Combined subsoiling and ridge-furrow rainfall harvesting during the summer fallow season improves wheat yield, water and nutrient use efficiency, and quality and reduces soil nitrate-N residue in the dryland summer fallow-winter wheat rotation.

Both subsoiling tillage (ST) and ridge and furrow rainfall harvesting (RF) are widely implemented and play an important role in boosting wheat productivity. However, information about the effects of ST coupled with RF during the summer fallow season on wheat productivity and environmental issues remains limited. This study aims to explore the effects of ST coupled with RF on water harvesting, wheat productivity-yield traits, water and nutrient use efficiency and quality, and soil nitrate-N residue in dryland winter wheat-summer fallow rotation at the intersection of southern Loess Plateau and western Huang-Huai-Hai Plain in China in 2018-2022. Three tillage practices-deep plowing with straw turnover (PTST), subsoiling with straw mulching (STSM), and STSM coupled with RF (SRFSM)-are conducted during the summer fallow season. The results indicated that tillage practices during the summer fallow season significantly impacted wheat productivity and soil nitrate-N residue. Compared to PTST, STSM significantly enhanced rainfall fallow efficiency and water use efficiency by 7.0% and 14.2%, respectively, as well as N, P, and K uptake efficiency by 16.9%, 16.2%, and 15.3%, and thus increased grain yield by 14.3% and improved most parameters of protein components and processing quality, albeit with an increase in nitrate-N residue in the 0- to 300-cm soil depth by 12.5%. SRFSM, in turn, led to a further increase in water storage at sowing, resulting in an increase of water use efficiency by 6.8%, as well as N, P, and K uptake efficiency and K internal efficiency by 11.8%, 10.4%, 8.8%, and 4.7%, thereby significantly promoting grain yield by 10.2%, and improving the contents of all the protein components and enhancing the processing quality in grain, and simultaneously reducing the nitrate-N residue in the 0- to 300-cm soil layer by 16.1%, compared to STSM. In essence, this study posits that employing subsoiling coupled with ridge-furrow rainfall harvesting (SRFSM) during the summer fallow season is a promising strategy for enhancing wheat yield, efficiency, and quality, and simultaneously reducing soil nitrate-N residue within the dryland summer fallow-winter wheat rotation system.

Brain network dynamics in women with primary dysmenorrhea during the pain-free periovulation phase.

The human brain is a dynamic system that shows frequency-specific features. Neuroimaging studies have shown that both healthy individuals and those with chronic pain disorders experience pain influenced by various processes that fluctuate over time. Primary dysmenorrhea is a chronic visceral pain that disrupts the coordinated activity of brain's functional network. However, it remains unclear whether the dynamic interactions across the whole-brain network over time and their associations with neurobehavioral symptoms are dependent on the frequency bands in patients with primary dysmenorrhea during the pain-free periovulation phase. In this study, we used an energy landscape analysis to examine the interactions over time across the large-scale network in a sample of 59 patients with primary dysmenorrhea and 57 healthy controls at different frequency bands. Compared to healthy controls, patients with primary dysmenorrhea exhibit aberrant brain dynamics, with more significant differences in the slow-4 frequency band. Patients with primary dysmenorrhea show more indirect neural transition times due to an unstable intermediate state, whereas neurotypical brain activity frequently transitions between two major states. This data-driven approach further revealed that the brains of individuals with primary dysmenorrhea have more abnormal brain dynamics than healthy controls. Our results suggested that unstable brain dynamics were associated with the strength of brain functional segregation and the Pain Catastrophizing Scale (PCS) score. Our findings provide preliminary evidence that atypical dynamics in the functional network may serve as a potential key feature and biological marker of patients with PDM during the pain-free phase. PERSPECTIVE: We applied energy landscape analysis on brain-imaging data to identify relatively stable and dominant brain activity patterns for patients with primary dysmenorrhea(PDM). More atypical brain dynamics were found in the slow-4 band and were related to the strength of functional segregation, providing new insights into the dysfunction brain dynamics.

Coupled one-off alternate furrow irrigation with nitrogen topdressing at jointing optimizes soil nitrate-N distribution and wheat nitrogen productivity in dryland.

The judicious management of water and nitrogen (N) is pivotal for augmenting crop productivity and N use efficiency, while also mitigating environmental concerns. With the advent of the High-Farmland Construction Program in China, one-off irrigation has become feasible for most dryland fields, presenting a novel opportunity to explore the synergistic strategies of water and N management. This study delves into the impact of one-off alternate furrow irrigation (AFI) and topdressing N fertilizer (TN) on soil nitrate-N distribution, and N productivity-including plant N accumulation, translocation, and allocation, and grain yield, protein content, N use efficiency of winter wheat (Triticum aestivum L.) in 2018-2019 and 2019-2020. Experimental treatments administered at the jointing stage comprised of two irrigation methods-every (EFI) and alternative (AFI) furrow irrigation at 75 mm, and two topdressing N rates-0 (NTN) and 60 (TN) kg N ha-1. Additionally, a conventional local farmer practice featuring no irrigation and no topdressing N (NINTN) was served as control. Compared to NINTN, EFINTN substantially increased aboveground N accumulation, grain yield, and protein yield, albeit with a reduction in grain protein content by 8.1%-10.6%. AFI, in turn, led to higher nitrate-N accumulation in the 60-160 cm soil depth at booting and anthesis, but diminished levels at maturity, resulting in a significant surge in N accumulation from anthesis to maturity and its contribution to grain, N fertilizer partial factor productivity (PFPN), and N uptake efficiency (NUPE), thereby promoting grain yield by 9.9% and preserving grain protein content. Likewise, TN enhanced soil nitrate-N at key growth stages, reflected in marked improvements in N accumulation both from booting to anthesis and from anthesis to maturity, as well as in grain yield, protein content, and protein yield. The combination of AFI and TN (AFITN) yielded the highest grain yield, protein content, with PFPN, NUPE, and N internal efficiency outstripping those of EFINTN, but not AFINTN. In essence, one-off AFI coupled with TN at the jointing stage is a promising strategy for optimizing soil nitrate-N and enhancing wheat N productivity in dryland where one-off irrigation is assured.

Organic fertilizer substituting 20% chemical N increases wheat productivity and soil fertility but reduces soil nitrate-N residue in drought-prone regions.

Organic fertilizer substitution is an effective measure for increasing both the quantity and quality of wheat grain while reducing chemical fertilizer input. However, the effects of reducing nitrogen (N) fertilizer combined with organic fertilizer substitution on grain yield, grain protein content and protein yield, plant N accumulation and translocation, N use efficiency, soil fertility, N apparent surplus and nitrate-N residue in rain-fed drought-prone areas remains limited. In this study, field experiments were conducted over four consecutive seasons (2019-2023) at two sites with four treatments: zero N application (ZN), farmer N application (FN), reduced 20% N of FN (RN), and organic fertilizer substituting 20% N of RN (OSN). The results showed that compared with the ZN treatment, the FN, RN and OSN treatments increased grain yield and its components, grain protein content and protein yield, aboveground N accumulation at the anthesis and maturity stages, pre-anthesis N translocation, post-anthesis N accumulation, N use efficiency, soil fertility. Compared with RN and FN, OSN increased grain yield by 17.12% and 15.03%, grain protein yield by 3.31% and 17.15%, grain N accumulation by 17.78% and 15.58%, and N harvest index by 2.63% and 4.45% averaged across years and sites, respectively. Moreover, OSN increased the contents of organic matter, total N, available P and available K in both 0-20 and 20-40 cm soil layers, decreased N apparent surplus and nitrate-N residue in 0-100 cm, and pH in both 0-20 and 20-40 cm soil layer. Fundamentally, this study suggests that integrating a 20% reduction N from conventional farmer practices with the utilization of organic fertilizer to replace 20% of the chemical N fertilizer (OSN) represents an effective strategy. This approach shows promise in enhancing wheat grain yield, grain protein yield, and N use efficiency. Additionally, it supports the improvement of soil fertility while simultaneously reducing soil nitrate-N residues and the apparent surplus of N in rain-fed drought-prone regions.

Dynamic nonreversibility view of intrinsic brain organization and brain dynamic analysis of repetitive transcranial magnitude stimulation.

Intrinsic neural activities are characterized as endless spontaneous fluctuation over multiple time scales. However, how the intrinsic brain organization changes over time under local perturbation remains an open question. By means of statistical physics, we proposed an approach to capture whole-brain dynamics based on estimating time-varying nonreversibility and k-means clustering of dynamic varying nonreversibility patterns. We first used synthetic fMRI to investigate the effects of window parameters on the temporal variability of varying nonreversibility. Second, using real test-retest fMRI data, we examined the reproducibility, reliability, biological, and physiological correlation of the varying nonreversibility substates. Finally, using repetitive transcranial magnetic stimulation-fMRI data, we investigated the modulation effects of repetitive transcranial magnetic stimulation on varying nonreversibility substate dynamics. The results show that: (i) as window length increased, the varying nonreversibility variance decreased, while the sliding step almost did not alter it; (ii) the global high varying nonreversibility states and low varying nonreversibility states were reproducible across multiple datasets and different window lengths; and (iii) there were increased low varying nonreversibility states and decreased high varying nonreversibility states when the left frontal lobe was stimulated, but not the occipital lobe. Taken together, these results provide a thermodynamic equilibrium perspective of intrinsic brain organization and reorganization under local perturbation.

DeepWalk-aware graph attention networks with CNN for circRNA-drug sensitivity association identification.

Circular RNAs (circRNAs) are a class of noncoding RNA molecules that are widely found in cells. Recent studies have revealed the significant role played by circRNAs in human health and disease treatment. Several restrictions are encountered because forecasting prospective circRNAs and medication sensitivity connections through biological research is not only time-consuming and expensive but also incredibly ineffective. Consequently, the development of a novel computational method that enhances both the efficiency and accuracy of predicting the associations between circRNAs and drug sensitivities is urgently needed. Here, we present DGATCCDA, a computational method based on deep learning, for circRNA-drug sensitivity association identification. In DGATCCDA, we first construct multimodal networks from the original feature information of circRNAs and drugs. After that, we adopt DeepWalk-aware graph attention networks to sufficiently extract feature information from the multimodal networks to obtain the embedding representation of nodes. Specifically, we combine DeepWalk and graph attention network to form DeepWalk-aware graph attention networks, which can effectively capture the global and local information of graph structures. The features extracted from the multimodal networks are fused by layer attention, and eventually, the inner product approach is used to construct the association matrix of circRNAs and drugs for prediction. The ultimate experimental results obtained under 5-fold cross-validation settings show that the average area under the receiver operating characteristic curve value of DGATCCDA reaches 91.18%, which is better than those of the five current state-of-the-art calculation methods. We further guide a case study, and the excellent obtained results also show that DGATCCDA is an effective computational method for exploring latent circRNA-drug sensitivity associations.

Integration of comparative transcriptomics and WGCNA characterizes the regulation of anthocyanin biosynthesis in mung bean (Vigna radiata L.).

Mung bean is a dual-use crop widely cultivated in Southeast Asia as a food and medicine resource. The development of new functional mung bean varieties demands identifying new genes regulating anthocyanidin synthesis and investigating their molecular mechanism. In this study, we used high-throughput sequencing technology to generate transcriptome sequence of leaves, petioles, and hypocotyls for investigating the anthocyanins accumulation in common mung bean variety as well as anthocyanidin rich mung bean variety, and to elucidate their molecular mechanisms. 29 kinds of anthocyanin compounds were identified. Most of the anthocyanin components contents were significantly higher in ZL23 compare with AL12. Transcriptome analysis suggested that a total of 93 structural genes encoding the anthocyanin biosynthetic pathway and 273 regulatory genes encoding the ternary complex of MYB-bHLH-WD40 were identified, of which 26 and 78 were differentially expressed in the two varieties. Weighted gene co-expression network analysis revealed that VrMYB3 and VrMYB90 might have enhanced mung bean anthocyanin content by inducing the expression of structural genes such as PAL, 4CL, F3'5'H, LDOX, and F3'H, which was consistent with qRT-PCR results. These findings are envisaged to provide a reference for studying the molecular mechanism of anthocyanin accumulation in mung beans.

Frequency dependent whole-brain coactivation patterns analysis in Alzheimer's disease.

Background: The brain in resting state has complex dynamic properties and shows frequency dependent characteristics. The frequency-dependent whole-brain dynamic changes of resting state across the scans have been ignored in Alzheimer's disease (AD). Objective: Coactivation pattern (CAP) analysis can identify different brain states. This paper aimed to investigate the dynamic characteristics of frequency dependent whole-brain CAPs in AD. Methods: We utilized a multiband CAP approach to model the state space and study brain dynamics in both AD and NC. The correlation between the dynamic characteristics and the subjects' clinical index was further analyzed. Results: The results showed similar CAP patterns at different frequency bands, but the occurrence of patterns was different. In addition, CAPs associated with the default mode network (DMN) and the ventral/dorsal visual network (dorsal/ventral VN) were altered significantly between the AD and NC groups. This study also found the correlation between the altered dynamic characteristics of frequency dependent CAPs and the patients' clinical Mini-Mental State Examination assessment scale scores. Conclusion: This study revealed that while similar CAP spatial patterns appear in different frequency bands, their dynamic characteristics in subbands vary. In addition, delineating subbands was more helpful in distinguishing AD from NC in terms of CAP.

Cholesterol esterification and p53-mediated tumor suppression.

Many human cancers carry missense mutations in or deletions of the tumor protein 53 (TP53) tumor suppressor gene. TP53's product, p53 regulates many biological processes, including cell metabolism. Cholesterol is a key lipid needed for the maintenance of membrane function and tissue homeostasis while also serving as a precursor for steroid hormone and bile acid synthesis. An over-abundance of cholesterol can lead to its esterification and storage as cholesterol esters. The recent study has shown that the loss of p53 leads to excessive cholesterol ester biosynthesis, which promotes hepatocellular carcinoma in mice. Blocking cholesterol esterification improves treatment outcomes, particularly for liver cancers with p53 deletions/mutations that originate in a background of non-alcoholic fatty liver disease.

Criticality in transient behavior of coupled oscillator system toward chimera and synchronization.

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, while how the system is steering toward different final destinies upon spatially localized perturbation is still unknown. Through a systematic numerical analysis of the evolution of the spatiotemporal patterns of multi-chimera states, we uncover a critical behavior of the system in transient time toward either chimera or synchronization as the final stable state. We measure the critical values and the transient time of chimeras with different numbers of clusters. Then, based on an adequate verification, we fit and analyze the distribution of the transient time, which obeys power-law variation process with the increase in perturbation strengths. Moreover, the comparison between different clusters exhibits an interesting phenomenon, thus we find that the critical value of odd and even clusters will alternatively converge into a certain value from two sides, respectively, implying that this critical behavior can be modeled and enabling the articulation of a phenomenological model.

Structures of p53/BCL-2 complex suggest a mechanism for p53 to antagonize BCL-2 activity.

Mitochondrial apoptosis is strictly controlled by BCL-2 family proteins through a subtle network of protein interactions. The tumor suppressor protein p53 triggers transcription-independent apoptosis through direct interactions with BCL-2 family proteins, but the molecular mechanism is not well understood. In this study, we present three crystal structures of p53-DBD in complex with the anti-apoptotic protein BCL-2 at resolutions of 2.3-2.7 Å. The structures show that two loops of p53-DBD penetrate directly into the BH3-binding pocket of BCL-2. Structure-based mutations at the interface impair the p53/BCL-2 interaction. Specifically, the binding sites for p53 and the pro-apoptotic protein Bax in the BCL-2 pocket are mostly identical. In addition, formation of the p53/BCL-2 complex is negatively correlated with the formation of BCL-2 complexes with pro-apoptotic BCL-2 family members. Defects in the p53/BCL-2 interaction attenuate p53-mediated cell apoptosis. Overall, our study provides a structural basis for the interaction between p53 and BCL-2, and suggests a molecular mechanism by which p53 regulates transcription-independent apoptosis by antagonizing the interaction of BCL-2 with pro-apoptotic BCL-2 family members.

The prognostic significance of KLRB1 and its further association with immune cells in breast cancer.

Background: Killer cell lectin-like receptor B1 (KLRB1) is an important member of the natural killer cell gene family. This study explored the potential value of KLRB1 as a breast cancer (BC) biomarker and its close association with the tumor immune microenvironment during the development of BC. Methods: We examined the differential expression of KLRB1 in pan-cancer. Clinical and RNA-Seq data from BC samples were evaluated in The Cancer Genome Atlas (TCGA) and validated in Gene Expression Omnibus (GEO) datasets and by immunohistochemistry (IHC) staining. The relationship between KLRB1 and clinical parameters was explored through Chi-square tests. The diagnostic value of KLRB1 was evaluated using a receiver operating characteristic (ROC) curve. Survival analysis was tested by Kaplan-Meier curves to demonstrate the relationship between KLRB1 and survival. Univariable and multivariate cox regression analyses were carried out as well. The analysis of immune infiltration level and gene set enrichment analysis (GSEA) were conducted to examine KLRB1's mechanism during the progression of BC. We used the Tumor Immune Estimation Resource (TIMER), the Cancer Single-cell Expression Map (CancerSCEM) database, the Tumor Immune Single-cell Hub (TISCH) database, and the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) method to explore KLRB1's association with immune infiltration level and different quantitative distribution of immune cells. The relevant signaling pathways in BC associated with KLRB1 were identified using GSEA. Results: The expression of KLRB1 was downregulated across the majority of cancers including BC. The lower KLRB1 expression group exhibited shorter relapse free survival (RFS) and overall survival (OS). IHC staining showed that KLRB1 staining was weaker in breast tumor tissues than in paratumors. Additionally, GSEA identified several pathway items distinctly enriched in BC. KLRB1 expression level was also positively related to the infiltrating number of immune cells in BC. Moreover, the CancerSCEM and TISCH databases as well as the CIBERSORT method demonstrated the close relationship between KLRB1 and immune cells, particularly macrophages. Conclusion: Low KLRB1 expression was considered an independent prognostic biomarker and played an important role in the tumor immune microenvironment of BC patients.

Low-frequency repetitive transcranial magnetic stimulation alters the individual functional dynamical landscape.

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive approach to modulate brain activity and behavior in humans. Still, how individual resting-state brain dynamics after rTMS evolves across different functional configurations is rarely studied. Here, using resting state fMRI data from healthy subjects, we aimed to examine the effects of rTMS to individual large-scale brain dynamics. Using Topological Data Analysis based Mapper approach, we construct the precise dynamic mapping (PDM) for each participant. To reveal the relationship between PDM and canonical functional representation of the resting brain, we annotated the graph using relative activation proportion of a set of large-scale resting-state networks (RSNs) and assigned the single brain volume to corresponding RSN-dominant or a hub state (not any RSN was dominant). Our results show that (i) low-frequency rTMS could induce changed temporal evolution of brain states; (ii) rTMS didn't alter the hub-periphery configurations underlined resting-state brain dynamics; and (iii) the rTMS effects on brain dynamics differ across the left frontal and occipital lobe. In conclusion, low-frequency rTMS significantly alters the individual temporo-spatial dynamics, and our finding further suggested a potential target-dependent alteration of brain dynamics. This work provides a new perspective to comprehend the heterogeneous effect of rTMS.

Triple-network analysis of Alzheimer's disease based on the energy landscape.

Introduction: Research on the brain activity during resting state has found that brain activation is centered around three networks, including the default mode network (DMN), the salient network (SN), and the central executive network (CEN), and switches between multiple modes. As a common disease in the elderly, Alzheimer's disease (AD) affects the state transitions of functional networks in the resting state. Methods: Energy landscape, as a new method, can intuitively and quickly grasp the statistical distribution of system states and information related to state transition mechanisms. Therefore, this study mainly uses the energy landscape method to study the changes of the triple-network brain dynamics in AD patients in the resting state. Results: AD brain activity patterns are in an abnormal state, and the dynamics of patients with AD tend to be unstable, with an unusually high flexibility in switching between states. Also , the subjects' dynamic features are correlated with clinical index. Discussion: The atypical balance of large-scale brain systems in patients with AD is associated with abnormally active brain dynamics. Our study are helpful for further understanding the intrinsic dynamic characteristics and pathological mechanism of the resting-state brain in AD patients.

Influence of Mycorrhiza on C:N:P Stoichiometry in Senesced Leaves.

Senesced leaves play a vital role in nutrient cycles in the terrestrial ecosystem. The carbon (C), nitrogen (N) and phosphorus (P) stoichiometries in senesced leaves have been reported, which are influenced by biotic and abiotic factors, such as climate variables and plant functional groups. It is well known that mycorrhizal types are one of the most important functional characteristics of plants that affect leaf C:N:P stoichiometry. While green leaves' traits have been widely reported based on the different mycorrhiza types, the senesced leaves' C:N:P stoichiometries among mycorrhizal types are rarely investigated. Here, the patterns in senesced leaves' C:N:P stoichiometry among plants associated with arbuscular mycorrhizal (AM), ectomycorrhizal (ECM), or AM + ECM fungi were explored. Overall, the senesced leaves' C, with 446.8 mg/g in AM plants, was significantly lower than that in AM + ECM and ECM species, being 493.1 and 501.4 mg/g, respectively, which was mainly caused by boreal biomes. The 8.9 mg/g senesced leaves' N in ECM plants was significantly lower than in AM (10.4 mg/g) or AM + ECM taxa (10.9 mg/g). Meanwhile, the senesced leaves' P presented no difference in plant associations with AM, AM + ECM and ECM. The senesced leaves' C and N presented contrary trends with the changes in mean annual temperature (MAT) and mean annual precipitation (MAP) in ECM or AM + ECM plants. The differences in senesced leaves' C and N may be more easily influenced by the plant mycorrhizal types, but not P and stoichiometric ratios of C, N and P. Our results suggest that senesced leaves' C:N:P stoichiometries depend on mycorrhizal types, which supports the hypothesis that mycorrhizal type is linked to the evolution of carbon-nutrient cycle interactions in the ecosystem.

Novel methylation-related long non-coding RNA clinical outcome prediction method: the clinical phenotype and immune infiltration research in low-grade gliomas.

Background: Recent studies have suggested that long non-coding RNAs (lncRNAs) may play crucial role in low-grade glioma; however, the underlying mechanisms linking them to epigenetic methylation remain unclear. Methods: We downloaded expression level data for regulators associated with N1 methyladenosine (m1A), 5-methyladenine (m5C), and N6 methyladenosine (m6A) (M1A/M5C/M6A) methylation from the Cancer Genome Atlas-low-grade glioma (TCGA-LGG) database. We identified the expression patterns of lncRNAs, and selected methylation-related lncRNAs using Pearson correlation coefficient>0.4. Non-negative matrix dimensionality reduction was then used to determine the expression patterns of the methylation-associated lncRNAs. We constructed a weighted gene co-expression network analysis (WGCNA) network to explore the co-expression networks between the two expression patterns. Functional enrichment of the co-expression network was performed to identify biological differences between the expression patterns of different lncRNAs. We also constructed prognostic networks based on the methylation presence in lncRNAs in low-grade gliomas. Results: We identified 44 regulators by literature review. Using a correlation coefficient greater than 0.4, we identified 2330 lncRNAs, among which 108 lncRNAs with independent prognostic values were further screened using univariate Cox regression at P< 0.05. Functional enrichment of the co-expression networks revealed that regulation of trans-synaptic signaling, modulation of chemical synaptic transmission, calmodulin binding, and SNARE binding were mostly enriched in the blue module. The calcium and CA2 signaling pathways were associated with different methylation-related long non-coding chains. Using the Least Absolute Shrinkage Selector Operator (LASSO) regression analysis, we analyzed a prognostic model containing four lncRNAs. The model's risk score was 1.12 *AC012063 + 0.74 * AC022382 + 0.32 * AL049712 + 0.16 * GSEC. Gene set variation analysis (GSVA) revealed significant differences in mismatch repair, cell cycle, WNT signaling pathway, NOTCH signaling pathway, Complement and Cascades, and cancer pathways at different GSEC expression levels. Thus, these results suggest that GSEC may be involved in the proliferation and invasion of low-grade glioma, making it a prognostic risk factor for low-grade glioma. Conclusion: Our analysis identified methylation-related lncRNAs in low-grade gliomas, providing a foundation for further research on lncRNA methylation. We found that GSEC could serve as a candidate methylation marker and a prognostic risk factor for overall survival in low-grade glioma patients. These findings shed light on the underlying mechanisms of low-grade glioma development and may facilitate the development of new treatment strategies.

Metabolomics and transcriptomics provide insights into the molecular mechanisms of anthocyanin accumulation in the seed coat of differently colored mung bean (Vigna radiata L.).

Black mung bean is rich in anthocyanin, however, the accumulation and the molecular mechanism of anthocyanin synthesis in black mung bean are unclear. In this study, anthocyanin metabolomics and transcriptomics on the seed coats of two different colors of mung bean were performed to clarify the composition of anthocyanins, and identify transcription factors involved in regulating anthocyanin biosynthesis. In the mature stage, 23 kinds of anthocyanin compounds were identified. All anthocyanin components contents were significantly higher in seed coat of black mung bean compare with green mung bean. Transcriptome analysis suggested that most of the structural genes for anthocyanin biosynthesis and some potential regulatory genes were significantly differentially expressed. WGCNA suggested VrMYB90 was an important regulatory gene in anthocyanin biosynthesis. Arabidopsis thaliana overexpressing VrMYB90 showed significant accumulation of anthocyanins. PAL, 4CL, DFR, F3'5'H, LDOX, F3'H and UFGT were up-regulated in 35S:VrMYB90 Arabidopsis thaliana. These findings provide valuable information for understanding the synthesis mechanism of anthocyanins in black mung bean seed coats.

Transcranial Alternating Current Stimulation Improves Memory Function in Alzheimer's Mice by Ameliorating Abnormal Gamma Oscillation.

Transcranial alternating current stimulation (tACS) is considered to have a positive effect on the rehabilitation of Alzheimer's disease (AD) as an intervention method that matches stimulation frequency to neurogenesis frequency. However, when tACS intervention is delivered to a single target, the current received by brain regions outside the target may be insufficient to trigger neural activity, compromising the effectiveness of stimulation. Therefore, it is worth studying how single-target tACS restores gamma-band activity in the whole hippocampal-prefrontal circuit during rehabilitation. We used Sim4Life software to conduct finite element methods (FEM) on the stimulation parameters to ensure that tACS intervened only in the right hippocampus (rHPC) and did not activate the left hippocampus (lHPC) or prefrontal cortex (PFC). We stimulated the rHPC by tACS for 21 days to improve the memory function of AD mice. We simultaneously recorded local field potentials (LFPs) in the rHP, lHPC and PFC and evaluated the neural rehabilitative effect of tACS stimulation with power spectral density (PSD), cross-frequency coupling (CFC) and Granger causality. Compared to the untreated group, the tACS group exhibited an increase in the Granger causality connection and CFC between the rHPC and PFC, a decrease in those between the lHPC and PFC, and enhanced performance on the Y-maze test. These results suggest that tACS may serve as a noninvasive method for Alzheimer's disease rehabilitation by ameliorating abnormal gamma oscillation in the hippocampal-prefrontal circuit.

Phosphomevalonate Kinase Controls ß-Catenin Signaling via the Metabolite 5-Diphosphomevalonate.

ß-catenin signaling is abnormally activated in cancer. Here, this work screens the mevalonate metabolic pathway enzyme PMVK to stabilize ß-catenin signaling using a human genome-wide library. On the one hand, PMVK-produced MVA-5PP competitively binds to CKIα to prevent ß-catenin Ser45 phosphorylation and degradation. On the other hand, PMVK functions as a protein kinase to directly phosphorylate ß-catenin Ser184 to increase its protein nuclear localization. This synergistic effect of PMVK and MVA-5PP together promotes ß-catenin signaling. In addition, PMVK deletion impairs mouse embryonic development and causes embryonic lethal. PMVK deficiency in liver tissue alleviates DEN/CCl4 -induced hepatocarcinogenesis. Finally, the small molecule inhibitor of PMVK, PMVKi5, is developed and PMVKi5 inhibits carcinogenesis of liver and colorectal tissues. These findings reveal a non-canonical function of a key metabolic enzyme PMVK and a novel link between the mevalonate pathway and ß-catenin signaling in carcinogenesis providing a new target for clinical cancer therapy.