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Abstract Background Understanding the genetic control of pod shatter resistance and its association with pod length is crucial for breeding improved pod shatter resistance and reducing pre-harvest yield losses due to extensive shattering in cultivars of Brassica species. In this study, we evaluated a doubled haploid (DH) mapping population derived from an F1 cross between two Brassica carinata parental lines Y-BcDH64 and W-BcDH76 (YWDH), originating from Ethiopia and determined genetic bases of variation in pod length and pod shatter resistance, measured as rupture energy. The YWDH population, its parental lines and 11 controls were grown across three years for genetic analysis. Results By using three quantitative trait loci (QTL) analytic approaches, we identified nine genomic regions on B02, B03, B04, B06, B07 and C01 chromosomes for rupture energy that were repeatedly detected across three growing environments. One of the QTL on chromosome B07, flanked with DArTseq markers 100,046,735 and 100,022,658, accounted for up to 27.6% of genetic variance in rupture energy. We observed no relationship between pod length and rupture energy, suggesting that pod length does not contribute to variation in pod shatter resistance. Comparative mapping identified six candidate genes; SHP1 on B6, FUL and MAN on chromosomes B07, IND and NST2 on B08, and MAN7 on C07 that mapped within 0.2 Mb from the QTL for rupture energy. Conclusion The results suggest that favourable alleles of stable QTL on B06, B07, B08 and C01 for pod shatter resistance can be incorporated into the shatter-prone B. carinata and its related species to improve final seed yield at harvest.

Abstract Aims/Introduction Diabetic cardiomyopathy (DCM) is a prevalent condition among individuals with diabetes, and is associated with a high mortality rate. The anti‐oxidant properties of Jing Huang or Polygonatum sibiricum polysaccharide (PSP) have been extensively used to treat diabetes‐related disorders; however, its potential effectiveness against DCM remains unknown. This study aimed to investigate PSP's therapeutic effects on DCM in an experimental diabetic mouse model. Materials and Methods To induce insulin resistance, mice were fed a high‐fat diet for 3 months, followed by intraperitoneal streptozotocin injection to induce slight hyperglycemia and develop DCM. Both DCM and control mice were given PSP orally for 3 weeks. Western blotting was used to detect the protein expressions of protein kinase G, C/EBP homologous protein, glucose‐regulated protein 78, phosphodiesterase type 5, protein kinase R‐like endoplasmic reticulum (ER) kinase, and phospho‐protein kinase R‐like endoplasmic reticulum kinase in heart tissue. Results The results showed a reduction in bodyweight and blood glucose levels in the PSP therapy group compared with DCM group. PSP also improved cardiac function and had a negligible effect on malondialdehyde activity. Furthermore, the findings showed that PSP alleviated ER and oxidative stress observed in DCM mice hearts, leading to the inhibition of cyclic guanosine monophosphate‐specific phosphodiesterase type 5 and cardiac cyclic guanosine monophosphate reactivation. Phosphodiesterase type 5 inhibition reduced high‐fat diet‐induced cardiac dysfunction and decreased ER stress. Conclusions PSP could effectively protect diabetic myocardium by inhibiting endoplasmic reticulum stress. These findings provide crucial insights into the potential of PSP to ameliorate DCM conditions in diabetic mice by decreasing ER and oxidative stress, and enhancing cyclic guanosine monophosphate protein kinase G signaling.

Abstract The prevalence of low-dose CT (LDCT) in lung cancer screening has gradually increased, and more and more lung ground glass nodules (GGNs) have been detected. So far, a consensus has been reached on the treatment of single pulmonary ground glass nodules, and there have been many guidelines that can be widely accepted. However, at present, more than half of the patients have more than one nodule when pulmonary ground glass nodules are found, which means that different treatment methods for nodules may have different effects on the prognosis or quality of life of patients. This article reviews the research progress in the diagnosis and treatment strategies of pulmonary multiple lesions manifested as GGNs.

Wear is the key issue hindering the further application of titanium alloy. The aim of this work was to explore the strengthening mechanisms for the wear properties of Ti–15Mo alloys via laser powder bed fusion (LPBF) by the La2O3 addition. The results showed that the grain of LPBF-fabricated Ti–15Mo/La2O3 composites was obviously refined after La2O3 addition by heterogeneous nucleation and inhibited grain growth. The average grain size of Ti–15Mo/(0.2 wt%, 0.4 wt%, 0.6 wt% and 0.8 wt%) La2O3 composites is 11.75 μm, 10.85 μm, 10.39 μm, and 9.99 μm, respectively. The wear rate of Ti–15Mo/(0.2 wt% - 0.8 wt%) La2O3 composites is 1.5916 × 10−4mm3N−1m−1, 1.2885 × 10−4mm3N−1m−1, 0.6821 × 10−4mm3N−1m−1 and 0.6063 × 10−4mm3N−1m−1, respectively. Thanks to the combined effect of fine grain strengthening, grain boundary strengthening, precipitation strengthening, dispersion strengthening and dislocation strengthening, the wear resistance of the obtained sample exceeds that of the LPBF-fabricated Ti–15Mo sample more than five times and that of the LPBF-fabricated CP-Ti sample more than ten times.

ObjectiveHow to conduct objective and accurate individualized assessments of patients with disorders of consciousness (DOC) and carry out precision rehabilitation treatment technology is a major rehabilitation problem that needs to be solved urgently.MethodsIn this study, a multi-layer brain network was constructed based on functional magnetic resonance imaging (fMRI) to analyze the structural and functional brain networks of patients with DOC at different levels and to find regulatory targets (imaging markers) with recovery potential for DOC. Then repeated transcranial magnetic stimulation (rTMS) was performed in DOC patients to clinically validate.ResultsThe brain network connectivity of DOC patients with different consciousness states is different, and the most obvious brain regions appeared in the olfactory cortex and precuneus. rTMS stimulation could effectively improve the consciousness level of DOC patients and stimulate the occipital lobe (specific regions found in this study) and the dorsolateral prefrontal cortex (DLPFC), and both parts had a good consciousness recovery effect.ConclusionIn clinical work, personalized stimulation regimen treatment combined with the brain network characteristics of DOC patients can improve the treatment effect.

“Synthetic” allopolyploids recreated by interspecific hybridization play an important role in providing novel genomic variation for crop improvement. Such synthetic allopolyploids often undergo rapid genomic structural variation (SV). However, how such SV arises, is inherited and fixed, and how it affects important traits, has rarely been comprehensively and quantitively studied in advanced generation synthetic lines. A better understanding of these processes will aid breeders in knowing how to best utilize synthetic allopolyploids in breeding programs. Here, we analyzed three genetic mapping populations (735 DH lines) derived from crosses between advanced synthetic and conventional Brassica napus (rapeseed) lines, using whole-genome sequencing to determine genome composition. We observed high tolerance of large structural variants, particularly toward the telomeres, and preferential selection for balanced homoeologous exchanges (duplication/deletion events between the A and C genomes resulting in retention of gene/chromosome dosage between homoeologous chromosome pairs), including stable events involving whole chromosomes (“pseudoeuploidy”). Given the experimental design (all three populations shared a common parent), we were able to observe that parental SV was regularly inherited, showed genetic hitchhiking effects on segregation, and was one of the major factors inducing adjacent novel and larger SV. Surprisingly, novel SV occurred at low frequencies with no significant impacts on observed fertility and yield-related traits in the advanced generation synthetic lines. However, incorporating genome-wide SV in linkage mapping explained significantly more genetic variance for traits. Our results provide a framework for detecting and understanding the occurrence and inheritance of genomic SV in breeding programs, and support the use of synthetic parents as an important source of novel trait variation.

The variability in the propagation pathway in epilepsy is a main factor contributing to surgical treatment failure. Ways to accurately capture the brain propagation network and quantitatively assess its evolution remain poorly described. This work aims to develop a dynamic step effective network (dSTE) to obtain the propagation path network of multiple seizures in the same patient and explore the degree of dissimilarity. Multichannel stereo-electroencephalography (sEEG) signals were acquired with ictal processes involving continuous changes in information propagation. We utilized high-order dynamic brain networks to obtain propagation networks through different levels of linking steps. We proposed a dissimilarity index based on singular value decomposition to quantitatively compare seizure pathways. Simulated data were generated through The Virtual Brain, and the reliability of this method was verified through ablation experiments. By applying the proposed method to two datasets consisting of 29 patients total, the evolution processes of each patient’s seizure networks was obtained, and the within-patient dissimilarities were quantitatively compared. Finally, three types of brain network connectivity patterns were found. Type I patients have a good prognosis, while type III patients are prone to postoperative recurrence. This method captures the evolution of seizure propagation networks and assesses their dissimilarity more reliably than existing methods, demonstrating good robustness for studying the propagation path differences for multiple seizures in epilepsy patients. The three different patterns will be important considerations when planning epilepsy surgery under sEEG guidance.

AbstractContext Hawthorn leaves are a kind of widely used medicinal plant in China. The major ingredient, hawthorn leaves flavonoids (HLF), have cardiotonic, cardioprotective, and vascular protective effects.Objective The study evaluated the protective role of HLF in cardiac remodelling and the underlying mechanisms under simulated microgravity by hindlimb unloading rats.Materials and methods Adult male Sprague-Dawley rats were divided into control, HLF, HU (hindlimb unloading) and HU + HLF groups (n = 8). After HU and daily intragastric administration at the dose of 100 mg/kg/d for 8 weeks, cardiac function and structure were evaluated by biochemical indices and histopathology. We identified the main active compounds and mechanisms involved in the cardioprotective effects of HLF via bioinformatics and molecular docking analysis, and relative signalling pathway activity was verified by Western blot.Results HLF treatment could reverse the HU-induced decline in LV-EF (HU, 55.13% ± 0.98% vs. HU + HLF, 71.16% ± 5.08%), LV-FS (HU, 29.44% ± 0.67% vs. HU + HLF, 41.62% ± 4.34%) and LV mass (HU, 667.99 ± 65.69 mg vs. HU + HLF, 840.02 ± 73.00 mg). Furthermore, HLF treatment significantly increased NPRA expression by 135.39%, PKG by 51.27%, decreased PDE5A by 20.03%, NFATc1 by 41.68% and Rcan1.4 by 54.22%.Conclusions HLF plays a protective effect on HU-induced cardiac remodelling by enhancing NPRA-cGMP-PKG pathway and suppressing the calcineurin-NFAT pathway, which provides a theoretical basis for use in clinical therapies.

The bionic-inspired Ti–15Mo gradient porous structures were fabricated by selective laser melting (SLM) for the first time in this work. The compression-compression fatigue behavior of functional gradient Ti–15Mo porous structures is investigated, with emphasis on understanding the relationship between fatigue performance and microstructure. The microstructure of the samples was analyzed both before and after fatigue, and correlated with the fatigue performance. During cyclic deformation, the pillars exhibited a non-uniform local stress distribution, primarily attributed to the disparity of gradient density distribution. Fatigue cracks typically initiate at the place with the defects and subsequently propagate until structural damage occurs. Fatigue ratcheting effect occurs throughout the entire fatigue process while the fatigue damage typically initiates at a later stage in the fatigue process. The results indicated that the fatigue performance of the lateral gradient (LG) structure was superior to that of the homogeneous structure, while the vertical gradient (VG) structure exhibited the poorest fatigue performance.

Drug-resistant epilepsy is frequent, persistent, and brings a heavy economic burden to patients and their families. Traditional epilepsy detection methods ignore the causal relationship of seizures and focus on a single time or spatial dimension, and the effect varies greatly in different patients. Therefore, it is necessary to research accurate automatic detection technology of epilepsy in different patients. We propose a causal-spatio-temporal graph attention network (CSTGAT), which uses transfer entropy (TE) to construct a causal graph between multiple channels, combining graph attention network (GAT) and bi-directional long short-term memory (BiLSTM) to capture temporal dynamic correlation and spatial topological structure information. The accuracy, specificity, and sensitivity of the SWEZ dataset were 97.24%, 97.92%, and 98.11%. The accuracy of the private dataset reached 98.55%. The effectiveness of each module was proven through ablation experiments and the impact of different network construction methods was compared. The experimental results indicate that the causal relationship network constructed by TE could accurately capture the information flow of epileptic seizures, and GAT and BiLSTM could capture spatiotemporal dynamic correlations. This model accurately captures causal relationships and spatiotemporal correlations on two datasets, and it overcomes the variability of epileptic seizures in different patients, which may contribute to clinical surgical planning.

Multivariate entropy algorithms have proven effective in the complexity dynamic analysis of electroencephalography (EEG) signals, with researchers commonly configuring the variables as multi-channel time series. However, the complex quantification of brain dynamics from a multi-frequency perspective has not been extensively explored, despite existing evidence suggesting interactions among brain rhythms at different frequencies. In this study, we proposed a novel algorithm, termed multi-frequency entropy (mFreEn), enhancing the capabilities of existing multivariate entropy algorithms and facilitating the complexity study of interactions among brain rhythms of different frequency bands. Firstly, utilizing simulated data, we evaluated the mFreEn’s sensitivity to various noise signals, frequencies, and amplitudes, investigated the effects of parameters such as the embedding dimension and data length, and analyzed its anti-noise performance. The results indicated that mFreEn demonstrated enhanced sensitivity and reduced parameter dependence compared to traditional multivariate entropy algorithms. Subsequently, the mFreEn algorithm was applied to the analysis of real EEG data. We found that mFreEn exhibited a good diagnostic performance in analyzing resting-state EEG data from various brain disorders. Furthermore, mFreEn showed a good classification performance for EEG activity induced by diverse task stimuli. Consequently, mFreEn provides another important perspective to quantify complex dynamics.

Brain networks based on functional magnetic resonance imaging (fMRI) provide a crucial perspective for diagnosing brain diseases. Representation learning has recently attracted tremendous attention due to its strong representation capability, which can be naturally applied to brain disease analysis. However, traditional representation learning only considers direct and local node interactions in original brain networks, posing challenges in constructing higher-order brain networks to represent indirect and extensive node interactions. To address this problem, we propose the Continuous Dictionary of Nodes model and Bilinear-Diffusion (CDON-BD) network for brain disease analysis. The CDON model is innovatively used to learn the original brain network, with its encoder weights directly regarded as latent features. To fully integrate latent features, we further utilize Bilinear Pooling to construct higher-order brain networks. The Diffusion Module is designed to capture extensive node interactions in higher-order brain networks. Compared to state-of-the-art methods, CDON-BD demonstrates competitive classification performance on two real datasets. Moreover, the higher-order representations learned by our method reveal brain regions relevant to the diseases, contributing to a better understanding of the pathology of brain diseases.

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) presents a high rate of postoperative recurrence, but its recurrent mechanisms are not fully clarified. In this study, we aim to explore biomarkers associated with the recurrence of CRSwNP and shed light on the underlying recurrent mechanisms using serum proteomics. Methods: A prospective cohort of CRSwNP patients was conducted, and serum samples were subjected to proteomic profiling. Participants were followed up for 2 years and divided into non-Recurrence and Recurrence groups and differentially expressed proteins (DEPs) were compared. The top 3 DEPs were validated in the serum and tissue samples in a validation cohort, and their predictive values for recurrence and their associations with macrophages were evaluated. In vitro, circulating macrophages were utilized to explore the influence of candidate proteins on macrophage polarization in underlying recurrent mechanisms of CRSwNP. Results: Sixteen CRSwNP patients completed the follow-up schedule, including 10 patients in the non-Recurrence group and 6 patients in the Recurrence group. Serum proteomics revealed a distinctive protein expression profile between the 2 groups. A validation cohort comprising 51 non-recurrent and 24 recurrent CRSwNP patients was recruited. Enzyme-linked immunosorbent assay (ELISA) results revealed that circulating levels of CSF1R and CDC42 were significantly higher, and DHRS9 levels were lower in the Recurrence group in comparison with the non-Recurrence group. In addition, tissue CSF1R and CDC42 were identified to be enhanced in the Recurrence group compared to the non-Recurrence group. Receiver-operated characteristic (ROC) curves and Kaplan-Meier survival analysis suggest that both serum and tissue CSF1R were associated with the risk of postoperative recurrence. Tissue immunofluorescence (IF) revealed that CSF1R was enhanced in the tissues of patients with recurrence, especially in the mesenchymal region. Multiplex IF highlighted that CSF1R was significantly co-expressed with M2 macrophage markers. In vitro experiments confirmed that CSF1R overexpression promoted macrophage M2 polarization and cytokine production. Conclusion: Serum proteomic signatures may affect postoperative recurrence in CRSwNP patients. CSF1R is a potential biomarker for predicting CRSwNP recurrence. Mechanistically, the recurrence of CRSwNP appears to involve the CSF1R-driven M2 polarization process.

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

Our recent study showed that Nitazoxanide (NTZ), an FDA-approved anti-parasitic drug, prevents ovariectomy-induced bone loss by inhibiting osteoclast activity. However, there have been no investigations to determine whether NTZ has preventive potential in other bone resorbing diseases, especially rheumatoid arthritis (RA). In this study, the primary RA fibroblast-like synoviocytes (RA-FLS) and collagen-induced arthritis (CIA) murine model were used to evaluate the effect of NTZ. The results showed that NTZ potently inhibited proliferation, migration and invasion capacity of RA-FLS in a dose dependent manner by restraining cell entry into S phases, without induction of cell apoptosis. NTZ obviously reduced spontaneous mRNA expression of IL-1β, IL-6 and RANKL, as well as TNF-α-induced transcription of the IL-1β, IL-6, and MMP9 genes. In terms of molecular mechanism, NTZ significantly inhibited the basal or TNF-α-induced activation of JAK2/STAT3 (T705) and NF-κB pathway, but not MAPK and STAT3 (S727) phosphorylation. Moreover, NTZ ameliorated synovial inflammation and bone erosion in CIA mice through reducing the production of inflammatory mediators and osteoclast formation, respectively. Collectively, our findings indicate that NTZ exhibits anti-inflammatory and anti-erosive effects both ex vivo and in vivo, which provides promising evidence for the therapeutic application of NTZ as a novel therapeutic agent for RA.

The microstructure evolution of near β-Ti alloys with initially lamellar and equiaxed microstructures subjected to dynamic loading was investigated. Results showed that during high strain rate compression, shear failure is more likely to occur in equiaxed microstructure. Owing to temperature rise and stress concentration, the lamellar α phase in adiabatic shear band (ASB) zone was recrystallized and re-melted, while the equiaxed α phase transformed in strip-shaped following the propagating direction of adiabatic shear band. During high strain rate loading, the twinning transfer was observed between β matrix and α phase, which demonstrates that twinning is the dominant deformation mode to accommodate plastic deformation.

Abstract Background The in vitro stability assessment is essential for investigating the diagnostic accuracy of pleural biomarkers. This study aimed to investigate the long‐term stability of pleural fluid carcinoembryonic antigen (CEA) at −80°C to −70°C. In addition, we analyzed the effects of frozen storage on the diagnostic accuracy of CEA for malignant pleural effusion (MPE). Methods Pleural fluid CEA of participants in two prospective cohorts were stored at −80°C to −70°C for 1–3 years. The CEA level in the stored specimen was measured with an immunoassay, and its level in the fresh specimen was extracted from medical records. The Bland–Altman method, Passing‐Bablok regression, and Deming regression were used to analyze the agreement of CEA between the fresh and frozen pleural fluid. In addition, we used receiver operating characteristic (ROC) curves to evaluate the diagnostic accuracy of CEA in the fresh and frozen specimens for MPE. Results A total of 210 participants were enrolled. The median CEA levels in frozen and fresh pleural fluid specimens were similar (frozen, 2.32 ng/mL; fresh, 2.59 ng/mL; p 0.05 for all). No significant difference was observed between the area under the ROC curves of CEA in the fresh and frozen specimens (p > 0.05 for all). Conclusion Pleural fluid CEA is seemingly stable when stored at –80°C to −70°C for 1–3 years. Frozen storage does not significantly affect the diagnostic accuracy of CEA for MPE.

Background: Lung cancer is the most common cause of malignant pleural effusion (MPE). Serum human epididymis secretory protein 4 (HE4) is a useful diagnostic marker for lung cancer. Objective: This study aimed to evaluate the diagnostic accuracy of pleural fluid HE4 for MPE. Design: A prospective, double-blind diagnostic test accuracy study. Methods: Patients with undiagnosed pleural effusion were enrolled in two cohorts (Hohhot and Changshu). Electrochemiluminescence immunoassay was used to detect pleural fluid HE4. The diagnostic accuracy of HE4 was evaluated by a receiver operating characteristic (ROC) curve, and the net benefit of HE4 was assessed by a decision curve analysis (DCA). Results: A total of 66 MPEs and 86 benign pleural effusions (BPEs) were enrolled in the Hohhot cohort. In the Changshu cohort, 26 MPEs and 32 BPEs were enrolled. In both cohorts, MPEs had significantly higher pleural fluid HE4 than BPEs. The area under the ROC curve (AUC) of HE4 was 0.73 (95% CI: 0.64–0.81) in the Hohhot cohort and 0.79 (95% CI: 0.67–0.91) in the Changshu cohort. At a threshold of 1300 pmol/L, HE4 had sensitivities of 0.44 (95% CI: 0.33–0.56) in the Hohhot cohort and 0.54 (95% CI: 0.35–0.73) in the Changshu cohort. The corresponding specificities were 0.90 (95% CI: 0.83–0.95) in the Hohhot cohort and 0.94 (95% CI: 0.84–1.00) in the Changshu cohort. In subgroup analyses, HE4 had an AUC (95% CI) of 0.78 (0.71–0.85) in exudates and an AUC of 0.69 (0.57–0.81) in patients with negative effusion cytology. The DCA revealed that HE4 determination had a net benefit in both cohorts. Conclusion: Pleural fluid HE4 has moderate diagnostic accuracy for MPE and has net benefit in pleural effusion patients with unknown etiology.

Abstract High sensitivity and fast response are the figures of merit for benchmarking commercial sensors. Due to the advantages of intrinsic signal amplification, bionic ability, and mechanical flexibility, electrochemical transistors (ECTs) have recently gained increasing popularity in constructing various sensors. In the current work, we have proposed a pulse‐driven synaptic ECT for supersensitive and ultrafast biosensors. By pulsing the presynaptic input (drain bias, VD) and setting the modulation potential (gate bias) near transconductance intersection (VG,i), the synaptic ECT‐based pH sensor can achieve a record high sensitivity up to 124 mV pH−1 (almost twice the Nernstian limit, 59.2 mV pH−1) and an ultrafast response time as low as 8.75 ms (7169 times faster than the potentiostatic sensors, 62.73 s). The proposed synaptic sensing strategy can effectively eliminate the transconductance fluctuation issue during the calibration process of the pH sensor and significantly reduce power consumption. Besides, the most sensitive working point at VG,i has been elaborately figured out through a series of detailed mathematical derivations, which is of great significance to provide higher sensitivity with quasi‐nonfluctuating amplification capability. The proposed electrochemical synaptic transistor paired with an optimized operating gate offers a new paradigm for standardizing and commercializing high‐performance biosensors.

Abstract Background Recently, despite the steady decline in the tuberculosis (TB) epidemic globally, school TB outbreaks have been frequently reported in China. This study aimed to quantify the transmissibility of Mycobacterium tuberculosis (MTB) among students and non-students using a mathematical model to determine characteristics of TB transmission. Methods We constructed a dataset of reported TB cases from four regions (Jilin Province, Xiamen City, Chuxiong Prefecture, and Wuhan City) in China from 2005 to 2019. We classified the population and the reported cases under student and non-student groups, and developed two mathematical models [nonseasonal model (Model A) and seasonal model (Model B)] based on the natural history and transmission features of TB. The effective reproduction number (R eff ) of TB between groups were calculated using the collected data. Results During the study period, data on 456,423 TB cases were collected from four regions: students accounted for 6.1% of cases. The goodness-of-fit analysis showed that Model A had a better fitting effect (P

Diabetic nephropathy (DN) is a severe microvascular complication of diabetes, which increases the risk of renal failure and causes a high global disease burden. Due to the lack of sustainable treatment, DN has become the primary cause of end-stage renal disease worldwide. Gut microbiota and its metabolites exert critical regulatory functions in maintaining host health and are associated with many pathogenesis of aging-related chronic diseases. Currently, the theory gut–kidney axis has opened a novel angle to understand the relationship between gut microbiota and multiple kidney diseases. In recent years, accumulating evidence has revealed that the gut microbiota and their metabolites play an essential role in the pathophysiologic processes of DN through the gut–kidney axis. In this review, we summarize the current investigations of gut microbiota and microbial metabolites involvement in the progression of DN, and further discuss the potential gut microbiota-targeted therapeutic approaches for DN.

Quinoa saponins are pentacyclic triterpene compounds composed of one triterpenoid glycoside and two different sugar chains. Previous studies have showed that natural quinoa saponins showed little or no antifungal activity, and there are few reports about their antifungal effects in recent decades. Fusarium wilt caused by Fusarium oxysporum f. sp. lycopersici (FOL) is the most serious for tomatoes in the field and under greenhouse conditions. The main objective of this study was to investigate the effectiveness of different concentrations and application modes of crude saponins from quinoa bran against the causal pathogen of tomato wilt under a greenhouse experiment. The results showed that the anti-FOL activity of quinoa saponins was weak in vitro, but significantly enhanced in vivo. Tomato seeds and seedlings treated with solution of quinoa saponins at 0.5 and 1.0 g/L significantly reduced the disease incidence (%) of tomato Fusarium wilt. The treatment types of saponin solution have influence on the preventive effects (%) of tomato seedlings against Fusarium wilt, among them, root soaking > foliar spray > seed soaking. The treatment of seed soaking with quinoa saponins inhibited germination of tomato seeds to some extent. However, the germination rate of tomato seeds after saponin soaking was comparable to the chemical pesticide (thiram carboxin); therefore, it could be used to control tomato wilt disease. This is due to the fact that the antifungal activity of quinoa saponins in vivo was much higher than that in vitro when the saponin concentration was between 0.5–1.0 g/L, indicating that the antifungal activity of quinoa saponins may be achieved mainly by inducing resistance. This investigation supports the potential use of quinoa saponins as a supplier of antifungal compounds, and could be the foundation for a future study examining the use of quinoa bran as a new resource against FOL.

Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain’s functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.

An ocean of studies have pointed to abnormal brain laterality changes in patients with bipolar disorder (BD). Determining the altered brain lateralization will help us to explore the pathogenesis of BD. Our study will fill the gap in the study of the dynamic changes of brain laterality in BD patients and thus provide new insights into BD research. In this work, we used fMRI data from 48 BD patients and 48 normal controls (NC). We constructed the dynamic laterality time series by extracting the dynamic laterality index (DLI) at each sliding window. We then used k-means clustering to partition the laterality states and the Arenas–Fernandez–Gomez (AFG) community detection algorithm to determine the number of states. We characterized subjects’ laterality characteristics using the mean laterality index (MLI) and laterality fluctuation (LF). Compared with NC, in all windows and state 1, BD patients showed higher MLI in the attention network (AN) of the right hemisphere, and AN in the left hemisphere showed more frequent laterality fluctuations. AN in the left hemisphere of BD patients showed higher MLI in all windows and state 3 compared to NC. In addition, in the AN of the right hemisphere in state 1, higher MLI in BD patients was significantly associated with patient symptoms. Our study provides new insights into the understanding of BD neuropathology in terms of brain dynamic laterality.

Identification of plant species and variety has important application value in the process of agricultural production. In this work, we try to use electrochemical fingerprinting technology to collect the electrochemical behavior of electrochemically active substances in plant leaf tissues. Twenty Lycium species and varieties were specifically selected to investigate the recognition ability of electrochemical fingerprinting. Two different extraction solvents and electrolytes were used to create different collection environments. The results show that different Lycium spp. can exhibit different electrochemical fingerprints. Different species of the same species exhibit relatively similar electrochemical fingerprints. After the second derivative processing, the electrochemical fingerprint of plants can be used for classification and recognition by different machine learning models. Partial least squares discriminant analysis (PLS-DA), k-nearest neighbor, (KNN), support vector machine (SVM), random forest (RF) and stochastic gradient boosting (SGB) were used to establish recognition model of Lycium spp. The results show that SGB has the best identification accuracy for electrochemical fingerprint after second derivative treatment.

Abstract Hand, foot, and mouth disease (HFMD) is a serious disease burden in the Asia–Pacific region, including China. This study calculated the transmissibility of HFMD at county levels in Jiangsu Province, China, analyzed the differences of transmissibility and explored the possible influencing factors of its transmissibility. We built a mathematical model for seasonal characteristics of HFMD, estimated the effective reproduction number (R eff ), and compared the incidence rate and transmissibility in different counties using non-parametric tests, rapid cluster analysis and rank-sum ratio in 97 counties in Jiangsu Province from 2015 to 2020. The average daily incidence rate was between 0 and 4 per 100,000 people in Jiangsu Province from 2015–2020. The Quartile of R eff in Jiangsu Province from 2015 to 2020 was 1.54 (0.49, 2.50). Rugao District and Jianhu District had the highest transmissibility according to the rank-sum ratio. R eff generally decreased in 2017 and increased in 2018 in most counties, and the median level of R eff was the lowest in 2017 (P

Abstract Physiological monitoring can provide detailed information about health conditions, and therefore presents great potentials for personalized healthcare. Flexible miniaturized sensors (FMS) for physiological monitoring have garnered significant attention because of their wide applications in collecting health-related information, evaluating and managing the state of human wellness in long term. In this review, we focus on the time scale of human physiological monitoring, the needs and advances in miniaturized technologies for long-term monitoring in typical applications. We also discuss the rational sample sources of FMS to select proper strategies for specific monitoring cases. Further, existing challenges and promising prospects are also presented.

Importance: Drug-likeness of a compound is an overall assessment of its potential to succeed in clinical trials, and is essential for economizing research expenditures by filtering compounds with unfavorable properties and poor development potential. To this end, a robust drug-likeness prediction method is indispensable. Various approaches, including discriminative rules, statistical models, and machine learning models, have been developed to predict drug-likeness based on physiochemical properties and structural features. Notably, recent advancements in novel deep learning techniques have significantly advanced drug-likeness prediction, especially in classification performance. Highlights: In this review, we addressed the evolving landscape of drug-likeness prediction, with emphasis on methods employing novel deep learning techniques, and highlighted the current challenges in drug-likeness prediction, specifically regarding the aspects of generalization and interpretability. Moreover, we explored potential remedies and outlined promising avenues for future research. Conclusion: Despite the hurdles of generalization and interpretability, novel deep learning techniques have great potential in drug-likeness prediction and are worthy of further research efforts.

Abstract Background Reaching optimal vaccination rates is an essential public health strategy to control the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to simulate the optimal vaccination strategy to control the disease by developing an age-specific model based on the current transmission patterns of COVID-19 in Wuhan City, China. Methods We collected two indicators of COVID-19, including illness onset data and age of confirmed case in Wuhan City, from December 2, 2019, to March 16, 2020. The reported cases were divided into four age groups: group 1, ≤ 14 years old; group 2, 15 to 44 years old; group 3, 44 to 64 years old; and group 4, ≥ 65 years old. An age-specific susceptible-exposed-symptomatic-asymptomatic-recovered/removed model was developed to estimate the transmissibility and simulate the optimal vaccination strategy. The effective reproduction number (R eff) was used to estimate the transmission interaction in different age groups. Results A total of 47 722 new cases were reported in Wuhan City from December 2, 2019, to March 16, 2020. Before the travel ban of Wuhan City, the highest transmissibility was observed among age group 2 (R eff = 4.28), followed by group 2 to 3 (R eff = 2.61), and group 2 to 4 (R eff = 1.69). China should vaccinate at least 85% of the total population to interrupt transmission. The priority for controlling transmission should be to vaccinate 5% to 8% of individuals in age group 2 per day (ultimately vaccinated 90% of age group 2), followed by 10% of age group 3 per day (ultimately vaccinated 90% age group 3). However, the optimal vaccination strategy for reducing the disease severity identified individuals ≥ 65 years old as a priority group, followed by those 45–64 years old. Conclusions Approximately 85% of the total population (nearly 1.2 billion people) should be vaccinated to build an immune barrier in China to safely consider removing border restrictions. Based on these results, we concluded that 90% of adults aged 15–64 years should first be vaccinated to prevent transmission in China. Graphical Abstract

Song, Fu, Yang, Niu, Tian, et al. present a high-quality genome assembly and transcriptome data of Taxus yunnanensis, a plant belonging to the Taxus genus known for sources of traditional medicine and natural anticancer drugs. This study explores the Taxus evolutionary history and sheds light on the Taxol biosynthetic pathway.

The common carp (Cyprinus carpio L.) is an important farmed species worldwide. Mucosal-associated lymphoid tissues play an essential role in the fight against pathogen infection. Spring viremia of carp virus (SVCV) poses a serious threat to the common carp aquaculture industry. Understanding the molecular mechanisms driving mucosal immune responses to SVCV infection is critical. In this study, the mucosal tissues (gills, foregut and hindgut) were collected from normal and infected fishes for transcriptome analysis. A total of 932,378,600 clean reads were obtained, of which approximately 80% were successfully mapped to the common carp genome. 577, 1,054 and 1,014 differential expressed genes (DEGs) were identified in the gills, foregut and hindgut, respectively. A quantitative polymerase chain reaction assay indicated that the DEGs expression in the foregut following SVCV infection was consistent with the transcriptome results. Among them, two key genes of the retinoic acid-inducible gene I (RIG-I)-like receptor family, melanoma-differentiation-associated gene 5 (MDA5) and laboratory of genetics and physiology 2 (LGP2) (i.e., CcMDA5 and CcLGP2), underwent further analysis. Overexpression of CcMDA5 or CcLGP2 increased phosphorylation of TANK-binding kinase 1 and interferon regulatory factor 3 and the expression of interferon-1 (ifn-1), myxovirus resistance (mx), viperin and interferon-stimulated gene 15 (isg15), and inhibited SVCV replication in epithelioma papulosum cyprini cells. Furthermore, CcLGP2 significantly upregulated the CcMDA5-induced ifn-1 mRNA expression and the activation of the ifn-1 promoter. Finally, confocal microscopy and coimmunoprecipitation experiments revealed that CcLGP2 colocalizes and interacts with CcMDA5 via the C-terminal regulatory domain. This study provides essential gene resources for understanding the fish immune response to SVCV infection and sheds light on the potential role of fish LGP2 in the MDA5 regulation.

Obesity induced by a high-fat diet (HFD) is an important cause of impaired memory and cognitive function, but the underlying mechanisms are not clear. In the present study, we analyzed the levels of circRNAs in the hippocampus of C57BL/6J mice and evaluated the memory and cognition ability of C57BL/6J mice with HFD using Morris water maze and Y-maze approaches to explore the potential mechanisms linking circRNAs in obesity-associated cognitive impairment. Learning performance showed that HFD-induced obesity mice have impaired memory and cognition. The Arraystar analysis of the hippocampus displayed that HFD-induced obesity leads to the differential expression of circRNAs (DE-circRNAs) in mice. In total, 46 circular RNAs with elevated expression and 10 with decreased expression were identified. Among them, mmu_circRNA_004797 was identified to be significantly downregulated and the expression of mmu_circRNA_21040 was significantly upregulated in the HFD-fed mice, compared with control mice by PCR test. Bioinformatics analysis also showed that the upregulated circRNAs were related to the neuronal function and behavior, and material transport process, while downregulated circRNAs participated in the process of cell response to external stimuli, such as cellular response to nutrient levels. Furthermore, the KEGG pathway analysis showed that the upregulated circRNAs are mainly involved in Axon guidance, calcium signaling pathway, and ErbB signaling pathway. Only a single significant pathway, that is, “protein processing in endoplasmic reticulum”, was observed in the downregulated circRNAs. Finally, we examined the deficits of hippocampal synaptic plasticity and detected the expression of ER stress-related protein. The results showed that ER stress was activated in the hippocampus, and hippocampal synaptic plasticity deficits were displayed. Our results demonstrated that circRNAs were most likely implicated in the predisposition to obesity-associated cognitive impairment.

ObjectivesThis study aims to explore the interaction of different pathogens in Hand, foot and mouth disease (HFMD) by using a mathematical epidemiological model and the reported data in five regions of China.MethodsA cross-regional dataset of reported HFMD cases was built from four provinces (Fujian Province, Jiangsu province, Hunan Province, and Jilin Province) and one municipality (Chongqing Municipality) in China. The subtypes of the pathogens of HFMD, including Coxsackievirus A16 (CV-A16), enteroviruses A71 (EV-A71), and other enteroviruses (Others), were included in the data. A mathematical model was developed to fit the data. The effective reproduction number (Reff) was calculated to quantify the transmissibility of the pathogens.ResultsIn total, 3,336,482 HFMD cases were collected in the five regions. In Fujian Province, the Reff between CV-A16 and EV-A71&CV-A16, and between CV-A16 and CV-A16&Others showed statistically significant differences (P < 0.05). In Jiangsu Province, there was a significant difference in Reff (P < 0.05) between the CV-A16 and Total. In Hunan Province, the Reff between CV-A16 and EV-A71&CV-A16, between CV-A16 and Total were significant (P < 0.05). In Chongqing Municipality, we found significant differences of the Reff (P < 0.05) between CV-A16 and CV-A16&Others, and between Others and CV-A16&Others. In Jilin Province, significant differences of the Reff (P < 0.05) were found between EV-A71 and Total, and between Others and Total.ConclusionThe major pathogens of HFMD have changed annually, and the incidence of HFMD caused by others and CV-A16 has surpassed that of EV-A71 in recent years. Cross-regional differences were observed in the interactions between the pathogens.

BackgroundThe epidemiological characteristics and transmissibility of Coronavirus Disease 2019 (COVID-19) may undergo changes due to the mutation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) strains. The purpose of this study is to compare the differences in the outbreaks of the different strains with regards to aspects such as epidemiological characteristics, transmissibility, and difficulties in prevention and control.MethodsCOVID-19 data from outbreaks of pre-Delta strains, the Delta variant and Omicron variant, were obtained from the Chinese Center for Disease Control and Prevention (CDC). Case data were collected from China's direct-reporting system, and the data concerning outbreaks were collected by on-site epidemiological investigators and collated by the authors of this paper. Indicators such as the effective reproduction number (Reff), time-dependent reproduction number (Rt), rate of decrease in transmissibility (RDT), and duration from the illness onset date to the diagnosed date (DID)/reported date (DIR) were used to compare differences in transmissibility between pre-Delta strains, Delta variants and Omicron variants. Non-parametric tests (namely the Kruskal-Wallis H and Mean-Whitney U tests) were used to compare differences in epidemiological characteristics and transmissibility between outbreaks of different strains. P < 0.05 indicated that the difference was statistically significant.ResultsMainland China has maintained a “dynamic zero-out strategy” since the first case was reported, and clusters of outbreaks have occurred intermittently. The strains causing outbreaks in mainland China have gone through three stages: the outbreak of pre-Delta strains, the outbreak of the Delta variant, and outbreaks involving the superposition of Delta and Omicron variant strains. Each outbreak of pre-Delta strains went through two stages: a rising stage and a falling stage, Each outbreak of the Delta variant and Omicron variant went through three stages: a rising stage, a platform stage and a falling stage. The maximum Reff value of Omicron variant outbreaks was highest (median: 6.7; ranged from 5.3 to 8.0) and the differences were statistically significant. The RDT value of outbreaks involving pre-Delta strains was smallest (median: 91.4%; [IQR]: 87.30–94.27%), and the differences were statistically significant. The DID and DIR for all strains was mostly in a range of 0–2 days, with more than 75%. The range of duration for outbreaks of pre-Delta strains was the largest (median: 20 days, ranging from 1 to 61 days), and the differences were statistically significant.ConclusionWith the evolution of the virus, the transmissibility of the variants has increased. The transmissibility of the Omicron variant is higher than that of both the pre-Delta strains and the Delta variant, and is more difficult to suppress. These findings provide us with get a more clear and precise picture of the transmissibility of the different variants in the real world, in accordance with the findings of previous studies. Reff is more suitable than Rt for assessing the transmissibility of the disease during an epidemic outbreak.

Summary: Lindera glauca is a crucial source of diverse industrial oil and medicines. The spicy aroma of tender leaves is caused by the presence of abundant aromatic compounds. Here, we present its chromosome-level genome assembly comprising 12 pseudochromosomes (2,092.2 Mb; scaffold N50: 186.5 Mb), which was predicted to have 65,145 protein-coding genes. Comparative genomic analyses indicated two whole-genome duplication (WGD) events in the Lauraceae family, contributing to the production of numerous terpene synthase (TPS) genes. We identified 138 TPS genes in L. glauca. Comparative transcriptomic analyses revealed high expression of genes Lg03G2346 and Lg08G140 in TPS-a and Lg07G2961 and Lg12G971 in TPS-b subfamilies, which regulated the biosynthesis of the monoterpenoid β-ocimene and sesquiterpenoid D-germacrene in L. glauca. The results suggested a molecular basis for species-specific terpenoid biosynthesis and provided a foundation for molecular breeding to produce desired characteristics and a valuable reference genome.

Control measures during the coronavirus disease 2019 (COVID-19) outbreak may have limited the spread of infectious diseases. This study aimed to analyze the impact of COVID-19 on the spread of hand, foot, and mouth disease (HFMD) in China. A mathematical model was established to fit the reported data of HFMD in six selected cities in mainland China from 2015 to 2020. The absolute difference (AD) and relative difference (RD) between the reported incidence in 2020, and simulated maximum, minimum, or median incidence of HFMD in 2015–2019 were calculated. The incidence and Reff of HFMD have decreased in six selected cities since the outbreak of COVID-19, and in the second half of 2020, the incidence and Reff of HFMD have rebounded. The results show that the total attack rate (TAR) in 2020 was lower than the maximum, minimum, and median TAR fitted in previous years in six selected cities (except Changsha City). For the maximum, median, minimum fitted TAR, the range of RD (%) is 42·20–99·20%, 36·35–98·41% 48·35–96·23% (except Changsha City) respectively. The preventive and control measures of COVID-19 have significantly contributed to the containment of HFMD transmission.

Public health decision-making may have great uncertainty especially in dealing with emerging infectious diseases, so it is necessary to establish a collaborative mechanism among modelers, epidemiologists, and public health decision-makers to reduce the uncertainty as much as possible. We searched the relevant studies on transmission dynamics modeling of infectious diseases, SARS, MERS, and COVID-19 as of March 1, 2021 based on PubMed. We compared the key health decision-making time points of SARS, MERS, and COVID-19 prevention and control, and the publication time points of modeling research, to reveal the collaboration between infectious disease modeling and public health decision-making in the context of the COVID-19 pandemic. Searching with infectious disease and mathematical model as keywords, there were 166, 81 and 1 289 studies on the modeling of infectious disease transmission dynamics of SARS, MERS, and COVID-19 were retrieved respectively. Based on the modeling application framework of public health practice proposed in the current study, the collaboration among modelers, epidemiologists and public health decision-makers should be strengthened in the future.

Coptis chinensis represents an early-diverging eudicot lineage with diverse medicinal applications. Here, the authors report its chromosome-scale genome assembly, infer a single ancient whole-genome duplication, and characterize the function of CYP719 in diversification of protoberberine-type alkaloids.

This study aimed to assess the effects of feeding with different forage sources and starter concentrations on growth performance, nutrient digestibility, ruminal fermentation, and the microbial community in weaned Holstein calves. A total of 54 Holstein calves (body weight (BW) = 77.50 ± 5.07 kg; age = 70 ± 2.54 days) were assigned to 1 of 3 treatment groups (n = 18/group) that were offered diets with different forages: (1) peanut vine (PV), (2) oat hay (OH), or (3) an alfalfa hay + oat hay combination (alfalfa hay:oat hay =1:1, AO). Starter and forage intakes were recorded daily, while BW and growth parameters were assessed at 15-day intervals. The apparent digestibility of nutrients was determined. Ruminal fluid samples were collected and used to detect relevant indicators. A difference was observed for the forage × age interaction for all feed, nutrient intake, BW, ADG, and body structure parameters (P < 0.05). The final BW, average daily feed intake (ADFI), and average daily gain of the PV calves were higher than those of calves from the other groups (P < 0.05). The ruminal propionate concentration evidently increased in calves of the AO group (P < 0.05). The abundances of Rikenellaceae_RC9_gut_group and Shuttleworthia showed distinct responses to feeding with different forages (P < 0.05) at the genus level. The relative abundance of Shuttleworthia was negatively related to rumen pH and acid detergent fiber digestibility (P < 0.05) and strongly positively related to propionate concentration (P < 0.01). A positive correlation was found between Ruminococcus_1 abundance and butyrate concentration and neutral detergent fiber digestibility (P < 0.05). The relative abundances of Succiniclasticum and Prevotella_7 were negatively related to butyrate concentration (P < 0.05). In conclusion, there was an interaction between the factors (forage × age). The peanut vine used as a forage source promoted a higher starter concentrate intake compared to other diets and increased with the calves' age. The growth performance and rumen bacterial community of the calves were further improved. These results indicate that peanut vine can be used as the main source of forage in the diets of weaned calves.

The human brain dynamically shifts between a predominantly integrated state and a predominantly segregated state, each with different roles in supporting cognition and behavior. However, no studies to date have investigated lesions placed in different regions of the cerebral cortex to determine the effects on the temporal balance of integration and segregation. Here, we used the integrated state occurrence rate to measure the temporal balance of integration and segregation in the resting brain. Based on dynamic mean-field models coupled through the individual's structural white matter connections, neural activity was modeled. By lesioning different individual nodes from the model, our results implied that the impact of lesions reaches far beyond focal damage and could impair cognition by affecting system-level dynamics. Lesions in a portion of the nodes in the visual, somatomotor, limbic, and default networks significantly compromised the temporal balance of integration and segregation. Crucially, the effects of lesions in different regions could be predicted based on the hierarchical axis inferred from the T1w/T2w map and specific graph measures of structural brain networks. Taken together, our findings indicate the possibility of significant contributions of anatomical heterogeneity to the dynamics of functional network topology. Although still in its infancy, computational modeling may provide an entry point for understanding brain disorders at a causal mechanistic level, possibly leading to novel, more effective therapeutic interventions.

Although many resting state and task state characteristics have been studied, it is still unclear how the brain network switches from the resting state during tasks. The current theory shows that the brain is a complex dynamic system and synchrony is defined to measure brain activity. The study compared the changes of synchrony between the resting state and different task states in healthy young participants (N = 954). It also examined the ability to switch from the resting state to the task-general architecture of synchrony. We found that the synchrony increased significantly during the tasks. And the results showed that the brain has a task-general architecture of synchrony during different tasks. The main feature of task-based reasoning is that the increase in synchrony of high-order cognitive networks is significant, while the increase in synchrony of sensorimotor networks is relatively low. In addition, the high synchrony of high-order cognitive networks in the resting state can promote task switching effectively and the pre-configured participants have better cognitive performance, which shows that spontaneous brain activity and cognitive ability are closely related. These results revealed changes in the brain network configuration for switching between the resting state and task state, highlighting the consistent changes in the brain network between different tasks. Also, there was an important relationship between the switching ability and the cognitive performance.

Abstract Sanwei-Tanxiang powder (SWTX), a traditional Mongolian and Tibetan medicine containing a cocktail of active molecules, relieves angina pectoris and improves recovery in patients with coronary heart disease (CHD). The pharmacological effect of SWTX on CHD was analyzed at a systemic point of view in our previous studies. The bioinformatics prediction showed that the PI3K/Akt/FoxO3a pathway was one of important pathways of SWTX on treatment of coronary heart disease. Based on it, the aim of this study was to evaluate the benefits of SWTX in acute myocardial ischemic-reperfused (MIR) rat in vivo and H9c2 cardiomyoblast cells under oxidative stress induced by H2O2 in vitro, and further investigate the involvement of PI3K/Akt/FoxO3a pathway in these processes. Ex vivo, under physiological conditions, SWTX did not show any modification in the heart rate and contraction amplitude. However, against a MIR injury, SWTX pretreatment provided significant protection, including reduced ST-segment elevation, pathological changes and myocardial infarct size in vivo, meanwhile, some monomers of SWTX showed antioxidant capacity and inhibited cardiomyocytic apoptosis in vitro. The effect was correlated with the activation of the PI3K/Akt/FoxO3a signaling pathway downstream and the regulation of downstream pro-apoptotic Bim of FoxO3a experimental verified by qRT-PCR, Western blot and immunofluorescent assay. In vitro, blocking Akt and p-FoxO3a activation with the PI3K inhibitor LY294002 effectively suppressed the protective effects of several active monomers (including quercetin, macelignan,methyleugenol and Santol) of SWTX against H2O2-induced injury. Collectively, these results suggest that SWTX decreases I/R injury, and the PI3K/Akt/FoxO3a pathway takes part in protection during this process, gallogen (G3) and quercetin (G8) of GZ, methyleugenol (R2) and macelignan (R7) of RDK, santol (T1) of TX are responsible at least in part for SWTX’s cardioprotection effect.

Rehmannia glutinosa is a potent medicinal plant with a significant importance in traditional Chinese medicine. Its root is enriched with various bioactive molecules mainly iridoids, possessing important pharmaceutical properties. However, the molecular biology and evolution of R. glutinosa have been largely unexplored. Here, we report a reference genome of R. glutinosa using Nanopore technology, Illumina and Hi-C sequencing. The assembly genome is 2.49 Gb long with a scaffold N50 length of 70 Mb and high heterozygosity (2%). Since R. glutinosa is an autotetraploid (4n = 56), the difference between each set of chromosomes is very small, and it is difficult to distinguish the two sets of chromosomes using Hi-C. Hence, only one set of the genome size was mounted to the chromosome level. Scaffolds covering 52.61% of the assembled genome were anchored on 14 pseudochromosomes. Over 67% of the genome consists of repetitive sequences dominated by Copia long terminal repeats and 48,475 protein-coding genes were predicted. Phylogenetic analysis corroborates the placement of R. glutinosa in the Orobanchaceae family. Our results indicated an independent and very recent whole genome duplication event that occurred 3.64 million year ago in the R. glutinosa lineage. Comparative genomics analysis demonstrated expansion of the UDP-dependent glycosyltransferases and terpene synthase gene families, known to be involved in terpenoid biosynthesis and diversification. Furthermore, the molecular biosynthetic pathway of iridoids has been clarified in this work. Collectively, the generated reference genome of R. glutinosa will facilitate discovery and development of important pharmacological compounds.

Varicella-zoster virus (VZV), a highly infectious agent that causes varicella (chickenpox), can also cause zoster (shingles), a disorder that is frequently associated with severe neuralgia. A reliable serological VZV diagnostic assay would be useful for identifying unprotected individuals and for surveilling post-vaccination immunoprotection status. Toward this goal, VZV membrane glycoprotein E (gE), the immunodominant VZV protein, served as target antigen in an indirect ELISA kit developed here to detect anti-VZV antibodies in clinical samples. For target antigen preparation, Chinese hamster ovary (CHO) cells were modified to express and secrete the VZV gE ectodomain, which was subsequently purified and used as coating antigen in an indirect ELISA. Ultimately, the optimal purified gE coating antigen concentration was determined to be 2 μg.ml−1 and the OD450nm detection cutoff value was 0.286. The coefficient of variation (CV) of intra-assay and inter-assay were

BackgroundHand-Foot-and-Mouth-Disease (HFMD) has been widely spread in Asia, and has result in a high disease burden for children in many countries. However, the dissemination characteristics intergroup and between different age groups are still not clear. In this study, we aim to analyze the differences in the transmissibility of HFMD, in the whole population and among age groups in Shenzhen city, by utilizing mathematical models.MethodsA database that reports HFMD cases in Shenzhen city from January 2010 to December 2017 was collected. In the first stage, a Susceptive-Infected-Recovered (SIR) model was built to fit data of Shenzhen city and its districts, and Reff was used to assess transmissibility in each district. In the second stage, a cross-age groups SIR model was constructed to calculate the difference in transmissibility of reported cases among three age groups of EV71 virus: 0–3 years, 3–5 years, and over 5 years which was denoted as age group 1, 2, and 3, respectively.ResultsFrom 2010 to 2017, 345,807 cases of HFMD were reported in Shenzhen city, with peak incidence in spring and autumn in Shenzhen city and most of its districts each year. Analysis of the EV71 incidence data by age group revealed that age Group 1 have the highest incidence (3.13 ×10−7–2.31 ×10−4) while age group 3 had the lowest incidence (0–3.54 ×10−5). The differences in weekly incidence of EV71 between age groups were statistically significant (t12 = 7.563, P < 0.0001; t23 = 12.420, P < 0.0001; t13 = 16.996, P < 0.0001). The R2 of the SIR model Shenzhen city population-wide HFMD fit for each region was >0.5, and P < 0.001. Reff values were >1 for the vast majority of time and regions, indicating that the HFMD virus has the ability to spread in Shenzhen city over the long-term. Differences in Reff values between regions were judged by using analysis of variance (ANOVA) (F = 0.541, P = 0.744). SiIiRi-SjIjRj models between age groups had R2 over 0.7 for all age groups and P

Rett syndrome (RTT) is a severe progressive neurodevelopmental disease characterized by psychomotor regression. The FOXG1 gene is one of the pathogenic genes associated with the congenital Rett variant, which is less studied. Only a few Chinese patients with FOXG1 mutation have been reported. In this study, we describe a Chinese female patient with congenital Rett variant who presented with psycho-motor retardation, developmental regression, microcephaly, seizure, stereotypic hand movement and hypotonia. Targeted high-throughput sequencing was conducted, and a heterozygous FOXG1 mutation [NM_005249.4: c.506dupG (P.G169Gfs* 286)] was identified. It was a frameshift mutation resulting in alteration of the reading frames downstream of the mutation.SIMILAR CASES PUBLISHED: 10. CONFLICT OF INTEREST: None.

In recent years, there has been growing interest in studying the complexity of resting-state functional magnetic resonance imaging (rs-fMRI) brain signals. As one of the most commonly used complexity methods, entropy measures have been used to quantitatively characterize abnormal brain activity in aged individuals and patients with psychopathic and neurological disorders, and most studies have analyzed brain signals from a single channel. The widely used entropy methods include approximate entropy (AE), sample entropy (SE), permutation entropy (PE), and fuzzy entropy (FE). However, the test-retest reliability of different entropy methods remains to be explored. In this study, we investigated the distribution and test-retest reliability of four entropy measures and a new entropy algorithm we proposed, permutation fuzzy entropy (PFE), in three independent data sets at three levels, i.e., based on voxels, brain regions, and functional networks. Our results showed that analyzing fMRI signals with entropy showed strong tissue sensitivity. The highest reliability was achieved with PFE, and PE and FE were superior to AE and SE at all three levels. The percentage of nodes with good to excellent reliability in PFE, PE, FE, SE and AE was 94.31%, 52.65%, 18.56%, 11.36% and 0.76%, respectively. PFE and PE showed fair to good reliability in the visual network, auditory network, default-mode network, etc. In conclusion, characterizing brain entropy may provide an informative tool to assess the complexity of brain functions. Our results suggested that PFE and PE had better reliability and reflected more topological information related to normal and disordered functioning of the human brain.

Parkinson’s disease (PD) is a common neurodegenerative disorder. Rapid eye movement sleep behavior disorder (RBD) is one of the prodromal symptoms of PD. Studies have shown that brain information transmission is affected in PD patients. Consequently, we hypothesized that brain information transmission is impaired in RBD and PD. To prove our hypothesis, we performed functional connectivity (FC) and functional dynamics analysis of three aspects—based on the whole brain, within the resting-state network (RSN), and the interaction between RSNs—using normal control (NC) (n = 21), RBD (n = 24), and PD (n = 45) resting-state functional magnetic resonance imaging (rs-fMRI) data sets. Furthermore, we tested the explanatory power of FC and functional dynamics for the clinical features. Our results found that the global functional dynamics and FC of RBD and PD were impaired. Within RSN, the impairment concentrated in the visual network (VIS) and sensorimotor network (SMN), and the impaired degree of SMN in RBD was higher than that in PD. On the interaction between RSNs, RBD showed a widespread decrease, and PD showed a focal decrease which concentrated in SMN and VIS. Finally, we proved FC and functional dynamics were related to clinical features. These differences confirmed that brain information transmission efficiency and flexibility are impaired in RBD and PD, and these impairments are associated with the clinical features of patients.

Epstein-Barr virus (EBV) linked with nasopharyngeal carcinoma (NPC) is considered to be one of the most prevalent head and neck malignancies in East and Southeast Asia. Although radiotherapy and chemotherapy are effective treatments for NPC, they have immunosuppressive effects. Immunotherapy has got considerable attention of clinicians for cancer treatment in recent years due to proven success of PD-1/PD-L 1 inhibition in solid tumors trials. The distinct immunological environment of EBV-associated NPC presents a reasonable therapeutic target for PD-1/PD-L 1 inhibition. Immune checkpoint blockade therapy targeting the programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L 1) receptors have shown efficacy in early phase I clinical trials, with ongoing phase III clinical trials. Herein, we have extensively addressed the role of the PD-1/PD-L1 axis in the immunotherapy of EBV-associated NPC. Immunotherapeutic strategies are anticipated to enter mainstream clinical practise and provide long-term remissions in patients with severe NPC.