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Understanding the pathogenesis of temporal lobe epilepsy (TLE) is essential for its diagnosis and treatment. The study aimed to explore regional homogeneity (ReHo) and changes in effective connectivity (EC) between brain regions in TLE patients, hoping to discover potential abnormalities in certain brain regions in TLE patients.Resting-state functional magnetic resonance data were collected from 23 TLE patients and 32 normal controls (NC). ReHo was used as a feature of multivariate pattern analysis (MVPA) to explore the ability of its alterations in identifying TLE. Based on the results of the MVPA, certain brain regions were selected as seed points to further explore alterations in EC between brain regions using Granger causality analysis.MVPA results showed that the classification accuracy for the TLE and NC groups was 87.27%, and the right posterior cerebellum lobe, right lingual gyrus (LING_R), right cuneus (CUN_R), and left superior temporal gyrus (STG_L) provided significant contributions. Moreover, the EC from STG_L to right fusiform gyrus (FFG_R) and LING_R and the EC from CUN_R to the right occipital superior gyrus (SOG_R) and right occipital middle gyrus (MOG_R) were altered compared to the NC group.The MVPA results indicated that ReHo abnormalities in brain regions may be an important feature in the identification of TLE. The enhanced EC from STG_L to FFG_R and LING_R indicates a shift in language processing to the right hemisphere, and the weakened EC from SOG_R and MOG_R to CUN_R may reveal an underlying mechanism of TLE.

The dynamic description of neural networks has attracted the attention of researchers for dynamic networks may carry more information compared with resting-state networks. As a non-invasive electrophysiological data with high temporal and spatial resolution, magnetoencephalogram (MEG) can provide rich information for the analysis of dynamic functional brain networks. In this review, the development of MEG brain network was summarized. Several analysis methods such as sliding window, Hidden Markov model, and time-frequency based methods used in MEG dynamic brain network studies were discussed. Finally, the current research about multi-modal brain network analysis and their applications with MEG neurophysiology, which are prospected to be one of the research directions in the future, were concluded.

Transcutaneous vagus nerve stimulation, which involves the application of electrical currents to the cervical (tcVNS) or auricular (taVNS) branches of the vagus nerve, may be a potential treatment for improving cognitive dysfunction. taVNS may improve cognitive performance in healthy adults, and fewer studies have been performed on the effects of tcVNS on cognition in healthy subjects. We conducted a randomized, single-blind, crossover-controlled trial to investigate the effects of tcVNS stimulation on cognitive function and neural activity in the brains of healthy adults. This study provides support for further tcVNS studies for the treatment of cognitive impairment. Twenty-one participants were randomly divided into two groups, A and B. Group A received tcVNS first and then sham-tcVNS, while group B received the intervention in the reverse order, receiving sham stimulation first and then true stimulation. All subjects were required to perform cognitive function tests before and after receiving intervention, and functional magnetic resonance imaging (fMRI) was performed concurrently during the intervention. We hypothesized that tcVNS would have an effect on the cognitive performance of the subjects and alter the neural activity of the brain. The present study showed that tcVNS had beneficial effects on cognitive performance, mainly improving memory and language skills and attention. tcVNS intervention produced significant spontaneous neural activity in the calcarine gyrus, fusiform gyrus, lingual gyrus, and parahippocampal gyrus of the brain. Future tcVNS/fMRI trials will need to explore the effects of changes in stimulus parameters on the neural activity response of the brain.

Alzheimer's disease (AD), a progressive disorder, has become a global health problem and is now the main cause of dementia. The aetiology of AD is complex and remains elusive making effective AD treatment difficult. Current drugs for AD only improve symptoms but do not interfere with pathogenic mechanisms. Three main hypotheses have been brought forward regarding AD aetiology, one of them being the 'inflammation hypothesis'. A number of studies have demonstrated that inflammation plays a critical role in AD. Self-limiting neuroinflammation is considered beneficial to AD, whereas chronic inflammation aggravates brain injury and neuronal death. Transforming growth factor β 1(TGF-β1) is an anti-inflammatory cytokine with neuroprotective properties. Smad proteins are downstream molecules of TGF-β signalling. They are cytoplasmic transcription factors that can regulate targeted gene expression. In AD, impairments of TGF-β1/Smad pathways have been observed. Moreover, microglia, astrocytes, inflammasomes, and insulin resistance also have been implicated in AD pathogenesis. Elucidating the molecular mechanisms underlying AD pathogenesis is a fundamental step toward designing new treatment options. In this review, we detail the changes in TGF-β1/Smad pathways in AD and hope this will facilitate further research on AD treatment.

Introduction Drug-resistant cytomegalovirus (CMV) infection remains a challenge in the management of pediatric recipients of hematopoietic stem cell transplantation (HSCT). In this study, we retrospectively reviewed the clinical data on pediatric recipients of HSCT and identified known and unknown drug-resistant CMV variants. Methods A total of 221 children underwent allogeneic HSCT between October 2017 and November 2019 at Shenzhen Children’s Hospital; of these, 35 patients were suspected of having drug-resistant CMV infections and were tested for drug-resistant mutations in the UL97 and UL54 genes by Sanger sequencing. Results Mutations in UL97 or UL54, or in both, were detected in 11 patients. Most of these mutations have not been previously reported. The UL97 mutation (A582V) was detected in only one patient who also harbored two UL54 mutations (T760X and R876W). One patient with both the G604S and T691A mutations in the UL54 gene died of CMV pneumonia. We investigated the risk factors associated with the development of drug-resistant CMV infection. Patients in whom both the donor and recipient had positive CMV serostatuses were less likely to have drug-resistant mutations (Fisher’s exact test, p

BackgroundCoronavirus disease 2019 (COVID-19) significantly impacts physical, psychological, and social functioning and reduces quality of life, which may persist for at least 6 months. Given the fact that COVID-19 is a highly infectious disease and therefore healthcare facilities may be sources of contagion, new methods avoiding face-to-face contact between healthcare workers and patients are urgently needed. Telerehabilitation is the provision of rehabilitation services to patients at a distance via information and communication technologies. However, high-quality evidence of the efficacy of telerehabilitation for COVID-19 is still lacking. This meta-analysis aimed to investigate the efficacy of telerehabilitation for patients with and survivors of COVID-19.MethodsWe searched the Cochrane Library, EMBASE, Medline (via PubMed), PEDro, ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform from January 1st, 2020 to April 30th, 2022 for randomized controlled trials published in English, which aimed to evaluate the efficacy of telerehabilitation vs. face-to-face rehabilitation, usual care, or no treatment for COVID-19. Methodological quality and overall evidence quality of the included studies were assessed. The statistical reliability of the data was quantified using the trial sequential analysis.ResultsSeven randomized controlled trials with eight comparisons were included and all of them were used for meta-analysis. The meta-analyses of absolute values showed the superiority of telerehabilitation over no treatment or usual care for dyspnea (Borg scale: mean difference = −1.88, −2.37 to −1.39; Multidimensional dyspnea-12: mean difference = −3.70, −5.93 to −1.48), limb muscle strength (mean difference = 3.29; 2.12 to 4.47), ambulation capacity (standardized mean difference = 0.88; 0.62 to 1.14), and depression (mean difference = −5.68; −8.62 to −2.74). Significant improvement in these variables persisted in the meta-analyses of change scores. No significant difference was found in anxiety and quality of life. No severe adverse events were reported in any of the included studies.ConclusionsModerate- to very low-quality evidence demonstrates that telerehabilitation may be an effective and safe solution for patients with and survivors of COVID-19 in dyspnea, lower limb muscle strength, ambulation capacity, and depression. Further well-designed studies are required to evaluate the long-term effects, cost-effectiveness, and satisfaction in larger samples.

In evidence theory, Dempster’s rule of combination is the most commonly applied method to aggregate bodies of evidence obtained from different sources to make a decision. However, when multiple independent bodies of evidence with conflict are aggregated by Dempster’s rule of combination, the counterintuitive results can be generated. Evidence discounting is proved to be an efficient way to eliminate the counterintuitive combination results. Following the discounting ideas, a new combination approach based on fuzzy discounting is put forward. Both the conflict between bodies of evidence and the uncertainty of a body of evidence itself are taken into account to determine the discounting factors. Jousselme’s evidence distance is used to represent conflict between bodies of evidence, and discriminability measure is defined to represent uncertainty of a body of evidence itself. Consider that both the evidence distance and the discriminability measure are semantically fuzzy. Thus, fuzzy membership functions are defined to describe both of them, and a fuzzy reasoning rule base is constructed to derive the discounting factors. Numerical examples indicate that this new combination approach proposed can achieve fast convergence speed and is robust to disturbing evidences, i.e., it is an effective method to process conflicting evidences combination.

Epilepsy is a brain syndrome caused by synchronous abnormal discharge of brain neurons. As an effective treatment for epilepsy, successful surgical resection requires accurate localization of epileptic foci to avoid iatrogenic disability. Previous studies have demonstrated the potential of restingstate functional magnetic resonance imaging (rs-fMRI) technique to localize epileptic foci though clinical applications of rs-fMRI are still at an early stage of development. fMRI data analysis approaches seek pre-defined regressors modeling contributions to the voxel time series, including the BOLD response following neuronal activation. In present study, localization strategies of epileptic foci in rs-fMRI technology were classified and summarized. To begin with, data-driven approaches attempting to determine the intrinsic structure of the data were discussed in detail. Then, as novel fMRI data analysis methods, deconvolution algorithms such as total activation (TA) and blind deconvolution were discussed, which were applied to explore the underlying activity-inducing signal of the BOLD signal. Lastly, effective connectivity approaches such as autocorrelation function method and Pearson correlation coefficient have also been proposed to identify the brain regions driving the generation of seizures within the epileptic network. In the future, fMRI technology can be used as a supplement of intraoperative subdural electrode method or combined with traditional epileptic focus localization technologies, which is one of the most attractive aspect in clinic. It may also play an important role in providing diagnostic information for epilepsy patients.

Shoujun Xu,1,&ast; Meng Li,2,&ast; Chunlan Yang,3 Xiangling Fang,4 Miaoting Ye,4 Yunfan Wu,2 Binrang Yang,4 Wenxian Huang,4 Peng Li,1 Xiaofen Ma,2 Shishun Fu,2 Yi Yin,2 Junzhang Tian,2 Yungen Gan,1 Guihua Jiang2 1Department of Radiology, Shenzhen Children’s Hospital, Shenzhen, People’s Republic of China; 2Department of Medical Imaging, Guangdong Second Provincial General Hospital, Guangzhou, People’s Republic of China; 3Department of Hematology and Oncology, Shenzhen Children’s Hospital, Shenzhen, People’s Republic of China; 4Department of Department of Children Healthcare, Shenzhen Children’s Hospital, Shenzhen, People’s Republic of China&ast;These authors have contributed equally to this workCorrespondence: Guihua Jiang; Yungen Gan, Email jianggh@gd2h.org.cn; gdszgyg-1@126.comPurpose: This study used the graph-theory approach, degree centrality (DC) to analyze whole-brain functional networks at the voxel level in children with ASD, and investigated whether DC changes were correlated with any clinical variables in ASD children.Methods: The current study included 86 children with ASD and 54 matched healthy subjects Aged 2– 5.5 years. Next, chloral hydrate induced sleeping-state functional magnetic resonance imaging (ss-fMRI) datasets were acquired from these ASD and healthy subjects. For a given voxel, the DC was calculated by calculating the number of functional connections with significantly positive correlations at the individual level. Group differences were tested using two-sample t-tests (p < 0.01, AlphaSim corrected). Finally, relationships between abnormal DCs and clinical variables were investigated via Pearson’s correlation analysis.Results: Children with ASD exhibited low DC values in the right middle frontal gyrus (MFG) (p 

While bacterial diversity is beneficial for the functioning of rhizosphere microbiomes, multi-species bioinoculants often fail to promote plant growth. One potential reason for this is that competition between inoculated consortia members create conflicts for their survival and functioning. To circumvent this, we used transposon mutagenesis to increase the functional diversity within Bacillus amyloliquefaciens bacterial species and tested if we could improve plant growth-promotion by assembling consortia of closely related but functionally specialized mutants. While most insertion mutations were harmful, some improved strains’ plant growth-promotion traits without increasing antagonism between them. Crucially, plant growth-promotion could be improved by applying these specialist mutants as consortia, leading to clear positive relationships between consortia richness, plant root colonization and protection from bacterial wilt disease. Together, our results suggest that increasing intra-species diversity could be an effective way to increase probiotic consortia multifunctionality, leading to more stable plant growth-promotion throughout growth cycle via insurance effects.

Background：Rheumatoid arthritis (RA) is a chronic autoimmune disease. Imrecoxib, disease-modifying anti-rheumatic drugs (DMARDs) and total glucosides of paeony (TGPs) are common clinical therapies for RA. However, the exact mechanism of combination therapy for rheumatoid arthritis is still unclear. This study aims to explore the potential mechanism of this combination therapy for RA.Methods：Five RA patients who used this combination drug therapy were enrolled. Serum was collected at the first visit and the second visit after 3 months of continuous use of the combination treatment. Label-free quantitative proteomics was used to perform a comparative analysis of protein expression in serum after depletion of high-abundance proteins. The GO database was used to annotate the functions of differentially expressed proteins (DEPs).Results： A total of 257 reliable proteins were identified. Six proteins (IGKV3-20, TTR, LRG1, SERPINA3, F10 and NMNAT3) were downregulated, and one protein (HBD) was upregulated after three months of continuous combination drug treatment. Bioinformatics analysis showed that DEPs were primarily involved in various biological processes, such as metabolic processes, cellular processes and biological regulation. The identified DEPs have been reported to be involved in inflammation, cell proliferation, angiogenesis and oxidative stress. Therefore, these proteins have played important roles in RA progression.Conclusion： This combination drug therapy could alleviate the symptoms of RA by regulating these DEPs associated with RA in different ways. The DEPs identified may help to predict the treatment outcome of therapy for RA in the future.

Background Hydroxychloroquine (HCQ) is a cornerstone therapy for systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). This study aimed to investigate the relationship of cytochrome P450 (CYP450) gene polymorphisms with blood concentrations of HCQ and its metabolites and adverse drug reactions (ADRs) in patients with SLE and RA. Methods A cohort of 146 patients with SLE and RA treated with HCQ was reviewed. The ADRs of the patients were recorded. The blood concentrations of HCQ and its metabolites were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Genotyping of single nucleotide polymorphisms (SNPs) in CYP450, a metabolic enzyme involved in the HCQ metabolic pathway, was performed using a MassARRAY system. The chi-square test, T-test, and one-way analysis of variance were used to analyse data. Results Among 29 candidate SNPs, we found that CYP3A4 (rs3735451) was significantly associated with blood levels of HCQ and its metabolites in both the unadjusted model and adjusted model (patients taking HCQ for > 10 years) (P P = 0.033). For CYP2C8 (rs1058932), the AG genotype carried a greater risk of abnormal renal function than the AA + GG genotype (P = 0.017); for rs10882526, the GG genotype carried a greater risk of ophthalmic ADRs than the AA + AG genotypes (P = 0.026). Conclusions The CYP2C8 (rs1058932 and rs10882526) and CYP3A5 (rs776746) polymorphisms are likely involved in the ADRs of HCQ. Gene polymorphism analysis of CYP450 and therapeutic drug monitoring of HCQ and its metabolites might be useful to optimise HCQ administration and predict ADRs.

To investigate the genetic etiology, clinical diagnosis and treatment of a child with pancytopenia, failure to thrive and pulmonary infection.Peripheral blood samples of the child and her parents were collected. Genomic DNA was extracted. Genetic variants associated with hematological diseases were detected by high-throughput sequencing.Three variants of TCN2 gene were found, one of which located in exon 5 upstream(c.581-8AT), the parents has carried this variant; one in exon 6 (c.924_927del), the variant was originated from the mother; one in exon 7 (c.973CT), the variant has ocurred de novo. The variants pathogenic analysis combined with clinical manifestation, pancytopenia, the increase in methylmalonic acid level and increased homocysteine, the child was diagnosed with transcobalaminIIdeficiency. The patient presented with respiratory infection, which was confirmed to be pneumocystosis by lung radioscopy and pathogenic high-throughput sequencing of broncho-alveolar lavage fluid. The patient presented with acute respiratory distress syndrome during the treatment with intramuscular injection of vitamin BWe reported a case of Chinese child with TCNII deficiency due to novel gene variant, and analyzed the pathogenicity of the three variants. The treatment of TCNII deficiency with cobalamin should be individualized.

Tumor Necrosis Factor was one of the first cytokines described in the literature as a soluble mediator of cytotoxicity to tumors. Over the years, more extensive research that tried to employ Tumor Necrosis Factor in cancer treatments showed nevertheless that it mainly functioned as a proinflammatory cytokine. However, this did not stop the search for the holy grail of cancer research: A cytokine that could act as a one-stop treatment for solid tumors and lymphomas. This review will summarize the long experimental history of Tumor Necrosis Factor that caused the initial observations of a tumor necrotizing cytokine that could serve as a potential cancer treatment and discuss the current state of research into this side of the activities of Tumor Necrosis Factor.

Changes in the brain networks of patients with temporal lobe epilepsy (TLE) have been extensively explored, but the biological mechanisms underlying these alterations remain unclear. Here, we aim to identify changes in brain networks in patients with TLE and provide an accurate algorithm for distinguishing these patients from normal controls (NC) with graph-theoretical approach and advanced machine learning methods.Directed network construction was applied to resting-state functional magnetic resonance imaging (rs-fMRI) data from 55 subjects (23 TLE patients and 32 NC), and 13 directed graph measures were calculated. Two-sample t-test selected features were used as inputs to a support vector machine (SVM). The leave-one-out cross-validation method was used in measuring classification performance.An accuracy of 94.55% (sensitivity = 91.30%, f1-score = 93.33%, Cohen's kappa = 0.9345) was achieved for the classification of TLE patients and NC with optimal features and SVM classifier. According to the results of the two-sample t-test results, TLE disease impacted several areas of the brain, including the temporal, parietal, occipital, posterior cingulate, angular gyrus, superior frontal gyrus, and cerebellum regions in degree centrality, flow coefficient and node efficiency. There was a significant correlation between performance IQ and the flow coefficient of the left posterior cerebellum lobe in TLE group.The study confirmed the validity of Granger causality analysis in constructing directed brain networks. The proposed machine learning approach based on directed graph measures may serve as a biomarker for the diagnosis of TLE to assist in the early diagnosis of TLE patients and intervention in treatment plans.

Antibiosis and resource competition are major drivers shaping the assembly, diversity and functioning of microbial communities. While it is recognized that competition is sensitive to environmental conditions, it is unclear to what extent this mediated by the availability of different carbon resources. Here, we used a model laboratory system to directly test this by exploring how carbon resource richness and identity shape resource competition and antibiosis between plant probiotic Bacillus amyloliquefaciens and phytopathogenic Ralstonia solanacearum bacteria. We found that while sugars typically promoted B. amyloliquefaciens growth, organic and amino acids increased the production of both bacillaene and macrolactin antibiotics and the direct inhibition of R. solanacearum. In contrast, when multiple different carbon resources were available, B. amyloliquefaciens could efficiently grow and produce antibiotics at the same time. Together, these results suggest that high carbon resource richness allows concurrent expression of growth- and antibiosis-related traits, potentially altering bacterial competitive dynamics and plant growth promotion in microbial communities. A plain language summary is available for this article.

Obstructive sleep apnea syndrome (OSAS) has become a major worldwide public health concern, given its global prevalence. It has clear links with multiple comorbidities and mortality. Cognitive impairment is one related comorbidity causing great pressure on individuals and society. The clinical manifestations of cognitive impairment in OSAS include decline in attention/vigilance, verbal–visual memory loss, visuospatial/structural ability impairment, and executive dysfunction. It has been proven that chronic intermittent hypoxia (CIH) may be a main cause of cognitive impairment in OSAS. Inflammation plays important roles in CIH-induced cognitive dysfunction. Furthermore, the nuclear factor kappa B and hypoxia-inducible factor 1 alpha pathways play significant roles in this inflammatory mechanism. Continuous positive airway pressure is an effective therapy for OSAS; however, its effect on cognitive impairment is suboptimal. Therefore, in this review, we address the role inflammation plays in the development of neuro-impairment in OSAS and the association between OSAS and cognitive impairment to provide an overview of its pathophysiology. We believe that furthering the understanding of the inflammatory mechanisms involved in OSAS-associated cognitive impairment could lead to the development of appropriate and effective therapy.

BACKGROUND: Pulmonary arterial smooth muscle cells(PASMCs) proliferation plays a crucial role in Hypoxia-induced pulmonary hypertension(HPH). Previous studies have found that Resistin-like molecule β(RELM-β) up-regulated de novo in response to hypoxia in cultured primary human PASMCs(HASMCs). RELM-β has been proved to promote PASMCs proliferation and involved in pulmonary vascular remodeling of patients with PAH. However, the expression pattern, the effects, and the mechanisms of RELM-β in HPH keep unknown. METHODS: We assessed the expression pattern, mitogenetic effect, and underlying mechanism of RELM-β in the rat HPH model and HASMCs. RESULTS: Overexpression of RELM-β alone caused the hemodynamic change in the rat model of HPH, similar to that caused by chronic hypoxia, with increased mean pulmonary arterial pressure(mPAP), right ventricle hypertrophy(RVSP), and thickening of small pulmonary arterioles. Knocking down of RELM-β partially blocked the increased mPAP, RVSP, and vascular remodeling induced by hypoxia. Phosphorylated PI3K/Akt/mTOR and PKC/MAPKs proteins were significantly up- or down-regulated by RELM-β gene overexpression or silencing. Recombinant RELM-β protein increase primary cultured human PASMCs intracellular Ca 2+ concentration and promote HASMCs proliferation. The mitogenic effect of RELM-β on HASMCs and phosphorylated PI3K/Akt/mTOR and PKC/MAPKs was suppressed by Ca 2+ inhibitor. CONCLUSIONS: Our findings suggested that RELM-β acts as a cytokine-like growth factor in the development of HPH and that this process is likely mediated by the Ca 2+ dependent PI3K/Akt/mTOR and PKC/MAPKs pathway. Keywords : hypoxic pulmonary arterial hypertension; resistin-like molecule β; Ca 2+ ; pulmonary vascular remodeling; signaling pathway

Mining induced land subsidence is one of the most hazardous geological phenomenon. Predictive modeling of the ground subsidence has attracted increased interest and is crucial to the hazard prevention. In this research, a data-driven approach integrated with survival analysis to model the mining-induced subsidence is studied. The data used in this research is collected in Fuxin, Liaoning Province, China and it contains multiple variables from different subsided locations. First, a survival analysis is conducted using the Cox proportional hazard model to evaluate the importance of variables considered. p values of all variables are computed and the important variables are selected. Next, data-driven models including k-nearest neighbor, support vector machine, back-propagated neural network, random forest, extreme learning machine, and online sequential extreme learning machine are constructed to predict the subsidence values and horizontal movement. Two evaluation matrices namely MAPE and RMSE are introduced to evaluate the performances of the data-driven models. Computational results demonstrate that online sequential extreme learning machine is capable of accurately predict the mining induced subsidence and surface deformation.

Normal aging has been linked with the decline of cognitive functions, such as memory and executive skills. One of the prominent approaches to investigate the age-related alterations in the brain is by examining the cortical brain connectome. IBASPM is a toolkit to realize individual atlas-based volume measurement. Hence, this study seeks to determine what further alterations can be revealed by cortical brain networks formed by IBASPM-extracted regional gray matter volumes. We found the reduced strength of connections between the superior temporal pole and middle temporal pole in the right hemisphere, global hubs as the left fusiform gyrus and right Rolandic operculum in the young and aging groups, respectively, and significantly reduced inter-module connection of one module in the aging group. These new findings are consistent with the phenomenon of normal aging mentioned in previous studies and suggest that brain network built with the IBASPM could provide supplementary information to some extent. The individualization of morphometric features extraction deserved to be given more attention in future cortical brain network research.

A green and convenient anhydrous method was developed to synthesize hydrophilic carbon dots (H-CDs) on large-scale in this work. During the whole process of preparation, toxicity materials and high pressure conditions were not used, and H-CDs can be formed in several minutes by directly putting glucose powder into hot edible oil, which can be used again. Therefore, it is a green method and very suitable for the industrial preparation of CDs on large-scale. Characterizations demonstrate the H-CDs possess excellent optical properties, higher photostability and very low cytotoxicty. Noticeably, the H-CDs exhibit a distinct pH-sensitive feature, and have been used to construct fluorescent pH sensor with a nice linear relationship in the pH range of 3.0–13.0. To the best of our knowledge, this is the broadest reported pH range based on carbon dots without heteroatom doped. The mechanism of pH-sensitive response was also discussed. The proposed pH sensor has been successfully used for the pH monitoring of environmental water samples and living cells, which demonstrates their applicability in complex matrixes.

In patients with Alzheimer's Disease (AD), the hippocampal network has been extensively investigated in previous studies; however, little is known about the morphological network associated with the hippocampus in the AD patients. A total of 68 patients with AD and another 68 gender and age matched healthy subjects were studied. Individual-level morphological hippocampal networks were constructed based on volume and texture features extracted from MRI to study the connections between bilateral hippocampus and 11 other subcortical gray matter structures. The relationship between morphological connections and Mini-Mental State Examination (MMSE) scores was also studied. Connections between bilateral hippocampus and bilateral thalamus, bilateral putamen were significant differences between the AD patients and controls (p 0.05). There were significantly different in bilateral hippocampal connectivity, and for the left hippocampus, the connection to the right caudate were found to be statistically significant. The morphological connections between left hippocampus and bilateral thalamus (left: R = 0.371, p 0.001; right: R = 0.411, p 0.001), bilateral putamen (left: R = 0.383, p 0.001; right: R = 0.348, p 0.001), right hippocampus and bilateral thalamus (left: R = 0.370, p 0.001; right: R = 0.387, p 0.001), left putamen (R = 0.377, p 0.001) were significantly positively correlated with the MMSE scores. Similar patterns were observed for left and right hippocampal connectivity and the connections highly associated with MMSE scores were also within the abnormal connections in AD patients.

Retinal images play an important role in the early diagnosis of diseases such as diabetes. In the present study, an automatic image processing technique is proposed to segment retinal blood vessels in fundus images. The technique includes the design of a bank of 180 Gabor filters with varying scale and elongation parameters. Furthermore, an optimization method, namely, the imperialism competitive algorithm (ICA), is adopted for automatic parameter selection of the Gabor filter. In addition, a systematic method is proposed to determine the threshold value for reliable performance. Finally, the performance of the proposed approach is analyzed and compared with that of other approaches on the basis of the publicly available DRIVE database. The proposed method achieves an area under the receiver operating characteristic curve of 0.953 and an average accuracy of up to 0.9392. Thus, the results show that the proposed method is well comparable with alternative methods in the literature.

Esculetin is an important bioactive coumarin with amazing potential to suppress the growth of cancer cells. The present study was designed to investigate the anticancer effects of esculetin against the human leukemia HL-60 cells.CCK-8 assay was used to assess cell viability. DAPI and annexin V/propidium iodide (PI) staining was performed to investigate the induction of apoptosis. Autophagy was detected by electron microscopic analysis. Flow cytometry was used for cell cycle analysis and Western blotting was used to estimate protein expression.Esculetin suppressed the proliferation of HL-60 cells dose-dependently. The IC50 of esculetin against HL-60 cells was observed to be 20 µM. The anticancer effects of esculetin against HL-60 cells occurred though different mechanisms. Esculetin induced apoptosis and autophagy in leukemia cells, which were accompanied by alteration in the expression of apoptosis as well as autophagy-related proteins. Esculetin also triggered G0/G1 cell cycle arrest in HL-60 cells, which was also accompanied by suppression of Cyclin D1 and D3. Esculetin could also block the Raf/MEK/ERK signalling pathway in leukemia cells in a concentration-dependent manner.These results indicate that esculetin inhibits the growth of leukemia cells and hence may prove beneficial for treating leukemia.

Traditionally, musk has been used as an analgesic to treat pain associated with cancer. Hepatocellular carcinoma (HCC) is an aggressive tumor; however, patients with liver cancer that received musk were reported to live longer and have a higher quality of life. Thus, the present study aimed to investigate whether muscone, a macrocyclic compound of musk, demonstrated potential as an anti‑liver cancer drug for the non‑surgical treatment of advanced liver cancer. Briefly, liver cancer cells were treated with muscone and the rates of cellular apoptosis and autophagy were investigated using staining techniques and western blotting. The underlying molecular mechanisms of muscone were evaluated using high‑throughput sequencing and the in vitro effects of muscone were subsequently validated in vivo using a nude mouse model. Muscone increased the rates of apoptosis and autophagy in liver cancer cells; the increase in cellular apoptosis was observed to occur through endoplasmic reticulum stress responses, whereas muscone‑induced autophagy was closely associated with the AMP kinase/mTOR complex 1 signaling pathway. These findings were verified in vivo. Notably, sestrin‑2 expression levels were also significantly decreased in liver cancer tissues compared with paracancerous tissues. In conclusion, the present study suggests that muscone demonstrates potential as an anticancer drug, and the findings of the present study provide the basis for the development of effective anticancer drugs derived from natural compounds.

Background: Although functional brain connectivity in anxiety-related disorders has been studied, brain connectivity in non-clinical populations with high trait anxiety has been rarely reported. Whether structural brain connectivity changes in young healthy individuals with high trait anxiety remains unknown. Methods: Thirty-eight young healthy individuals with high anxiety levels and 34 healthy subjects with low anxiety levels who were matched by age, gender, and educational level were recruited. Diffusion tensor images were acquired to analyze white matter connectivity. A two-sample t-test was used for group comparison of weighted networks and graph properties. Results: Different connections were detected in fractional anisotropy- and fiber number-weighted networks. These connections were widely distributed in various regions, where relative significance was located in the inter-hemispheric frontal lobe, the frontal-limbic lobe in the right intra-hemisphere, and the frontal-temporal lobe in the ipsilateral hemisphere. However, no significant difference was found in fiber length-weighted network and in graph properties among the three networks. Conclusions: The structural connectivity of white matter may be a vulnerability marker. Hence, healthy individuals with high trait anxiety levels are susceptible to anxiety-related psychopathology. The findings may help elucidate the pathological mechanism of anxiety and establish interventions for populations susceptible to anxiety disorders.

Neuroimaging studies have shown that autism spectrum disorders (ASDs) may be associated with abnormalities in brain structures and functions at rest as well as during cognitive tasks. However, it remains unclear if functional connectivity (FC) of all brain neural networks is also changed in these subjects. In this study, we acquired functional magnetic resonance imaging scans from 93 children with ASD and 79 matched healthy subjects. Group independent component analysis was executed for all of the participants to estimate FC. One-sample t-tests were then performed to obtain the networks for each group. Group differences in the different brain networks were tested using two-sample t-tests. Finally, relationships between abnormal FC and clinical variables were investigated with Pearson’s correlation analysis. The results from one-sample t-tests revealed nine networks with similar spatial patterns in these two groups. When compared with the controls, children with ASD showed increased connectivity in the right dorsolateral superior frontal gyrus and left middle frontal gyrus (MFG) within the occipital pole network. Children with ASD also showed decreased connectivity in the left gyrus rectus, left middle occipital gyrus, right angular gyrus, right MFG and right inferior frontal gyrus (IFG), orbital part within the lateral visual network (LVN), the left IFG, right precuneus, and right angular gyrus within the left frontoparietal (cognition) network. Furthermore, the mean FC values within the LVN showed significant positive correlations with total score of the Childhood Autism Rating Scale. Our findings indicate that abnormal FC extensively exists within some networks in children with ASD. This abnormal FC may constitute a biomarker of ASD. Our results are an important contribution to the study of neuropathophysiological mechanisms in children with ASD.

Background and objective Magnetoencephalography (MEG) is an advanced magnetic source imaging technology that measures the magnetic fields produced by neural activities. It has been extensively used in scientific research and clinical diagnosis due to its high temporal and spatial resolution. Considering the special nature of MEG data, it needs to perform a series of processes and analysis to obtain valuable information. Therefore, the identification of data processing is a key point of MEG studies. At present, the software for MEG analysis such as FieldTrip has no Graphic User Interface (GUI) and users must write their own script to perform concrete analysis. It brings the difficulties to researchers like the doctors without experience in programming or newcomers to MEG. Thus, an open-sourced software-EasyMEG was developed. It has friendly interface with highly functions-integration. Methods The functions of EasyMEG are developed based on MATLAB language to ensure the consistency of the user interface under different operating systems. EasyMEG is a highly integrated software that contains a set of functions for preprocessing, time-lock analysis, time–frequency analysis, source analysis, and plotting. EasyMEG provides a friendly GUI and allows users to complete analyses through a simple and clean interface. Results This toolbox has been released as an open-source software on GitHub under the GNU General Public License: https://tonywu2018.github.io/EasyMEG/ . Conclusions We hope to improve this toolbox by the power of community and wish to make EasyMEG a simple and powerful toolbox for further MEG studies.

Hippocampus, an area of cortex that plays an important role in thinking, planning and remembering. In Alzheimer’s disease (AD), the hippocampus is one of the first areas of the brain to become shriveled and this leads to the memory less, damage in learning and declaration of emotional behaviors. In this paper, we investigate the effects of sex on hippocampus gray matter (HGM) atrophy in four groups of participants, namely, males with AD (M-AD, n = 34), age-matched normal male controls (M-NC, n = 34), females with AD (F-AD, n = 34), and age matched normal female controls (F-NC, n = 34) from ADNI dataset. In this regard, Analysis of variance (ANOVA) is employed to compare means of HGM differences among groups. The statistical results obtained by ANOVA show that the distribution of HGM atrophy is effected by sex. Also there was a significant diagnosis with higher severity in the F-AD compared to M-AD. The AD studies based on the sex may help to figure out the root of AD mechanisms and poten-tially can be used as an imaging marker for the studies of AD in the future.

Investigation of the properties and mechanisms of the interactions of root-colonizing biocontrol bacteria and plant pathogens is necessary to optimize the biocontrol strategies. In the present study, the interaction of a biocontrol strain Bacillus amyloliquefaciens T-5 tagged with a green fluorescent protein marker and a bacterial wilt pathogen Ralstonia solanacearum QL-Rs1115 tagged with red fluorescent protein marker was studied on tomato roots using different inoculation methods. The results showed that in the co-culture experiment, the population of pathogen QL-RFP was decreased by increasing the initial inoculum concentration of biocontrol strain. In the greenhouse experiment, both strains T-5-GFP and QL-RFP colonized tomato roots (root tips, root hairs, primary roots, and root junctions) and formed a biofilm on the root surfaces as determined by dilution plating and confocal laser scanning microscopy (CLSM) techniques. However, the root colonization of pathogen strain QL-RFP was almost completely suppressed in the presence of biocontrol strain T-5-GFP when both soil and plant seedlings were treated with T-5-GFP. The results of this study revealed the effectiveness of strain B. amyloliquefaciens T-5 as a biocontrol agent against tomato wilt pathogen and the significance of inoculation method used to inoculate biocontrol strain.

Thalamic segmentation serves an important function in localizing targets for deep brain stimulation (DBS). However, thalamic nuclei are still difficult to identify clearly from structural MRI. In this study, an improved algorithm based on the fuzzy connectedness framework was developed. Three-dimensional T1-weighted images in axial orientation were acquired through a 3D SPGR sequence by using a 1.5T GE magnetic resonance scanner. Twenty-five normal images were analyzed using the proposed method, which involved adaptive fuzzy connectedness combined with confidence connectedness (AFCCC). After non-brain tissue removal and contrast enhancement, the seed point was selected manually, and confidence connectedness was used to perform an ROI update automatically. Both image intensity and local gradient were taken as image features in calculating the fuzzy affinity. Moreover, the weight of the features could be automatically adjusted. Thalamus, ventrointermedius (Vim), and subthalamic nucleus were successfully segmented. The results were evaluated with rules, such as similarity degree (SD), union overlap, and false positive. SD of thalamus segmentation reached values higher than 85%. The segmentation results were also compared with those achieved by the region growing and level set methods, respectively. Higher SD of the proposed method, especially in Vim, was achieved. The time cost using AFCCC was low, although it could achieve high accuracy. The proposed method is superior to the traditional fuzzy connectedness framework and involves reduced manual intervention in time saving. An improved fuzzy connectedness based thalamic segmentation method was proposed.Image local gradient was incorporated in calculation of fuzzy affinity.The weight of intensity and local gradient can be automatic adjusted.Confidence connectedness was used in automatic ROI update.Only one seed point was needed.

Soilborne plant diseases seriously limit agricultural production. Due to environmental concerns, sustainable agricultural practices must involve the use of environmentally friendly alternatives, such as biocontrol microbes (BMs), to suppress various plant diseases. However, the success of BM application largely depends on the carrier formulation. An ideal carrier that can support the survival of a BM while discouraging the growth of the target pathogen is expected to enhance the performance of the BM in plant disease control. In this study, various commercial composts and peats were evaluated as carriers for Bacillus amyloliquefaciens QL-18, a BM used to control tomato bacterial wilt (TBW) caused by the soilborne bacterial pathogen Ralstonia solanacearum. Among the evaluated carriers, rapeseed cake compost (RCC) was found to be the best carrier, acting as both a substrate and food source for B. amyloliquefaciens QL-18. RCC facilitated the growth and survival of strain QL-18 by supplying adequate levels of dissolved carbon and nitrogen. Moreover, aqueous extracts of RCC alone inhibited R. solanacearum growth, suggesting that certain RCC components are toxic to the pathogen. Greenhouse and field experiments demonstrated that RCC improved the ability of B. amyloliquefaciens QL-18 to reduce the incidence of TBW and the population of the pathogen in the tomato rhizosphere. Although other carriers maintained large populations of B. amyloliquefaciens QL-18, similar to those obtained with RCC, they were not deemed suitable carriers because they constituted a poor nutrient supply for B. amyloliquefaciens QL-18 growth; thus, they had less of an impact on disease control. The principle of BM carrier selection should be adopted in the future when developing new bio-products for the effective control of soilborne plant diseases.

Evidence theory is an efficient tool to fuse multi-source information. However, when Dempster’s rule of combination is applied to combine highly conflicting evidences, counter-intuitive results may emerge. In order to resolve such a problem, a new weighted averaging evidence combination method based on singular value was put forward. Minimum singular value can measure the conflict between two evidences more accurately than other common methods. Thus, using singular value to determine the weights of evidences is more reasonable. Based on the weighted averaged evidences and Dempster’s rule, the final results are acquired. The numerical example illustrates that the proposed method can fuse highly conflict evidences effectively and has faster convergence speed and better focusing degree than some other existing combination methods.

Dempster's rule of combination is a core part in evidence theory. However, it may generate an unreasonable result when fusing conflicting evidences. For the sake of dealing with such a problem, a novel discounting method is proposed. Minimum singular value of BPA (basic probability assignment) matrix consisting of two BPAs corresponding to two evidences can measure the dissimilarity between these two evidences more accurately than some other dissimilarity measures. Thus, minimum singular value is applied to determine discounting factor. Then, the discounted evidences are fused by Dempster's rule to make the final decision. This presented discounting method can maintain both the diversity of the evidences and the good properties of Dempster's rule associativity and commutativity. Numerical example illustrates that this evidence discounting method presented can efficiently fuse conflicting evidences and has faster convergence speed, better focusing degree than some existing approaches.

Normal aging is associated with both structural changes in many brain regions and functional declines in several cognitive domains with advancing age. Advanced neuroimaging techniques enable explorative analyses of structural alterations that can be used as assessments of such age-related changes. Here we used voxel-based morphometry (VBM) to investigate regional and global brain volume differences among four groups of healthy adults from the IXI Dataset: older females (OF, mean age 68.35 yrs; n=69), older males (OM, 68.43 yrs; n=66), young females (YF, 27.09 yrs; n=71), and young males (YM, 27.91 yrs; n=71), using 3D T1-weighted MRI data. At the global level, we investigated the influence of age and gender on brain volumes using a two-way analysis of variance. With respect to gender, we used the Pearson correlation to investigate global brain volume alterations due to age in the older and young groups. At the regional level, we used a flexible factorial statistical test to compare the means of gray matter (GM) and white matter (WM) volume alterations among the four groups. We observed different patterns in both the global and regional GM and WM alterations in the young and older groups with respect to gender. At the global level, we observed significant influences of age and gender on global brain volumes. At the regional level, the older subjects showed a widespread reduction in GM volume in regions of the frontal, insular, and cingulate cortices compared to the young subjects in both genders. Compared to the young subjects, the older subjects showed a widespread WM decline prominently in the thalamic radiations, in addition to increased WM in pericentral and occipital areas. Knowledge of these observed brain volume differences and changes may contribute to the elucidation of mechanisms underlying aging as well as age-related brain atrophy and disease.

Percutaneous thermal ablation has been widely used as a minimally invasive treatment for tumors. Treatment monitoring is essential for preventing complications while ensuring treatment efficacy. Mechanical testing measurements on tissue reveal that tissue stiffness increases with temperature and ablation duration. Different types of imaging methods can be used to monitor ablation procedures, including temperature or thermal strain imaging, strain imaging, modulus imaging, and shear modulus imaging. Ultrasound elastography demonstrates the potential to become the primary imaging modality for monitoring percutaneous ablation. This review briefly presented the state-of-the-art ultrasound elastography approaches for monitoring radiofrequency ablation and microwave ablation. These techniques were divided into four groups: quasi-static elastography, acoustic radiation force elastography, sonoelastography, and applicator motion elastography. Their advantages and limitations were compared and discussed. Future developments were proposed with respect to heat-induced bubbles, tissue inhomogeneities, respiratory motion, three-dimensional monitoring, multi-parametric monitoring, real-time monitoring, experimental data center for percutaneous ablation, and microwave ablation monitoring.

The in vitro and in vivo experiments were conducted to evaluate antifungal activity of crude extracts derived from neem (Azadirachta indica) leaves and ginger (Zingiber officinale) rhizomes against three isolates of Sclerotinia sclerotiorum, the causal agent of storage carrot (Daucus carota) rot. Ethyl acetate (EA) and ethanol were used as different solvents. Although plant extracts significantly reduced the mycelial growth of three isolates at volatile phase, highest inhibitory efficacy was observed at contact phase. Furthermore, all crude extracts were able to reduce carpogenic germination of sclerotia at concentrations 2 g/l. The isolate 2 was found to be more inhibited in in vitro tests. At volatile phase, EA and ethanol extracts of ginger meaningfully reduced myceliogenic germination of sclerotia in three isolates. However, all plant extracts decreased the myceliogenic germination of sclerotia at contact phase at the concentration 10 g/l. The results of in vivo tests showed that all plant extracts are able to decrease disease severity of carrot rot at the concentration 2 g/l. In addition, the enzymatic analyses of phenylalanine ammonia layse, polyphenoloxidase and peroxidase in inoculated carrots after application of plant crude extracts indicated that neem extracts can be considered as resistance inducers against Sclerotinia carrot rot.

With the development of nerve stereotactic technology, brain stereotactic surgery has become an effective method for the current treatment of Parkinson's disease. The accurate localization of the target nuclei is the key issue of the treatment. In this paper, we constructed a dependence tree model to identify the target nuclei further. Theory of fuzzy connectedness was used in the segmentation. Experimental results show it was more desirable and suitable to the clinical applications.

Fundus abnormalities were usually diagnosed by clinical ophthalmologists using the equipment like ophthalmoscope, which was influenced by complex method, subjective fault and low efficiency. Fortunately, fundus can be shown in the key structures of the fundus digital image. Hence, it is necessary to develop a computer-aided fundus image processing system as a tool to assist in the diagnosis diseases. Algorithms were proposed including the pre-processing such as contrast enhancement and spatial filtering, binaryzation, morphology, boundary extraction and skeleton extraction. This paper preliminary summarized the key technologies of segmentation on the structures of optic cup, optic disc and blood vessel. Experiments were performed in MATLAB. Automatic algorithms were evaluated to be able to detect the key structures of the fundus digital image. It is expected to be applied in computer-aided fundus image processing system.

BACKGROUND AND PURPOSE Small animal neuroimaging using magnetic resonance microscopy (MRM) has evolved significantly from understanding of imaging physics to widely use today as an important tool in computational neuroanatomy, while how to get optimal inhomogeneity correction for inhomogeneous mouse brain MRM has been given less attention. METHODS This present study investigates the ability of fine-tuning the nonparametric nonuniform intensity normalization (N3) technique to get optimal inhomogeneity correction of mouse brain MRM. Six mice were scanned on a 7-T scanner with a phased array surface coil of four elements. The N3 parameters such as stopping criteria, maximum iterations, down-sampling ratio, full width at half maximum, spline distance, and brain mask have been tuned to get optimal correction result. We used coefficient of variation of the white matter and joint variation to ascertain quantitatively the correction. The data were analyzed by two-way repeated measures analysis of variance and Bonferroni post hoc test. RESULTS The quantitative outcomes show that brain mask and spline distance have a significant influence on correcting performance. CONCLUSIONS The present study demonstrates the benefit of reducing the spline distance values to 25 and tighter mask. The finding can help researches to enhance precision in studies where mouse MRM need further registration or segmentation.

Root colonization by Bacillus amyloliquefaciens is directly related to bacterial growth, chemotaxis, biofilm formation, and the interaction with host plant root exudates. In this study, root exudates were collected from two tomato plant varieties that supported bacterial cell division and induced the B. amyloliquefaciens T-5 chemotactic response, even at the concentration of 10 μg ml−1. Root exudates also induced biofilm formation, but lower than control treatment. In addition, five organic acids were identified in the root exudates and subsequently evaluated. Malic acid, citric acid, succinic acid and fumaric acid significantly induced the chemotaxis response and swarming motility. Maximal chemotactic response and swarming motility were induced by malic acid, and all the organic acid did not have a significant effect on biofilm formation. Furthermore, these organic acids promoted the B. amyloliquefaciens T-5 recruitment under gnotobiotic conditions, increasing the rhizosphere bacterial population. This data suggested that tomato root colonization by B. amyloliquefaciens T-5 was influenced by organic acids secreted by roots. This study expands our understanding of B. amyloliquefaciens T-5 colonization on tomato roots under natural conditions and reflects the significance of B. amyloliquefaciens T-5 strain as biocontrol agent which will be useful for preparing formulations for the better control of plant wilt diseases.

To explore the diagnostic value of combined detection of plasma miR-127-3p and HE4 for breast cancer (BC).Included in this study were 102 patients with pathologically confirmed BC who received treatment in the affiliated hospital of Nantong University between March 2015 and April 2016, 87 patients with benign breast tumors, and 90 healthy volunteers as control. Plasma miR-127-3p was detected by SYBR Green RT-qPCR, and plasma HE4 was detected by chemiluminescent immunoassay. The diagnostic efficacy of miR-127-3p alone, HE4 alone and combined detection of miR-127-3p and HE4 in BC women patients was evaluated by ROC curve analysis.The relative expression quantity (RQ) of plasma miR-127-3p and HE4 in BC patients was 13.561 (3.345∼18.281) pmol/L and 105.42 (40.28∼156.31) pmol/L. The RQ of plasma miR-127-3p in BC patients was significantly higher than that in benign breast tumor patients and healthy individuals (both P0.001), and there was no significant difference between benign breast tumor patients and healthy individuals (P0.05). There was no significant correlation between plasma miR-127-3p and HE4 levels (r2= 0.086, P= 0.471). ROC curve analysis on the diagnostic efficacy of plasma miR-127-3p and HE4 in BC diagnosis showed that the cut-off value of miR-127-3p and HE4 in BC diagnosis was 3.471 and 63.21 pmol/L; AUC was 0.767 and 0.670; sensitivity was 78.2% and 64.6%; specificity was 79.1% and 69.3%; accuracy was 73.2% and 65.1%, respectively. Prediction probability (P) obtained from the miR-127-3p and HE4 model established by logistic regression was P= 1/ [1 + exp (-0.142miR-127-3p-0.024HE4 + 2.875)]. AUC calculated from ROC was 0.825 and the sensitivity was increased to 87.4%.Combined detection of plasma miR-127-3p and HE4 greatly improved the sensitivity of BC diagnosis and may prove to be a candidate biomarker for early detection and diagnosis of BC.