this study, brain structural MRI data and clinical measures of 221 male subjects with ASD and 257 healthy controls were selected from 7 independent sites from the Autism Brain Image Data Exchange database (ABIDE). Heterogeneity through discriminative analysis (HYDRA), a recently-proposed semi-supervised clustering method was utilized to divide individuals with ASD into several neurosubtypes by regional volumetric measures of gray matter, white matter, and cerebrospinal fluid. Voxel-wise volume, clinical measures, dynamic resting-state functional magnetic resonance imaging (R-fMRI) measures among different neurosubtypes of ASD were explored. In addition, support vector machine (SVM) model was applied to test whether the neurosubtyping of ASD could improve diagnostic accuracy of ASD. Results Two neurosubtypes of ASD with different voxel-wise volumetric patterns were revealed. The full-scale intelligence quotient (IQ), verbal IQ, Autism Diagnostic Observation Schedule (ADOS) total scores and ADOS severity scores were significantly different between the two neurosubtypes, the total intracranial volume was correlated with performance IQ in Subtype 1 and was correlated with ADOS communication score and ADOS social score in Subtype 2. Compared with Subtype 2, Subtype 1 showed lower dynamic R-fMRI measures, lower dynamic functional architecture stability, higher mean and lower standard deviation (SD) of concordance among dynamic R-fMRI measures in cerebellum. In addition, classification accuracies between ASD neurosubtypes and healthy controls were significantly improved compared with classification accuracy between entire ASD group and healthy controls. Limitations The present study excluded female subjects and left-handed subjects, which limited the ability to investigate the associations between these factors and the heterogeneity of ASD. Conclusions The two distinct neuroanatomical subtypes of ASD validated by other data modalities not only adds reliability of the result, but also bridges from brain phenomenology to clinical behavior. The current neurosubtypes of ASD could facilitate understanding the neuropathology of this disorder and could be potentially used to improve clinical decision-making process and optimize treatment.

Abstract Photoacoustic computed tomography (PACT) is a hybrid imaging modality that combines optical excitation and acoustic detection techniques. It obtains high‐resolution deep‐tissue images based on the deep penetration of light, the anisotropy of light absorption in objects, and the photoacoustic effect. Hence, PACT shows great potential in biomedical sample imaging. Recently, due to its advantages of high sensitivity to optical absorption and wide scalability of spatial resolution with the desired imaging depth, PACT has received increasing attention in preclinical and clinical practice. To date, there has been a proliferation of PACT systems designed for specific biomedical imaging applications, from small animals to human organs, from ex vivo to in vivo real‐time imaging, and from simple structural imaging to functional and molecular imaging with external contrast agents. Therefore, it is of great importance to summarize the previous applications of PACT systems in biomedical imaging and clinical practice. In this review, we searched for studies related to PACT imaging of biomedical tissues and samples over the past two decades; divided the studies into two categories, PACT imaging of preclinical animals and PACT imaging of human organs and body parts; and discussed the significance of the studies. Finally, we pointed out the future directions of PACT in biomedical applications. With the development of exogenous contrast agents and advances of imaging technique, in the future, PACT will enable biomedical imaging from organs to whole bodies, from superficial vasculature to internal organs, from anatomy to functions, and will play an increasingly important role in biomedical research and clinical practice.

Oily sewage poses a serious environmental risk normally; thus, herein, the modified guar gum (GG-SH) was prepared through rapid condensation reaction between polysaccharide and stearic hydrazide. GG-SH exhibited high removal efficiency of crude oil, the maximum adsorption capacity was calculated to be 2157.3 mg•g-1. The kinetics and isotherm statistical theories showed that the sorption of crude oil onto GG-SH was governed by pseudo-second-order, and Langmuir models, respectively. The removal rate was still high after six cycles of regeneration, indicating an outstanding technique to prepare polysaccharide-based material for the oily sewage treatment with high efficiency and recyclability.

An increasing number of studies have shown that the functional interactions between the thalamus and cerebral cortices play an important role in cognitive function and are influenced by age. Previous studies have revealed age-related changes in the thalamo-cortical system within individuals, while neglecting differences between individuals. Here, we characterized inter-subject functional correlation (ISFC) between the thalamus and several cortical brain networks in 500 healthy participants aged 18–87 years old from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) cohort using movie-watching state fMRI data. General linear models (GLM) were performed to assess age-related changes in ISFC of thalamo-cortical networks and the relationship between ISFC and fluid intelligence. We found significant age-related decreases in ISFC between the posterior thalamus (e.g., ventral posterior nucleus and pulvinar) and the attentional network, sensorimotor network, and visual network (FDR correction with p < 0.05). Meanwhile, the ISFC between the thalamus (mainly the mediodorsal nucleus and ventral thalamic nuclei) and higher-order cortical networks, including the default mode network, salience network and control network, showed complex changes with age. Furthermore, the altered ISFC of thalamo-cortical networks was positively correlated with decreased fluid intelligence (FDR correction with p < 0.05). Overall, our results provide further evidence that alterations in the functional integrity of the thalamo-cortical system might play an important role in cognitive decline during aging.

Aggregation-induced emission (AIE) molecules have garnered considerable interest since its first appearance in 2001. Recent studies on AIE materials in biological and medical areas have demonstrated that they show their promise as biomaterials for bioimaging and other biomedical applications. Benefiting from significant advantages of their high sensitivity, excellent photostability, and good biocompatibility, AIE-based materials provide dramatically improved analytical capacities for in vivo detection and demonstration of vital biological processes. Herein, we introduce the development history of AIE molecules and recent progress in areas of biotesting and bioimaging. Additionally, this review also offers an outlook for the potential applications of versatile AIE materials for tracing and treating pathological tissues, including overcoming challenges and feasible solutions.

The diagnosis based on clinical assessment of pediatric bipolar disorder (PBD) may sometimes lead to misdiagnosis in clinical practice. For the past several years, machine learning (ML) methods were introduced for the classification of bipolar disorder (BD), which were helpful in the diagnosis of BD. In this study, brain cortical thickness and subcortical volume of 33 PBD-I patients and 19 age-sex matched healthy controls (HCs) were extracted from the magnetic resonance imaging (MRI) data and set as features for classification. The dimensionality reduced feature subset, which was filtered by Lasso or f_classif, was sent to the six classifiers (logistic regression (LR), support vector machine (SVM), random forest classifier, naïve Bayes, k-nearest neighbor, and AdaBoost algorithm), and the classifiers were trained and tested. Among all the classifiers, the top two classifiers with the highest accuracy were LR (84.19%) and SVM (82.80%). Feature selection was performed in the six algorithms to obtain the most important variables including the right middle temporal gyrus and bilateral pallidum, which is consistent with structural and functional anomalous changes in these brain regions in PBD patients. These findings take the computer-aided diagnosis of BD a step forward.

BackgroundThere are few data on the clinical significance of coronary computed tomography angiography (CCTA) in asymptomatic type 2 diabetes mellitus (T2DM) patients. We performed a retrospective study to evaluate coronary heart disease (CHD) screening in asymptomatic patients with T2DM using CCTA and CHD risk stratification prediction.Materials and methodsData from 141 T2DM patients (58 ± 8 years, 57% males) without known symptoms suggestive of CHD who underwent CCTA were retrospectively analyzed. The patients were classified into three subgroups based on United Kingdom prospective diabetes study (UKPDS) CHD risk stratification prediction. Seventy-four patients without diabetes mellitus and CHD who underwent CCTA successively were chosen as the control group. The segment involvement score (SIS), segment stenosis score (SSS), stenosis coefficient (SC), severe proximal plaque (SPP) positive ratio and CCTA-adapted Leaman score (CT-LeSc) based on CCTA data were evaluated and compared among the groups.ResultsCompared with the patients in the control group, patients in the moderate-high risk DM groups had higher scores on the SIS, SSS, SC, CT-LeSc, and a higher SPP positive ratio (all p-values < 0.001), and no difference was observed between the low-risk group and the control group (p = 0.136, p = 0.088, p = 0.0.067, p = 0.225, p = 1.000, respectively). Compared with patients in the control group, the patients in the moderate-high risk DM groups had increased odds of SIS > 3 [odds ratio (OR) = 6.557, p < 0.001; OR = 4.455, p < 0.001, respectively], SSS > 5 (OR = 5.727, p < 0.001; OR = 5.144, p < 0.001, respectively), CT-LeSc > 8.7 (OR = 3.780, p = 0.001; OR = 2.804, p = 0.007, respectively), and obstructive stenosis (OR = 7.233, p < 0.001; OR = 5.787, p < 0.001, respectively).ConclusionThe moderate-high CHD risk patients had increased odds of obstructive coronary artery stenosis, and the distribution of coronary artery stenosis was more extensive and more severe in that group compared to the patients without diabetes mellitus and CHD. CHD can be effectively screened in moderate-high risk asymptomatic T2DM patients using CCTA.

This study proposes an improved algorithm based on the You Only Look Once v7 (YOLOv7) to address the low accuracy of apple fruit target recognition caused by high fruit density, occlusion, and overlapping issues. Firstly, we proposed a preprocessing algorithm for the split image with overlapping to improve the robotic intelligent picking recognition accuracy. Then, we divided the training, validation, and test sets. Secondly, the MobileOne module was introduced into the backbone network of YOLOv7 to achieve parametric fusion and reduce network computation. Afterward, we improved the SPPCSPS module and changed the serial channel to the parallel channel to enhance the speed of image feature fusion. We added an auxiliary detection head to the head structure. Finally, we conducted fruit target recognition based on model validation and tests. The results showed that the accuracy of the improved YOLOv7 algorithm increased by 6.9%. The recall rate increased by 10%, the mAP1 algorithm increased by 5%, and the mAP2 algorithm increased by 3.8%. The accuracy of the improved YOLOv7 algorithm was 3.5%, 14%, 9.1%, and 6.5% higher than that of other control YOLO algorithms, verifying that the improved YOLOv7 algorithm could significantly improve the fruit target recognition in high-density fruits.

As a microenvironment where cells reside, the extracellular matrix (ECM) has a complex network structure and appropriate mechanical properties to provide structural and biochemical support for the surrounding cells. In tissue engineering, the ECM and its derivatives can mitigate foreign body responses by presenting ECM molecules at the interface between materials and tissues. With the widespread application of three-dimensional (3D) bioprinting, the use of the ECM and its derivative bioinks for 3D bioprinting to replicate biomimetic and complex tissue structures has become an innovative and successful strategy in medical fields. In this review, we summarize the significance and recent progress of ECM-based biomaterials in 3D bioprinting. Then, we discuss the most relevant applications of ECM-based biomaterials in 3D bioprinting, such as tissue regeneration and cancer research. Furthermore, we present the status of ECM-based biomaterials in current research and discuss future development prospects.

Abstract Background ADHD is one of the most common psychiatric disorders in children and adolescents. Altered functional connectivity has been associated with ADHD symptoms. This study aimed to investigate abnormal changes in the functional connectivity of resting-state brain networks (RSNs) among adolescent patients with different subtypes of ADHD. Methods The data were obtained from the ADHD-200 Global Competition, including fMRI data from 88 ADHD patients (56 patients of ADHD-Combined, ADHD-C and 32 patients of ADHD-Inattentive, ADHD-I) and 67 typically developing controls (TD-C). Group ICA was utilized to research aberrant brain functional connectivity within the different subtypes of ADHD. Results In comparison with the TD-C group, the ADHD-C group showed clusters of decreased functional connectivity in the left inferior occipital gyrus (p = 0.0041) and right superior occipital gyrus (p = 0.0011) of the dorsal attention network (DAN), supplementary motor area (p = 0.0036) of the executive control network (ECN), left supramarginal gyrus (p = 0.0081) of the salience network (SN), middle temporal gyrus (p = 0.0041), and superior medial frontal gyrus (p = 0.0055) of the default mode network (DMN), while the ADHD-I group showed decreased functional connectivity in the right superior parietal gyrus (p = 0.0017) of the DAN and left middle temporal gyrus (p = 0.0105) of the DMN. In comparison with the ADHD-I group, the ADHD-C group showed decreased functional connectivity in the superior temporal gyrus (p = 0.0062) of the AN, inferior temporal gyrus (p = 0.0016) of the DAN, and the dorsolateral superior frontal gyrus (p = 0.0082) of the DMN. All the clusters surviving at p

Abstract Background The anomalous origin of the right coronary artery (RCA) from the left coronary artery sinus (AORL) is one of the abnormal origins of the coronary arteries. Most of these issues rarely have any effects on human health, but some individuals may exhibit symptoms, such as myocardial ischemia or even sudden death. Recently, researchers have investigated the AORL through clinical cases, but studies based on computational fluid dynamics (CFD) have rarely been reported. In this study, the hemodynamic changes between the normal origin of the RCA and the AORL are compared based on numerical simulation results. Methods Realistic three-dimensional (3D) models of the 16 normal right coronary arteries and 26 abnormal origins of the RCAs were constructed, respectively. The blood flow was numerically simulated using the ANSYS software. This study used a one-way fluid–solid coupling finite element model, wherein the blood is assumed to be an incompressible Newtonian fluid, and the vessel is assumed to be made of an isotropic linear elastic material. Results The cross-sectional area differences between the inlet of the normal group and that of the abnormal group were significant (P

The evolution of grain boundary character distribution in a cold-deformed nickel-based superalloy during the electropulsing treatment (EPT) was studied. The results revealed that both coherent Σ3 boundaries (Σ3c) and incoherent Σ3 boundaries (Σ3ic) were formed in the recrystallized structures mainly by growth accidents during EPT, while the fraction of Σ3ic boundaries became much lower at the higher EPT temperatures. Meanwhile, the fraction of Σ3 boundaries increased with the increasing EPT temperatures till 850 °C, and decreased again at 900 °C. In addition, the high mobility of grain boundary during EPT could promote the formation of stacking errors at some locations of high angle grain boundaries (HAGBs), and thus promoting the nucleation of annealing twins. With the increasing EPT time, the fraction of Σ3 boundaries increased slightly, and the unstable Σ3ic boundaries were transformed into stable Σ3c boundaries, in which intersecting migrating SRX fronts were easier to be extended. On the other hand, a lot of low-Σ CSL grain boundaries were formed in the pre-deformed alloy with the strain of 0.1 during EPT, which was mainly attributed to the development of large grain-clusters. As the strain was large enough, the energy supplied by electropulsing could enable the cold-rolled alloy to effectively utilize the stored energy on the formation of Σ3 boundaries. Besides that, the evolution of Σ9 and Σ27 boundaries was analyzed in detail as well as the corrosion resistance of the studied alloy after different treatments.

In this paper, a multiplexing technique of coherent polarization states based on three-dimensional rotation group is proposed. The technique applies two Stokes parameters in one polarized light as signal and local oscillator (LO), and combines them in the single spatial mode. Three-dimensional rotation group SO(3) is used to describe the transformation of Stokes parameters. SO(3) is decomposed into three subgroups, with each subgroup represents a rotation along different axes. A multiplexer is designed with three electro-optical crystals to realize the function of three-dimensional rotation group. The multiplexer achieves an ergodicity of polarization states. Signal and LO propagates in the same spatial mode, multiplexing of polarization states is realized. Finally, the multiplexer is tested in a free space quantum communication system and its feasibility in quantum communication is confirmed.

Localizing the site of tumor origin for patients with lymphoid tumor is fairly difficult before the definitive detection of the primary tumor, which causes redundant imaging examinations and medical costs. To circumvent this obstacle, the emergence of the world’s first total-body positron emission tomography/computed tomography (PET/CT) provides a transformative platform for simultaneously static and dynamic human molecular imaging. Here, we reported a case of lymph node metastasis from an unknown primary tumor, and the primary tumor was detected with the aid of the total-body PET/CT scanner. This patient with right neck mass was subjected to static and dynamic PET scan, as the static PET imaging found irregular thickening of the upper rectal wall and the dynamic PET imaging recognized the associations between the lymph metastasis and the rectal tumor lesions. The diagnosis by the total-body PET/CT was confirmed by pathological examination.

BackgroundBy calculating cortical thickness (CT) and cortical structural covariance (SC), we aimed to investigate cortical morphology and cortical inter-regional correlation alterations in adolescent bipolar disorder type I (BD-I) and type II (BD-II) patients.MethodsT1-weighted images from 36 BD-I and 22 BD-II patients and 19 healthy controls (HCs) were processed to estimate CT. CT values of the whole brain were compared among three groups. Cortical regions showing CT differences in groups were regarded as seeds for analyzing cortical SC differences between groups. The relationship between CT and clinical indices was further assessed.ResultsBoth BD groups showed cortical thinning in several frontal and temporal areas vs. HCs, and CT showed no significant difference between two BD subtypes. Compared to HCs, both BD groups exhibited reduced SC connections between left superior frontal gyrus (SFG) and right postcentral gyrus (PCG), left superior temporal gyrus (STG) and right pars opercularis, and left STG and right PCG. Compared with HCs, decreased SC connections between left STG and right inferior parietal gyrus (IPG) and right pars opercularis and right STG were only observed in the BD-I group, and left PCG and left SFG only in the BD-II group. CT of right middle temporal gyrus was negatively correlated with number of episodes in BD-II patients.ConclusionsAdolescent BD-I and BD-II showed commonly decreased CT while presenting commonly and distinctly declined SC connections. This study provides a better understanding of cortical morphology and cortical inter-regional correlation alterations in BD and crucial insights into neuroanatomical mechanisms and pathophysiology of different BD subtypes.

Cerebral small vessel disease (CSVD) is associated with altered cerebral perfusion. However, global and regional cerebral blood flow (CBF) are highly heterogeneous across CSVD patients. The aim of this study was to identify subtypes of CSVD with different CBF patterns using an advanced machine learning approach. 121 CSVD patients and 53 healthy controls received arterial spin label MRI, T1 structural MRI and clinical measurements. Regional CBF were used to identify distinct perfusion subtypes of CSVD via a semi-supervised machine learning algorithm. Statistical analyses were used to explore alterations in CBF, clinical measures, gray and white matter volume between healthy controls and different subtypes of CSVD. Correlation analysis was used to assess the association between clinical measures and altered CBF in each CSVD subtype. Three subtypes of CSVD with distinct CBF patterns were found. Subtype 1 showed decreased CBF in the temporal lobe and increased CBF in the parietal and occipital lobe. Subtype 2 exhibited decreased CBF in the right hemisphere of the brain, and increased CBF in the left cerebrum. Subtype 3 demonstrated decreased CBF in the posterior part of the brain, and increased CBF in anterior part of the brain. The three subtypes also differed significantly in gender (p = 0.005), the proportion of subjects with lacune (p = 0.002), with periventricular white matter hyperintensity (p = 0.043), and CSVD burden score (p = 0.048). In subtype 3, it was found that widespread decreased CBF was correlated with total CSVD burden score (r = -0.324, p = 0.029). Compared with healthy controls, the three CSVD subtypes also showed distinct volumetric patterns of white matter. The current results associate different subtypes with different clinical and imaging phenotypes, which can improve the understanding of brain perfusion alterations of CSVD and can facilitate precision diagnosis of CSVD.

The female Bombyx mori accumulates a large amount of egg proteins, mainly Vg and 30K, during egg formation to provide nutrition for embryo development. The synthesis and transport of Vg have been extensively studied, particularly the regulation of Vg transcription induced by 20E; however, the mechanism of 30K protein synthesis is poorly studied. As a model organism of the order Lepidoptera, B. mori has high reproduction potential. In the present study, we found that the FHL2 homologous gene (BmFhl2) in B. mori is involved in inhibiting female egg formation by influencing the synthesis of 30K protein. Interference of BmFhl2 expression in silkworm females increased 30K protein synthesis, accelerated ovarian development, and significantly increased the number of eggs produced and laid; however, the 20E pathway was inhibited. The transcription levels of Vg and 30Kc19 were significantly downregulated following BmFhl2 overexpression in the silkworm ovarian cell line BmN. The Co-IP assay showed that the potential binding protein of BmFHL2 included three types of 30K proteins (30Kc12, 30Kc19, and 30Kc21). These results indicate that BmFHL2 participates in egg formation by affecting 30K protein in female B. mori.

For studying the pathogenesis of complex diseases, it is important to identify the disease modules in the system level. Since the protein-protein interaction (PPI) networks contain a number of incomplete and incorrect interactome, most existing methods often lead to many disease proteins isolating from disease modules. In this paper, we propose an effective disease module identification method IDMCSS, where the used human PPI networks are obtained by adding some potential missing interactions from existing PPI networks, as well as removing some potential incorrect interactions. In IDMCSS, a network adjustment strategy is developed to add or remove links around disease proteins based on both topological and semantic information. Next, neighboring proteins of disease proteins are prioritized according to a suggested similarity between each of them and disease proteins, and the protein with the largest similarity with disease proteins is added into a candidate disease protein set one by one. The stopping criterion is set to the boundary of the disease proteins. Finally, the connected subnetwork having the largest number of disease proteins is selected as a disease module. Experimental results on asthma demonstrate the effectiveness of the method in comparison to existing algorithms for disease module identification. It is also shown that the proposed IDMCSS can obtain the disease modules having crucial biological processes of asthma and 12 targets for drug intervention can be predicted.

Earthquake prediction is an important and complex task in the real world. Although many data mining-based methods have been proposed to solve this problem, the prediction accuracy is still far from satisfactory due to the deficiency of feature extraction techniques. To this end, in this paper, we propose a precursory pattern-based feature extraction method to enhance the performance of earthquake prediction. Especially, the raw seismic data is firstly divided into fixed day time periods, and the magnitude of the largest earthquake in each fixed time period is labeled as the main shock. The precursory pattern is a part of the seismic sequence before the main shock, on which the existing mathematical statistic features can be directly generated as seismic indicators. Based on these precursory pattern-based features, a simple yet effective classification and regression tree algorithm is adopted to predict the label of the main shock in a pre-defined future time period. The experimental results on two historical earthquake records of the Changding-Garzê and Wudu-Mabian seismic zones of China demonstrate the effectiveness of the proposed precursory pattern-based features with the selected CART algorithm for earthquake prediction.

Optimizing pseudo-linear performance measures has gained increasing interest in recent years. Compared with the existing works focusing on L2-norm, it is more challenging to design the model with L1-norm, especially, when data are of large scale. To address the issue, in this paper, we propose a sparse stochastic method to optimize the pseudo-linear metrics. The algorithm begins by formulating the problem as a cost-sensitive classification with L1 regularization, then composite objective mirror descent (COMID) is adopted for the inner optimization, which can obtain a sparse solution with promising performance. However, the original COMID method only has O(log(T)/T) convergence rate with the strong convex objective. To this end, a simple yet efficient polynomial-decay average strategy is suggested. We prove that with this strategy, the proposed algorithm can not only achieve the optimal convergence rate of O(1/T) but also obtain the classifier with higher sparsity. The empirical studies on several public benchmark data sets demonstrate the superior performance of the proposed algorithm in terms of both efficiency and sparsity.

As a vector of pine wood nematode disease, Monochamus alternatus is wood-boring, cryptic, and extremely difficult to control—features that have made them a disastrous problem. In this study, we present a method of scanning the galleries of Monochamus alternatus using CT (computed tomography) technology to obtain their systematic structure via 3D (three-dimensional) reconstruction, so as to clarify the gallery types and their structural parameters. TLC (thin-layer chromatography) scanning on wood segments damaged by M. alternatus was performed using a 128-row spiral CT GE Revolution EVO to obtain 64-layer CT scanned images. From the scanned images, we were able to clearly identify the beetle larvae and their galleries. The galleries were clearly delineated from the peripheral xylem, except for parts that were blocked by a frass–feces mixture, which were slightly blurred. Three-dimensional reconstruction of the galleries showed that most of the gallery types were C-shaped, and a few were S-shaped or Y-shaped. There was only one larva per gallery, and the galleries were separate. The vicinity of the entrance hole and the anterior part of the pupal chamber were blocked with a frass–feces mixture. There were no significant differences among the galleries’ parameters, such as the width of the entrance holes, tunneling depth, vertical length, blockage length and volume, total length of the galleries, and boring volume. With MIMICS (Materialise’s interactive medical image control system) image processing software, the images of each layer were made into a composite image, providing an effective way to visualize the 3D distribution of galleries. Using the methodology outlined in this study, both a single gallery structure and the spatial distribution of multiple galleries of M. alternatus can be shown, and the specific parameters of galleries can also be accurately calculated, which provides new ideas and methods for carrying out ecological and scientific research and precise prevention and control techniques of M. alternatus.

PurposeA 3D printed geometric phantom was developed that can be scanned with computed tomography (CT) and magnetic resonance imaging (MRI) to measure the geometric distortion and determine the relevant dose changes.Materials and MethodsA self-designed 3D printed photosensitive resin phantom was used, which adopts grid-like structures and has 822 1 cm2 squares. The scanning plan was delivered by three MRI scanners: the Elekta Unity MR-Linac 1.5T, GE Signa HDe 1.5T, and GE Discovery-sim 750 3.0T. The geometric distortion comparison was concentrated on two 1.5T MRI systems, whereas the 3.0T MRI was used as a supplemental experiment. The most central transverse images in each dataset were selected to demonstrate the plane distortion. Some mark points were selected to analyze the distortion in the 3D direction based on the plane geometric distortion. A treatment plan was created with the off-line Monaco system.ResultsThe distortion increases gradually from the center to the outside. The distortion range is 0.79 ± 0.40 mm for the Unity, 1.31 ± 0.56 mm for the GE Signa HDe, and 2.82 ± 1.48 mm for the GE Discovery-sim 750. Additionally, the geometric distortion slightly affects the actual planning dose of the radiotherapy.ConclusionGeometric distortion increases gradually from the center to the outside. The distortion values of the Unity were smaller than those of the GE Signa HDe, and the Unity has the smallest geometric distortion. Finally, the Unity’s dose variation best matched with the standard treatment plan.

Population aging has become a serious social problem. Accordingly, many researches are focusing on changes in brains of the elderly. In this study, we used multiple parameters to analyze age-related changes in white matter fibers. A sample cohort of 58 individuals was divided into young and middle-age groups and tract-based spatial statistics (TBSS) were used to analyze the differences in fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD) between the two groups. Deterministic fiber tracking was used to investigate the correlation between fiber number and fiber length with age. The TBSS analysis revealed significant differences in FA, MD, AD, and RD in multiple white matter fibers between the two groups. In the middle-age group FA and AD were lower than in young people, whereas the MD and RD values were higher. Deterministic fiber tracking showed that the fiber length of some fibers correlated positively with age. These fibers were observed in the splenium of corpus callosum (SCC), the posterior limb of internal capsule (PLIC), the right posterior corona radiata (PCR_R), the anterior corona radiata (ACR), the left posterior thalamic radiation (include optic radiation; PTR_L), and the left superior longitudinal fasciculus (SLF_L), among others. The results showed that the SCC, PLIC, PCR_R, ACR, PTR_L, and SLF_L significantly differed between young and middle-age people. Therefore, we believe that these fibers could be used as image markers of age-related white matter changes.

ObjectiveSerum hormone deficiencies during menopause transition may affect spontaneous brain activity and global cognition. The purpose of this study was to explore the differences in spontaneous brain activity between premenopausal and perimenopausal women, and to investigate the associations between spontaneous brain activity, serum hormone levels and global cognition.MethodsThirty-two premenopausal women (47.75 ± 1.55 years) and twenty-five perimenopausal women (51.60 ± 1.63 years) underwent resting-state functional MRI (fMRI) scan. Clinical information including Mini-Mental State Examination (MMSE), levels of estradiol (E2), free testosterone, progesterone, prolactin, follicle-stimulating hormone and luteinizing hormone were measured. Regional homogeneity (ReHo) was used to evaluate spontaneous brain activity alterations between perimenopausal and premenopausal women. Correlation analysis was used to investigate the associations between brain functional alterations and clinical measures in perimenopausal group.ResultsThe results demonstrated increased ReHo value in the right lingual gyrus (LG) and decreased ReHo value in the right superior frontal gyrus (SFG) in perimenopausal women compared with premenopausal women. In perimenopausal group, ReHo of the right LG showed a negative correlation with level of E2 (r = -0.586, p = 0.002), ReHo of the right SFG showed a positive correlation with level of E2 (r = 0.470, p = 0.018) and MMSE (r = 0.614, p = 0.001).ConclusionsThe results demonstrated that women approaching menopause suffered from altered functions in brain regions related to cognitive function, working memory, the results also revealed a direct association between levels of E2 and brain functions in perimenopausal women.

Purpose: To develop a method for constructing customizable, multimodal quality control (QC) imaging phantoms based on 3D printing technology.Materials and Methods: Four phantoms were designed and constructed through 3D printing technology using three unique printing materials. Physical parameters of the 3D printed materials were evaluated, including density, shore hardness, porosity, deformation temperature, computed tomography (CT) number, absorption coefficient, and printing accuracy. Imaging performance of the phantoms was studied using MRI, CT, PET/MR, and PET/CT, and compared with conventional/commercial phantoms. Imaging assessments included high contrast resolution, low contrast resolution, uniformity, deformation, SNR, slice accuracy/slice thickness, location accuracy/laser alignment, CT number, relaxation time, and registration.Results: All three printing materials have a shore hardness of 90. The physical densities of these materials are 1.15 g/cm3, 0.76 g/cm3, and 1.27 g/cm3, respectively. The porosities are 9.09, 6.81, and 18.56%, respectively. The threshold temperature of deformation for the three materials is >105°C, which is higher than that of PMMA and silica gel. Imaging scans of the constructed phantoms for single modality scanners (MRI and CT) and dual-modality scanners (PET/MRI and PET/CT) were compared with those of the commercial phantoms. The standard deviation of the HU value uniformity test was

Introduction: It remains unknown whether volumetric alterations of ventricles are similar or not in pediatric bipolar disorder (PBD) among different mood states. The present study aims to estimate ventricular volumetric alteration of PBD patients in manic and euthymic status, as well as the relationship between this alteration and cognitive changes.Methods: T1 magnetic resonance images were obtained from 20 manic PBD patients, 21 euthymic PBD patients, and 19 healthy controls (HCs). Ventricular volumes were automatically obtained via FreeSurfer 6.0 software. Ventricular volumes and cognitive indices were compared among the three groups, and the relationship between ventricular volumes and cognitive/clinical indices was analyzed.Results: In contrast to HCs, manic and euthymic PBD patients exhibited decreased cognitive scores of the Stroop color-word test and the digit span subtest. Manic PBD subjects presented enlarged volumes in the bilateral ventricles, third ventricle, and whole ventricles, and euthymic PBD participants displayed increased volumes in the third ventricle, fourth ventricle, and whole ventricles. No significant differences in cognitive performance and ventricular volumes were found between PBD groups. No significant correlation was discovered between ventricular volumes and cognitive/clinical indices in both manic and euthymic PBD patients.Conclusions: No significant differences in cognitive performance and ventricle volume were observed between euthymic and manic PBD groups, which may imply that the alterations are not specific to mood state. It may indicate structural and functional damage of corresponding brain circuits in euthymic PBD patients similar with that of manic PBD, which may provide clues to the diagnosis and treatment of euthymic PBD.

BackgroundHigh-tension glaucoma (HTG) is the most common type of primary open angle glaucoma and elevated intraocular pressure (IOP) is the major risk factor of the disease. The aim of this study was to assess alterations in resting-state visual networks in patients with HTG and investigate the effect of elevated IOP on the visual networks.MethodsT1-weighted and resting-state functional MRI images were acquired from 36 HTG patients (aged 49.22 ± 15.26 years) and 20 healthy controls (aged 49.90 ± 5.62 years). Group independent component analysis (ICA) was utilized to evaluate altered functional connectivity (FC) in resting-state visual networks between HTG patients and healthy controls. Pearson correlation analysis between mean IOP and altered FCs in the visual networks was performed.ResultsICA demonstrated decreased FCs in HTG group in the left calcarine cortex of the lateral visual network, in the bilateral lingual gyrus of the medial visual network and in the bilateral lingual gyrus of the occipital visual network compared with healthy controls. Furthermore, correlation analysis revealed negative correlation between mean IOP and altered FC within the lateral visual network.ConclusionThe results suggested reduced FCs between primary and higher visual cortices in HTG brain. The IOP elevation might be responsible for the functional alterations in the visual networks.

BackgroundThe amygdala has been proposed to be involved in the pathophysiology of pediatric and adult bipolar disorder (BD). The goal of this structural magnetic resonance imaging (sMRI) study was to investigate the morphometric characteristics of amygdala subnuclei in patients with pediatric bipolar disorder (PBD) compared to healthy controls (HCs). Simultaneously, we examined correlation between amygdala subnuclei volumes and cognitive dysfunction.Materials and MethodsWe assessed 40 adolescent outpatients, diagnosed with manic or euthymic PBD according to the DSM-5 criteria for BD and 19 HCs. Cognitive functions were evaluated using a Stroop color-word test (SCWT), trail making test (TMT), visual reproduction immediate recall subtest (VR I), and digit span subtest (DST). Amygdala and its subnuclei structures were automated segmented using FreeSurfer software and the volumes of them were compared between groups and correlation with clinical and cognitive outcomes was conducted.ResultsManic patients exhibited significantly decreased volumes in the bilateral whole amygdala and its basal nucleus, cortico-amygdaloid transition (CAT), and accessory basal nucleus (ABN) compared with HCs. Euthymic patients had decreased volume in the bilateral ABN and left CAT. In addition, we found significant positive associations between VR I scores and the right whole amygdala and its bilateral basal, right lateral, and ABN volumes in the manic group.ConclusionThese findings support previous reports of smaller amygdala volumes and cognitive dysfunctions in PBD, and further mapping abnormalities to specific amygdala subnuclei. Correlation between basolateral volume and VR I of PBD may expand our understanding of neural abnormalities that could be targeted by treatment.

BackgroundCerebral small vessel disease (CSVD) is a common age-related vascular disease of the brain associated with slowly accumulating tissue damage. At present, total CSVD burden score is a commonly used method to evaluate the severity of the disease.PurposeTo observe whether global and regional cerebral perfusion is related to total CSVD score and to explore global and regional cerebral blood flow (CBF) changes in patients with different degrees of CSVD.MethodsWe collected 130 subjects with different total burden score of CSVD (0 point: 33 subjects, 1 point: 39 subjects, 2 points: 24 subjects, 3 points: 24 subjects, 4 points: 10 subjects). Total CSVD burden score was evaluated by clinically routine sequences (T2WI, T2-FLAIR, T1WI, DWI, and SWAN sequence). Global and regional CBF were calculated and correlation analysis was used to investigate the relationship between total CSVD score and CBF of the whole brain and several brain regions.ResultsThe analysis results showed that there was a negative correlation between total CSVD burden score and global CBF (r = −0.33, p = 0.001). Total CSVD burden score also had moderately negative correlations with CBF of almost all the brain regions.ConclusionCSVD is a disease that affects the whole brain. With the increase of total CSVD burden score, the global and regional CBF decreased. The CSVD total burden score could be used to evaluate the overall condition of brain perfusion.

Purpose.Anisometropic amblyopia usually occurs during early childhood and results in monocular visual deficit. Recent neuroimaging studies have demonstrated structural and functional alterations in pediatric anisometropic amblyopia (PAA) patients. However, the relationship between structural and functional alterations remains largely unknown. The aim of this study was to investigate the relationship between structural and functional alterations in PAA patients. Materials and Methods. Eighteen PAA patients and 14 healthy children underwent a multimodal MRI scanning including T1WI and functional MRI (fMRI). Voxel-based morphometry was used to assess structural alterations between PAA patients and healthy children. Regional homogeneity (ReHo) was used to investigate changes in local spontaneous brain activity in the enrolled subjects. Correlations between structural, functional alterations, and clinical information were analyzed in the PAA group. Results. Compared with healthy children, PAA patients exhibited significantly reduced ReHo of spontaneous brain activity in the right superior temporal gyrus (STG) and right middle frontal gyrus (MFG) and increased gray matter volume in the right lobules 4 and 5 of the cerebellum. The gray matter volume of the right lobules 4 and 5 of the cerebellum was negatively correlated with the ReHo values of the right MFG. Conclusions. Our findings may suggest that PAA patients experience structural and functional abnormalities in brain regions related to oculomotor and visual-spatial information. In addition, the increased gray matter volume may compensate the decreased brain activity in the oculomotor regions, which reflects compensatory or neural plasticity in PAA patients.

Accumulating studies demonstrate emotional and cognitive dysregulation in the euthymic period of pediatric bipolar disorder (PBD). However, the relative contribution of functional integration in human brain to disturbed emotion and cognitive function in the euthymic PBD patients remains unclear. In this study, 16 euthymic PBD patients and 16 healthy controls underwent resting-state functional magnetic resonance imaging. A data-driven functional connectivity analysis was used to investigate functional connectivity changes of the euthymic PBD. Compared with healthy controls, the euthymic PBD exhibited greater global functional connectivity density in the left anterior insula and lower global functional connectivity density in the right temporoparietal junction, the left angular gyrus, and the bilateral occipital lobule. A distant functional connectivity analysis demonstrated altered integration within the salience and default mode networks in euthymic PBD. Correlation analysis found that altered functional connectivity of the salience network was related to the reduced performance in the backward digit span test, and altered functional connectivity of the default mode network was related to the Young Mania Rating Scale in euthymic PBD patients. Our findings indicated that disturbed functional integration in salience and default mode networks might shed light on the physiopathology associated with emotional and cognitive dysregulation in PBD.

Recently, increasing attention has been focused on the problem of online AUC maximization, and a great deal of efficient algorithms has been proposed. In spite of the promising performance of those online algorithms, however, most of them are sensitive to the outliers, which make them unsuitable for the applications with noisy data. To tackle the issue, in this paper, an adaptive robust method for online AUC maximization, termed AROAM is suggested. Specifically, a ramp loss based objective function oriented to AUC metric is firstly defined in AROAM, which has the strong ability of suppressing the influence of outliers. Then, concave-convex procedure is adopted for the convex approximation of the objective function. Finally, to further improve the performance of AROAM, an adaptive learning rate strategy is developed in each iteration, which can update the classifier effectively. Empirical studies on the benchmark data sets demonstrate the superiority of the proposed method in comparison with the state-of-the-arts.

Abstract The SrTiO3 modified rutile TiO2 composite nanofibers were synthesized by a simple electrospinning technique. The result of XRD, SEM and TEM indicate that the SrTiO3/TiO2 heterojuction has been prepared successfully. Compared with the TiO2 and SrTiO3, the photocatalytic activity of the SrTiO3/TiO2 (rutile) for the degradation of methyl orange exhibits an obvious enhancement under UV illumination. which is almost 2 times than that of bare TiO2 (rutile) nanofiber. Further, the high crystallinity and photon-generated carrier separation of the SrTiO3/TiO2 heterojuction are considered as the main reason for this enhancement.

Structural changes in the hippocampus and amygdala have been demonstrated in schizophrenia patients. However, whether morphological information from these subcortical regions could be used by machine learning algorithms for schizophrenia classification were unknown. The aim of this study was to use volume of the amygdaloid and hippocampal subregions for schizophrenia classification. The dataset consisted of 57 patients with schizophrenia and 69 healthy controls. The volume of 26 hippocampal and 20 amygdaloid subregions were extracted from T1 structural MRI images. Sequential backward elimination (SBE) algorithm was used for feature selection, and a linear support vector machine (SVM) classifier was configured to explore the feasibility of hippocampal and amygdaloid subregions in the classification of schizophrenia. The proposed SBE-SVM model achieved a classification accuracy of 81.75% on 57 patients and 69 healthy controls, with a sensitivity of 84.21% and a specificity of 81.16%. AUC was 0.8241 (p < 0.001 tested with 1000-times permutation). The results demonstrated evidence of hippocampal and amygdaloid structural changes in schizophrenia patients, and also suggested that morphological features from the amygdaloid and hippocampal subregions could be used by machine learning algorithms for the classification of schizophrenia.

In this work, nanocrystalline AZ31 magnesium alloy powders, reinforced by submicron TiB2 particles, were prepared via mechanical milling. It was found that TiB2 particles stimulated the fracture and welding of AZ31/TiB2 powders, leading to the acceleration of the milling process. Meanwhile, the TiB2 particles were refined to submicron-scale size during the milling process, and their distribution was uniform in the Mg matrix. In addition, the matrix was significantly refined during the milling process, which was also accelerated by the TiB2 particles. The formation of grain boundary segregation layers also led to the weakened TiB2 peaks in the XRD patterns during the mechanical milling. The grain sizes of AZ31–2.5 wt % TiB2, AZ31–5 wt % TiB2 and AZ31–10 wt % TiB2 powders were refined to 53 nm, 37 nm and 23 nm, respectively, after milling for 110 h. Under the combined effect of the nanocrystalline matrix and the well-dispersed submicron TiB2 particles, the AZ31/TiB2 composites exhibited excellent micro-hardness. For the AZ31–10 wt % TiB2 composite, the micro-hardness was enhanced to 153 HV0.5.

Background: The hippocampus is an important limbic structure closely related to memory function. However, few studies have focused on the association between hippocampal subfields and age-related memory decline. We investigated the volume alterations of hippocampal subfields at different ages and assessed the correlations with Immediate and Delayed recall abilities.Materials and Methods: A total of 275 participants aged 20–89 years were classified into 4 groups: Young, 20–35 years; Middle-early, 36–50 years; Middle-late, 51–65 years; Old, 66–89 years. All data were acquired from the Dallas Lifespan Brain Study (DLBS). The volumes of hippocampal subfields were obtained using Freesurfer software. Analysis of covariance (ANCOVA) was performed to analyze alterations of subfield volumes among the 4 groups, and multiple comparisons between groups were performed using the Bonferroni method. Spearman correlation with false discovery rate correction was used to investigate the relationship between memory recall scores and hippocampal subfield volumes.Results: Apart from no significant difference in the left parasubiculum (P = 0.269) and a slight difference in the right parasubiculum (P = 0.022), the volumes of other hippocampal subfields were significantly different across the adult lifespan (P < 0.001). The hippocampal fissure volume was increased in the Old group, while volumes for other subfields decreased. In addition, Immediate recall scores were associated with volumes of the bilateral molecular layer, granule cell layer of the dentate gyrus (GC-DG), cornus ammonis (CA) 1, CA2/3, CA4, left fimbria and hippocampal amygdala transition area (HATA), and right fissure (P < 0.05). Delayed recall scores were associated with the bilateral molecular layer, GC-DG, CA2/3 and CA4; left tail, presubiculum, CA1, subiculum, fimbria and HATA (P < 0.05).Conclusion: The parasubiculum volume was not significantly different across the adult lifespan, while atrophy in dementia patients in some studies. Based on these findings, we speculate that volume changes in this region might be considered as a biomarker for dementia disorders. Additionally, several hippocampal subfield volumes were significantly associated with memory scores, further highlighting the key role of the hippocampus in age-related memory decline. These regions could be used to assess the risk of memory decline across the adult lifespan.