Mulberry leaves supplementation alters lipid metabolism and promotes fatty acid ß oxidation in growing mutton sheep.

Mulberry leaves (MLs) are an unconventional feed with fiber and various active ingredients, and are acknowledged as likely to regulate lipid metabolism, while the molecular mechanism remains undefined. Therefore, our objective was to define the role of MLs on the overall lipid metabolism. We conducted a feeding experiment of three groups on growing mutton sheep fed with dried mulberry leaves (DMLs), with fermented mulberry leaves (FMLs), or without MLs (as control). Analyses of transcriptome and widely target lipids demonstrated the addition of MLs triggered big perturbations in genes and metabolites related to glycerolipid, phospholipid, ether lipid, and sphingolipid metabolism. Additionally, the variations of the above lipids in the treatment of MLs possibly facilitate immunity enhancement of growing mutton sheep via the activation of complement and coagulation cascades. Furthermore, treatments with MLs could expedite proceedings of lipid degradation and fatty acid ß oxidation in mitochondria, thereby to achieve the effect of lipid reduction. Besides, added DMLs also fuel fatty acid ß-oxidation in peroxisomes and own much stronger lipolysis than added FMLs, possibly attributed to high fiber content in DMLs. These findings establish the novel lipid-lowering role and immune protection of MLs, which lays the foundation for the medicinal application of MLs.

Mulberry leaves (MLs) are rich in a wide variety of active ingredients and are also a kind of traditional Chinese medicine with the same origin as medicine and food. Previous studies have found that MLs may regulate lipid metabolism. But the exact mechanism remains unclear. Our study reveals that ML supplement not only alters lipid metabolism including glycerol phospholipid, ether lipid as well as sphingolipid metabolism, which may help to improve immunity but also promote fatty acid degradation as well as ß oxidation to achieve the effect of fat reduction.

Increased transcriptional elongation and RNA stability of GPCR ligand binding genes unveiled via RNA polymerase II degradation.

RNA polymerase II drives mRNA gene expression, yet our understanding of Pol II degradation is limited. Using auxin-inducible degron, we degraded Pol II's RPB1 subunit, resulting in global repression. Surprisingly, certain genes exhibited increased RNA levels post-degradation. These genes are associated with GPCR ligand binding and are characterized by being less paused and comprising polycomb-bound short genes. RPB1 degradation globally increased KDM6B binding, which was insufficient to explain specific gene activation. In contrast, RPB2 degradation repressed nearly all genes, accompanied by decreased H3K9me3 and SUV39H1 occupancy. We observed a specific increase in serine 2 phosphorylated Pol II and RNA stability for RPB1 degradation-upregulated genes. Additionally, α-amanitin or UV treatment resulted in RPB1 degradation and global gene repression, unveiling subsets of upregulated genes. Our findings highlight the activated transcription elongation and increased RNA stability of signaling genes as potential mechanisms for mammalian cells to counter RPB1 degradation during stress.

SIPAS: A Comprehensive Susceptibility Imaging Process and Analysis Studio.

Quantitative susceptibility mapping (QSM) is a rising MRI-based technology and quite a few QSM-related algorithms have been proposed to reconstruct maps of tissue susceptibility distribution from phase images. In this paper, we develop a comprehensive susceptibility imaging process and analysis studio (SIPAS) that can accomplish reliable QSM processing and offer a standardized evaluation system. Specifically, SIPAS integrates multiple methods for each step, enabling users to select algorithm combinations according to data conditions, and QSM maps could be evaluated by two aspects, including image quality indicators within all voxels and region-of-interest (ROI) analysis. Through a sophisticated design of user-friendly interfaces, the results of each procedure are able to be exhibited in axial, coronal, and sagittal views in real-time, meanwhile ROIs can be displayed in 3D rendering visualization. The accuracy and compatibility of SIPAS are demonstrated by experiments on multiple in vivo human brain datasets acquired from 3T, 5T, and 7T MRI scanners of different manufacturers. We also validate the QSM maps obtained by various algorithm combinations in SIPAS, among which the combination of iRSHARP and SFCR achieves the best results on its evaluation system. SIPAS is a comprehensive, sophisticated, and reliable toolkit that may prompt the QSM application in scientific research and clinical practice.

Disulfide bonds as a molecular switch of enzyme-activatable anticancer drug precise release for fluorescence imaging and enhancing tumor therapy.

Enzyme-activatable drug delivery systems have been developed for cancer diagnosis and therapy. However, targeted intracellular drug delivery is a challenge for precisely tumor imaging and therapy due to the increased stability of copolymer nanoparticles (NPs) is accompanied by a notable decrease in enzyme degradation. Herein, disulfide bond was designed as an enzyme-activatable molecular switch of SS-P(G2)2/DOX NPs. The copolymer NPs consists of polyvinylpyrrolidone (PVP) with disulfide bonds in the center and enzyme-degradable peptide dendrites (Phe-Lys) to form dendritic-linear-dendritic triblock copolymers (TBCs). The amphiphilic TBCs could be split into two identical amphiphilic diblock copolymers (DBCs) by glutathione (GSH) in cancer cells specifically while maintaining the same hydrophilic-lipophilic equilibrium. This structural transformation significantly reduced the stability of copolymer NPs and enhanced sensitivity of DOX release by cathepsin B-activated. Subsequently, the released DOX acted as an indicator of fluorescence imaging and chemotherapy drug for cancer cells. The polymeric NPs achieved excellent drug-loaded stability and prolonged blood circulation in vivo, and realized fluorescence imaging and specific cancer cell killing capabilities by responding to the overexpression of GSH and cathepsin B in tumor cells. Furthermore, the copolymer NPs demonstrated excellent blood compatibility and biosafety. Therefore, a novel strategy based on one tumor marker acting as the switch for another tumor microenvironment responsive drug delivery system could be designed for tumor intracellular imaging and chemotherapy.

Metabolomic and transcriptomic analysis of flavonoids biosynthesis mechanisms in mulberry fruit (Hongguo 2) under exogenous hormone treatments.

The mulberry fruit is prized for its superior nutrition value and abundant color due to its high flavone content. To enhance comprehension of flavone biogenesis induced by external hormones, we sprayed exogenous ethylene (ETH), indoleacetic acid (IAA) and spermine (SPM) on mulberry fruit (Hongguo 2) during its color-changed period. The levels of anthocyanin, titratable acid, soluble sugar and endogenous hormones were determined after hormone treatment, integrated transcriptome and metabolome analysis were performed for mechanism exploration. Our results indicated that exogenous ETH, SPM, and IAA play important roles in mulberry ripening, including acid reduction, sugar increase and flavonoid synthesis.

A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging.

Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from prolonged scan time. To alleviate this limitation, advanced fast MRI technology attracts extensive research interests. Recent deep learning has shown its great potential in improving image quality and reconstruction speed. Faithful coil sensitivity estimation is vital for MRI reconstruction. However, most deep learning methods still rely on pre-estimated sensitivity maps and ignore their inaccuracy, resulting in the significant quality degradation of reconstructed images. In this work, we propose a Joint Deep Sensitivity estimation and Image reconstruction network, called JDSI. During the image artifacts removal, it gradually provides more faithful sensitivity maps with high-frequency information, leading to improved image reconstructions. To understand the behavior of the network, the mutual promotion of sensitivity estimation and image reconstruction is revealed through the visualization of network intermediate results. Results on in vivo datasets and radiologist reader study demonstrate that, for both calibration-based and calibrationless reconstruction, the proposed JDSI achieves the state-of-the-art performance visually and quantitatively, especially when the acceleration factor is high. Additionally, JDSI owns nice robustness to patients and autocalibration signals.

Grafting seedling rootstock strengthens tolerance to drought stress in polyploid mulberry (Morus alba L.).

The economically adaptable mulberry (Morus alba L.) has a long history of grafting in China, yet the physiological mechanisms and advantages in drought tolerance remain unexplored. In our study, we investigated the responses of self-rooted 2X (diploid), 3X (triploid), and 4X (tetraploid) plants, as well as polyploid plants grafted onto diploid seedling rootstocks (2X/2X, 3X/2X, and 4X/2X) under drought stress. We found that self-rooted diploid plants exhibited the most severe phenotypic damage, lowest water retention, photosynthetic capacity, and the least effective osmotic stress adjustment compared to tetraploid and triploid plants. However, grafted diploid and triploid plants showed effective mitigation of drought-induced damage, with higher relative water content and improved soil water retention. Grafted plants also improved the photosystem response to drought stress through elevated photosynthetic potential, closed stomatal aperture, and faster recovery of chlorophyll biosynthesis in the leaves. Additionally, grafted plants altered osmotic protective compound levels, including starch, soluble sugar, and proline content, thereby enhancing drought resistance. Absolute quantification PCR indicated that the expression levels of proline synthesis-related genes in grafted plants were not influenced after drought stress, whereas they were significantly increased in self-rooted plants. Consequently, our findings support that self-rooted triploid and tetraploid mulberries exhibited superior drought resistance compared to diploid plants. Moreover, grafting onto seedling rootstocks enhanced tolerance against drought stress in diploid and triploid mulberry, but not in tetraploid. Our study provides valuable insights for a comprehensive analysis of physiological effects in response to drought stress between stem-roots and seedling rootstocks.

A spatially adaptive regularization based three-dimensional reconstruction network for quantitative susceptibility mapping.

Objective.Quantitative susceptibility mapping (QSM) is a new imaging technique for non-invasive characterization of the composition and microstructure ofin vivotissues, and it can be reconstructed from local field measurements by solving an ill-posed inverse problem. Even for deep learning networks, it is not an easy task to establish an accurate quantitative mapping between two physical quantities of different units, i.e. field shift in Hz and susceptibility value in ppm for QSM.Approach. In this paper, we propose a spatially adaptive regularization based three-dimensional reconstruction network SAQSM. A spatially adaptive module is specially designed and a set of them at different resolutions are inserted into the network decoder, playing a role of cross-modality based regularization constraint. Therefore, the exact information of both field and magnitude data is exploited to adjust the scale and shift of feature maps, and thus any information loss or deviation occurred in previous layers could be effectively corrected. The network encoding has a dynamic perceptual initialization, which enables the network to overcome receptive field intervals and also strengthens its ability to detect features of various sizes.Main results. Experimental results on the brain data of healthy volunteers, clinical hemorrhage and simulated phantom with calcification demonstrate that SAQSM can achieve more accurate reconstruction with less susceptibility artifacts, while perform well on the stability and generalization even for severe lesion areas.Significance. This proposed framework may provide a valuable paradigm to quantitative mapping or multimodal reconstruction.

Enzyme and pH dual responsive linear-dendritic block copolymer micelles based on a phenylalanyl-lysine motif and peripherally ketal-functionalized dendron as potential drug carriers.

Stimuli-responsive linear-dendritic block copolymers (LDBCs) have attracted significant research attention as novel drug carriers. We report here three generations of new enzyme and pH dual responsive linear-dendritic block copolymers (LDBCs) with a phenylalanyl-lysine (Phe-Lys) dipeptide linking hydrophilic linear poly(N-vinylpyrrolidone) (PNVP) and a hydrophobic peripherally ketal-functionalized dendron derived from 2,2'-bis(hydroxymethyl)propionic acid (bis-MPA). The LDBCs are synthesized via a combination of interchange of xanthates/reversible addition-fragmentation chain transfer (MADIX/RAFT) polymerization of N-vinylpyrrolidone (NVP) and "chain-first" strategy. Their structures are confirmed by 1H NMR spectra. The gel permeation chromatograph (GPC) analysis revealed that the LDBCs have a narrow molecular weight distribution (PDI ≤ 1.25). The amphiphilic LDBCs can self-assemble into spherical nanomicelles in aqueous solution. The presence of enzyme or/and the change of pH cause disassembly of micelles to release encapsulated cargos. The release rates of the guest molecules are faster in buffer solution at pH 5.0 than those upon the addition of the activating enzyme and can be fine-tuned by changing the generation of bis-MPA dendrons. The combination of enzyme and pH dual stimuli results in significantly accelerated and more complete release of the loaded hydrophobic guests. The cell viability assay confirmed the favorable biocompatibility until the LDBC micelle concentration reached 800 µg mL-1. These results indicate that the LDBCs can be considered as a good candidate for targeting drug delivery.

Protocol for quantitative analysis of RNA 3'-end processing induced by disassociated subunits using chromatin-associated RNA-seq data.

Sequencing chromatin-associated RNA using libraries from the chromatin fraction makes it possible to characterize RNA processing driven by disassociated subunits. Here, we present an experimental strategy and computational pipeline for processing chromatin-associated RNA-seq data to detect and quantify readthrough transcripts. We describe steps for constructing degron mouse embryonic stem cells, detecting readthrough genes, data processing, and data analysis. This protocol can be adapted to various biological scenarios and other types of nascent RNA-seq, such as TT-seq. For complete details on the use and execution of this protocol, please refer to Li et al. (2023).1.

Meet the authors: The Ji lab.

We talk to the Ji lab about their paper, "RNA Pol II preferentially regulates ribosomal protein expression by trapping disassociated subunits" (in this issue), lessons from their scientific journey so far, and what inspires them along their scientific paths.

RNA Pol II preferentially regulates ribosomal protein expression by trapping disassociated subunits.

RNA polymerase II (RNA Pol II) has been recognized as a passively regulated multi-subunit holoenzyme. However, the extent to which RNA Pol II subunits might be important beyond the RNA Pol II complex remains unclear. Here, fractions containing disassociated RPB3 (dRPB3) were identified by size exclusion chromatography in various cells. Through a unique strategy, i.e., "specific degradation of disassociated subunits (SDDS)," we demonstrated that dRPB3 functions as a regulatory component of RNA Pol II to enable the preferential control of 3' end processing of ribosomal protein genes directly through its N-terminal domain. Machine learning analysis of large-scale genomic features revealed that the little elongation complex (LEC) helps to specialize the functions of dRPB3. Mechanistically, dRPB3 facilitates CBC-PCF11 axis activity to increase the efficiency of 3' end processing. Furthermore, RPB3 is dynamically regulated during development and diseases. These findings suggest that RNA Pol II gains specific regulatory functions by trapping disassociated subunits in mammalian cells.

Accurate Classification and Prediction of Acute Myocardial Infarction through an ARMD Procedure.

The risk stratification of acute myocardial infarction (AMI) patients is of prime importance for clinical management and prognosis assessment. Thus, we propose an ensemble machine learning analysis procedure named ADASYN-RFECV-MDA-DNN (ARMD) to address sample-unbalanced problems and enable stratification and prediction of AMI outcomes. The ARMD analysis procedure was applied to the NMR data of sera from 534 AMI-related subjects in four categories with an extremely imbalanced sample proportion. Firstly, the adaptive synthetic sampling (ADASYN) algorithm was used to address the issue of the original sample imbalance. Secondly, the recursive feature elimination with cross-validation (RFECV) processing and random forest mean decrease accuracy (RF-MDA) algorithm was performed to identify the differential metabolites corresponding to each AMI outcome. Finally, the deep neural network (DNN) was employed to classify and predict AMI events, and its performance was evaluated by comparing the four traditional machine learning methods. Compared with the other four machine learning models, DNN presented consistent superiority in almost all of the model parameters including precision, f1-score, sensitivity, specificity, area under the receiver operating characteristic curve (AUC), and classification accuracy, highlighting the potential of deep learning in classification and stratification of clinical diseases. The ARMD analysis procedure was a practical analysis tool for supervised classification and regression modeling of clinical diseases.

A latent code based multi-variable modulation network for susceptibility mapping.

Quantitative susceptibility mapping (QSM) is a technique for obtaining quantitative information on tissue susceptibility and has shown promising potential for clinical applications, in which the magnetic susceptibility is calculated by solving an ill-posed inverse problem. Recently, deep learning-based methods are proposed to address this issue, but the diversity of data distribution was not well considered, and thus the model generalization is limited in clinical applications. In this paper, we propose a Latent Code based Multi-Variable modulation network for QSM reconstruction (LCMnet). Particularly, a specific modulation module is exploited to incorporate three variables, i.e., field map, magnitude image, and initial susceptibility. The latent code in the modulated convolution is learned from feature maps of the field data using the encoder-decoder framework. The susceptibility map pre-estimated from simple thresholding is the constant input of the module, thereby enhancing the network stability and accelerating training convergence. As another input, multi-level features generated by a cross-fusion block integrate the information of field and magnitude data effectively. Experimental results on in vivo human brain data, challenge data, clinical data and synthetic data demonstrate that the proposed method LCMnet can achieve outstanding performance on accurate susceptibility measurement and also excellent generalization.

Targeted protein degradation reveals RNA Pol II heterogeneity and functional diversity.

RNA polymerase II (RNA Pol II) subunits are thought to be involved in various transcription-associated processes, but it is unclear whether they play different regulatory roles in modulating gene expression. Here, we performed nascent and mature transcript sequencing after the acute degradation of 12 mammalian RNA Pol II subunits and profiled their genomic binding sites and protein interactomes to dissect their molecular functions. We found that RNA Pol II subunits contribute differently to RNA Pol II cellular localization and transcription processes and preferentially regulate RNA processing (such as RNA splicing and 3' end maturation). Genes sensitive to the depletion of different RNA Pol II subunits tend to be involved in diverse biological functions and show different RNA half-lives. Sequences, associated protein factors, and RNA structures are correlated with RNA Pol II subunit-mediated differential gene expression. These findings collectively suggest that the heterogeneity of RNA Pol II and different genes appear to depend on some of the subunits.

Single-shot multi-parametric mapping based on multiple overlapping-echo detachment (MOLED) imaging.

Multi-parametric quantitative magnetic resonance imaging (mqMRI) allows the characterization of multiple tissue properties non-invasively and has shown great potential to enhance the sensitivity of MRI measurements. However, real-time mqMRI during dynamic physiological processes or general motions remains challenging. To overcome this bottleneck, we propose a novel mqMRI technique based on multiple overlapping-echo detachment (MOLED) imaging, termed MQMOLED, to enable mqMRI in a single shot. In the data acquisition of MQMOLED, multiple MR echo signals with different multi-parametric weightings and phase modulations are generated and acquired in the same k-space. The k-space data is Fourier transformed and fed into a well-trained neural network for the reconstruction of multi-parametric maps. We demonstrated the accuracy and repeatability of MQMOLED in simultaneous mapping apparent proton density (APD) and any two parameters among T2, T2*, and apparent diffusion coefficient (ADC) in 130-170 ms. The abundant information delivered by the multiple overlapping-echo signals in MQMOLED makes the technique potentially robust to system imperfections, such as inhomogeneity of static magnetic field or radiofrequency field. Benefitting from the single-shot feature, MQMOLED exhibits a strong motion tolerance to the continuous movements of subjects. For the first time, it captured the synchronous changes of ADC, T2, and T1-weighted APD in contrast-enhanced perfusion imaging on patients with brain tumors, providing additional information about vascular density to the hemodynamic parametric maps. We expect that MQMOLED would promote the development of mqMRI technology and greatly benefit the applications of mqMRI, including therapeutics and analysis of metabolic/functional processes.

Quantitative Proteomics and Functional Characterization Reveal That Glutathione Peroxidases Act as Important Antioxidant Regulators in Mulberry Response to Drought Stress.

Mulberry (Morus alba L.) has been an economically important food crop for the domesticated silkworm, Bombyx mori, in China for more than 5000 years. However, little is known about the mechanism underlying mulberry response to environmental stress. In this study, quantitative proteomics was applied to elucidate the molecular mechanism of drought response in mulberry. A total of 604 differentially expressed proteins (DEPs) were identified via LC-MS/MS. The proteomic profiles associated with antioxidant enzymes, especially five glutathione peroxidase (GPX) isoforms, as a scavenger of reactive oxygen species (ROS), were systematically increased in the drought-stressed mulberry. This was further confirmed by gene expression and enzymatic activity. Furthermore, overexpression of the GPX isoforms led to enhancements in both antioxidant system and ROS-scavenging capacity, and greater tolerance to drought stress in transgenic plants. Taken together, these results indicated that GPX-based antioxidant enzymes play an important role in modulating mulberry response to drought stress, and higher levels of GPX can improve drought tolerance through enhancing the capacity of the antioxidant system for ROS scavenging.

Anti-Inflammatory Activity of Mulberry Leaf Flavonoids In Vitro and In Vivo.

Mulberry (Morus alba L.) is a flowering tree traditionally used in Chinese herbal medicine. Mulberry leaf flavonoids (MLFs) have been reported to exert important anti-inflammatory and antioxidant properties. The purpose of this study was to select the MLF with the best anti-inflammatory and antioxidative activities from MLFs eluted by different ethanol concentrations (30%, 50%, and 75%) and explore its pharmacological properties. Three types of MLFs inhibited the production of nitric oxide (NO), prostaglandin E2 (PGE2), inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), and inflammatory cytokines in lipopolysaccharide (LPS)-induced RAW 264.7 cells. All MLFs boosted the antioxidative capacity by decreasing the reactive oxygen species (ROS) production and the scavenging of 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radicals and improving the metal ion chelating activity and reducing power. The results revealed that the MLFs eluted by 30% ethanol exhibited the best anti-inflammatory and antioxidative activities. A nontargeted metabolomic analysis was used to analyze 24 types of differential flavonoids between the MLFs. Quercetin, kaempferol, and their derivatives in 30%MLF were more abundant than the other two MLFs. Furthermore, we evaluated the pharmacological activities of 30%MLF in dextran sodium sulfate (DSS)-induced ulcerative colitis (UC) mice. The 30%MLF could alleviate the clinical symptoms, reduce the secretion of inflammatory cytokines, and inhibit the activation of the inflammatory pathway in DSS-induced colitis mice. This study will provide valuable information for the development of MLFs eluted by 30% ethanol as a functional food.

Leaf-Associated Epiphytic Fungi of Gingko biloba, Pinus bungeana and Sabina chinensis Exhibit Delicate Seasonal Variations.

Plant-leaf surface on Earth harbors complex microbial communities that influence plant productivity and health. To gain a detailed understanding of the assembly and key drivers of leaf microbial communities, especially for leaf-associated fungi, we investigated leaf-associated fungal communities in two seasons for three plant species at two sites by high-throughput sequencing. The results reveal a strong impact of growing season and plant species on fungal community composition, exhibiting clear temporal patterns in abundance and diversity. For the deciduous tree Gingko biloba, the number of enriched genera in May was much higher than that in October. The number of enriched genera in the two evergreen trees Pinus bungeana and Sabina chinensis was slightly higher in October than in May. Among the genus-level biomarkers, the abundances of Alternaria, Cladosporium and Filobasidium were significantly higher in October than in May in the three tree species. Additionally, network correlations between the leaf-associated fungi of G. biloba were more complex in May than those in October, containing extra negative associations, which was more obvious than the network correlation changes of leaf-associated fungi of the two evergreen plant species. Overall, the fungal diversity and community composition varied significantly between different growing seasons and host plant species.

Optimized Ensiling Conditions and Microbial Community in Mulberry Leaves Silage With Inoculants.

Mulberry leaves (ML) are a promising alternative fodder source due to their high protein content and the abundance of active components. A test of three inoculants in various combinations revealed that high-quality ML silage was produced at an inoculum ratio of 1:1:0 (50% Saccharomyces cerevisiae, 50% Lactobacillus plantarum, and 0% Bacillus subtilis). Using dry matter (DM) loss, pH, ammonia-N and amino acid contents, total antioxidant activity, and total flavonoids content to evaluate silage quality, this inoculant mixture was shown to produce high-quality silage within a range of inoculum size (5-15%), moisture contents (50-67%), ensiling temperatures (27-30°C), and ensiling duration (14-30 days). A third trial comparing silages produced after 30 days at 28°C and 50% moisture content revealed that silage E, prepared using an L. plantarum inoculant alone, displayed the lowest DM loss and pH, and low bacterial diversity, and it was dominated by Lactobacillus (88.6%), with low abundance of Enterobacter (6.17%). In contrast, silage B5, prepared with equal ratios of L. plantarum and S. cerevisiae, was dominated by Enterococcus (67.16%) and Lactobacillus (26.94%), with less marked yeast persistence, and reducing the DM content from 50 to 40% altered these relative abundances to 5.47 and 60.61, respectively. Control silages produced without an inoculant had the highest pH and ammonia-N content (indicative of poor quality), had the lowest antioxidant activity, had higher bacterial diversity, and were dominated by Carnobacterium (74.28%) and Enterococcus (17.3%). In summary, ensiling of ML conditions with proper inoculants yielded high-quality silage with a favorable microbial community composition.