Metabolic differences in MSTN and FGF5 dual-gene edited sheep muscle cells during myogenesis.

Dynamic metabolic reprogramming occurs at different stages of myogenesis and contributes to the fate determination of skeletal muscle satellite cells (MuSCs). Accumulating evidence suggests that mutations in myostatin (MSTN) have a vital role in regulating muscle energy metabolism. Here, we explored the metabolic reprogramming in MuSCs and myotube cells in MSTN and FGF5 dual-gene edited sheep models prepared previously, and also focused on the metabolic alterations during myogenic differentiation of MuSCs. Our study revealed that the pathways of nucleotide metabolism, pantothenate and CoA biosynthesis were weakened, while the unsaturated fatty acids biosynthesis were strengthened during myogenic differentiation of sheep MuSCs. The MSTN and FGF5 dual-gene editing mainly inhibited nucleotide metabolism and biosynthesis of unsaturated fatty acids in sheep MuSCs, reduced the number of lipid droplets in per satellite cell, and promoted the pentose phosphate pathway, and the interconversion of pentose and glucuronate. The MSTN and FGF5 dual-gene editing also resulted in the inhibition of nucleotide metabolism and TCA cycle pathway in differentiated myotube cells. The differential metabolites we identified can be characterized as biomarkers of different cellular states, and providing a new reference for MSTN and FGF5 dual-gene editing in regulation of muscle development. It may also provide a reference for the development of muscle regeneration drugs targeting biomarkers.

Electrochemically Dealloying Engineering toward Integrated Monolithic Electrodes with Superior Electrochemical Li-Storage Properties.

Integrated monolithic electrodes (IMEs) free of inactive components demonstrate great potential in boosting energy-power densities and cycling life of lithium-ion batteries. However, their practical applications are significantly limited by low active substance loading (< 4.0 mg cm-2 and 1.0 g cm-3), complicated manufacturing process, and high fabrication cost. Herein, employing industrial Cu-Mn alloy foil as a precursor, a simple neutral salt solution-mediated electrochemical dealloying strategy is proposed to address such problems. The resultant Cu-Mn IMEs achieve not only a significantly larger active material loading due to the in situ generated Cu2O and MnOx (ca. 16.0 mg cm-2 and 1.78 g cm-3), simultaneously fast transport of ions and electrons due to the well-formed nanoporous structure and built-in Cu current collector, but also high structural stability due to the interconnected ligaments and suitable free space to relieve the volume expansion upon lithiation. As a result, they demonstrate remarkable performances including large specific capacities (> 5.7 mAh cm-2), remarkable pseudocapacitive effect despite the battery-type constitutes, long cycling life, and good working condition in a lithium-ion full cell. This study sheds new light on the further development of IMEs, enriches the existing dealloying techniques, and builds a bridge between the two.

Enhancing ferroelectric performance in hafnia-based MFIS capacitor through interface passivation and bulk doping.

In recent times, there has been a notable surge of interests in hafnia (HfO2)-based ferroelectrics, primarily due to their remarkable ferroelectric properties employed in ultra-thin configurations, alongside their compatibility with the conventional CMOS manufacturing process. In order to harness the full potential of HfO2-based films for high-performance non-volatile memory applications, it is imperative to enhance their ferroelectric characteristics and durability. This study introduces a straightforward approach aimed at augmenting the ferroelectric performance of HfxZr1-xO2(HZO) films deposited on silicon (Si) substrates through the engineering of oxygen vacancies (VO). The results of this endeavor demonstrate a significant enhancement in ferroelectric performance, characterized by a 2Pr value of 47µC cm-2and impressive endurance, enduring up to 108cycles under an 8 MV cm-1electric field without the need of a wake-up process. This marked improvement can be attributed to a dual-pronged approach, involving the incorporation of an Al2O3interlayer and the introduction of Al atoms into the HZO film. The Al2O3interlayer primarily serves to mitigate the presence of oxygen vacancies at the interface, while the introduction of Al dopants elevates the concentration of oxygen vacancies within the bulk material. This modulation of oxygen vacancy concentration proves instrumental in facilitating the formation of a ferroelectric o-III phase within the HZO-based films, thereby further augmenting their ferroelectric performance. This innovative and effective strategy offers an alternative avenue for enhancing the ferroelectric properties of materials characterized by a fluorite crystal structure.

Potassium transporter OsHAK9 regulates seed germination under salt stress by preventing gibberellin degradation through mediating OsGA2ox7 in rice.

Soil salinity has a major impact on rice seed germination, severely limiting rice production. Herein, a rice germination defective mutant under salt stress (gdss) was identified by using chemical mutagenesis. The GDSS gene was detected via MutMap and shown to encode potassium transporter OsHAK9. Phenotypic analysis of complementation and mutant lines demonstrated that OsHAK9 was an essential regulator responsible for seed germination under salt stress. OsHAK9 is highly expressed in germinating seed embryos. Ion contents and non-invasive micro-test technology results showed that OsHAK9 restricted K+ efflux in salt-exposed germinating seeds for the balance of K+/Na+. Disruption of OsHAK9 significantly reduced gibberellin 4 (GA4) levels, and the germination defective phenotype of oshak9a was partly rescued by exogenous GA3 treatment under salt stress. RNA sequencing (RNA-seq) and real-time quantitative polymerase chain reaction analysis demonstrated that the disruption of OsHAK9 improved the GA-deactivated gene OsGA2ox7 expression in germinating seeds under salt stress, and the expression of OsGA2ox7 was significantly inhibited by salt stress. Null mutants of OsGA2ox7 created using clustered, regularly interspaced, short palindromic repeat (CRISPR)/CRISPR-associated nuclease 9 approach displayed a dramatically increased seed germination ability under salt stress. Overall, our results highlight that OsHAK9 regulates seed germination performance under salt stress involving preventing GA degradation by mediating OsGA2ox7, which provides a novel clue about the relationship between GA and OsHAKs in rice.

Natural Microbial Reactor-Based Sensing Platform for Highly Sensitive Detection of Inorganic Arsenic in Rice Grains.

Rice is a major dietary source of inorganic arsenic (iAs), a highly toxic arsenical that accumulates in rice and poses health risks to rice-based populations. However, the availability of detection methods for iAs in rice grains is limited. In this study, we developed a novel approach utilizing a natural bacterial biosensor, Escherichia coli AW3110 (pBB-ArarsR-mCherry), in conjunction with amylase hydrolysis for efficient extraction, enabling high-throughput and quantitative detection of iAs in rice grains. The biosensor exhibits high specificity for arsenic and distinguishes between arsenite [As(III)] and arsenate [As(V)] by modulating the concentration of PO43- in the detection system. We determined the iAs concentrations in 19 rice grain samples with varying total As concentrations and compared our method with the standard technique of microwave digestion coupled with HPLC-ICP-MS. Both methods exhibited comparable results, without no significant bias in the concentrations of As(III) and As(V). The whole-cell biosensor demonstrated excellent reproducibility and a high signal-to-noise ratio, achieving a limit of detection of 16 µg kg-1 [As(III)] and 29 µg kg-1 [As(V)]. These values are considerably lower than the maximum allowable level (100 µg kg-1) for infant rice supplements established by the European Union. Our straightforward sensing strategy presents a promising tool for detecting iAs in other food samples.

Sparsity-guided multiple functional connectivity patterns for classification of schizophrenia via convolutional network.

The explorations of brain functional connectivity network (FCN) using resting-state functional magnetic resonance imaging can provide crucial insights into discriminative analysis of neuropsychiatric disorders, such as schizophrenia (SZ). Pearson's correlation (PC) is widely used to construct a densely connected FCN which may overlook some complex interactions of paired regions of interest (ROIs) under confounding effect of other ROIs. Although the method of sparse representation takes into account this issue, it penalizes each edge equally, which often makes the FCN look like a random network. In this paper, we establish a new framework, called convolutional neural network with sparsity-guided multiple functional connectivity, for SZ classification. The framework consists of two components. (1) The first component constructs a sparse FCN by integrating PC and weighted sparse representation (WSR). The FCN retains the intrinsic correlation between paired ROIs, and eliminates false connection simultaneously, resulting in sparse interactions among multiple ROIs with the confounding effect regressed out. (2) In the second component, we develop a functional connectivity convolution to learn discriminative features for SZ classification from multiple FCNs by mining the joint spatial mapping of FCNs. Finally, an occlusion strategy is employed to explore the contributive regions and connections, to derive the potential biomarkers in identifying associated aberrant connectivity of SZ. The experiments on SZ identification verify the rationality and advantages of our proposed method. This framework also can be used as a diagnostic tool for other neuropsychiatric disorders.

Using RegGAN to generate synthetic CT images from CBCT images acquired with different linear accelerators.

BACKGROUND: The goal was to investigate the feasibility of the registration generative adversarial network (RegGAN) model in image conversion for performing adaptive radiation therapy on the head and neck and its stability under different cone beam computed tomography (CBCT) models. METHODS: A total of 100 CBCT and CT images of patients diagnosed with head and neck tumors were utilized for the training phase, whereas the testing phase involved 40 distinct patients obtained from four different linear accelerators. The RegGAN model was trained and tested to evaluate its performance. The generated synthetic CT (sCT) image quality was compared to that of planning CT (pCT) images by employing metrics such as the mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). Moreover, the radiation therapy plan was uniformly applied to both the sCT and pCT images to analyze the planning target volume (PTV) dose statistics and calculate the dose difference rate, reinforcing the model's accuracy. RESULTS: The generated sCT images had good image quality, and no significant differences were observed among the different CBCT modes. The conversion effect achieved for Synergy was the best, and the MAE decreased from 231.3 ± 55.48 to 45.63 ± 10.78; the PSNR increased from 19.40 ± 1.46 to 26.75 ± 1.32; the SSIM increased from 0.82 ± 0.02 to 0.85 ± 0.04. The quality improvement effect achieved for sCT image synthesis based on RegGAN was obvious, and no significant sCT synthesis differences were observed among different accelerators. CONCLUSION: The sCT images generated by the RegGAN model had high image quality, and the RegGAN model exhibited a strong generalization ability across different accelerators, enabling its outputs to be used as reference images for performing adaptive radiation therapy on the head and neck.

Transforming growth factor-ß receptor type 2 is required for heparin-binding protein-induced acute lung injury and vascular leakage for transforming growth factor-ß/Smad/Rho signaling pathway activation.

Heparin-binding protein (HBP), as a granule protein secreted by polymorphonuclear neutrophils, participates in the pathophysiological process of sepsis. It has been reported that HBP is a biomarker of sepsis related to the severity of septic shock and organ dysfunction. HBP binds to vascular endothelial cells as a primary target site. However, it is still unclear whether HBP-binding protein receptors exist on the surface of endothelial cells. The effect of HBP on vascular permeability in sepsis and its mechanism needs to be explored. We conducted in vivo and in vitro studies and demonstrated that HBP binds to transforming growth factor-ß receptor type 2 (TGF-ß-R2) as a ligand. Glutathione S-transferase pull-down analysis revealed that HBP mainly interacts with the extracellular domain of TGF-ß-R2. HBP induces acute lung injury and vascular leakage via activation of the TGF-ß/SMAD2/3 signaling pathway. A permeability assay suggested that TGF-ß-R2 is necessary for HBP-induced increased permeability. We also defined the role of HBP and its potential membrane receptor TGF-ß-R2 in the blood-gas barrier in the pathogenesis of HBP-related acute lung injury.

MRI-based two-stage deep learning model for automatic detection and segmentation of brain metastases.

OBJECTIVES: To develop and validate a two-stage deep learning model for automatic detection and segmentation of brain metastases (BMs) in MRI images. METHODS: In this retrospective study, T1-weighted (T1) and T1-weighted contrast-enhanced (T1ce) MRI images of 649 patients who underwent radiotherapy from August 2019 to January 2022 were included. A total of 5163 metastases were manually annotated by neuroradiologists. A two-stage deep learning model was developed for automatic detection and segmentation of BMs, which consisted of a lightweight segmentation network for generating metastases proposals and a multi-scale classification network for false-positive suppression. Its performance was evaluated by sensitivity, precision, F1-score, dice, and relative volume difference (RVD). RESULTS: Six hundred forty-nine patients were randomly divided into training (n = 295), validation (n = 99), and testing (n = 255) sets. The proposed two-stage model achieved a sensitivity of 90% (1463/1632) and a precision of 56% (1463/2629) on the testing set, outperforming one-stage methods based on a single-shot detector, 3D U-Net, and nnU-Net, whose sensitivities were 78% (1276/1632), 79% (1290/1632), and 87% (1426/1632), and the precisions were 40% (1276/3222), 51% (1290/2507), and 53% (1426/2688), respectively. Particularly for BMs smaller than 5 mm, the proposed model achieved a sensitivity of 66% (116/177), far superior to one-stage models (21% (37/177), 36% (64/177), and 53% (93/177)). Furthermore, it also achieved high segmentation performance with an average dice of 81% and an average RVD of 20%. CONCLUSION: A two-stage deep learning model can detect and segment BMs with high sensitivity and low volume error. KEY POINTS: • A two-stage deep learning model based on triple-channel MRI images identified brain metastases with 90% sensitivity and 56% precision. • For brain metastases smaller than 5 mm, the proposed two-stage model achieved 66% sensitivity and 22% precision. • For segmentation of brain metastases, the proposed two-stage model achieved a dice of 81% and a relative volume difference (RVD) of 20%.

High-transmission and large group delay terahertz triple-band electromagnetically induced transparency in a metal-perovskite hybrid metasurface.

A high-transmission and large group delay terahertz triple-band electromagnetically induced transparency (EIT) effect is obtained in a metal-perovskite hybrid metasurface, which consists of a cross metal (CM), a pair of square metal frames (SMFs), and a pair of square split rings (SSRs). The results reveal that the transmission amplitudes of three transparent windows are 0.83, 0.9, and 0.89. The maximum values of group delays at three transparent windows are 7.64 ps, 4.07 ps, and 4.27 ps. The multipole scattering theory shows that the first and third transparent windows are created by the coupling between the electric dipole and toroidal dipole, and the second transparent window is created by the electric dipoles. The triple-band EIT effect can be dynamically controlled by adjusting the conductivity of perovskite while the modulation depths are 49.4%, 41%, and 31.5%. Moreover, the slow light effect can also be tunable by tuning the conductivity of perovskite while the modulation depths are 87.8%, 65.6%, and 68.4%. Our study puts forward a novel design concept for multi-band EIT effect and shows great prospects in the application of multi-band devices.

Polarization-insensitive electromagnetically induced transparency and its sensing performance based on spoof localized surface plasmons in vanadium dioxide-based terahertz metasurfaces.

The multi-layer terahertz metasurfaces are designed to achieve polarization-insensitive electromagnetically induced transparency (EIT) effect and its sensing performance based on spoof localized surface plasmons (S-LSPs). The unit cell of the proposed metasurfaces is comprised of a metallic spiral (MS) structure, square metal frame (SMF) structure, and vanadium dioxide (VO2) layer. The EIT effect is realized by the bright-bright coupling between spoof electric localized surface plasmons (S-ELSPs) and electric dipole, which can be proved by the multipole scattering theory. The maximum value of transmission amplitude at the transparent window is 0.91, and the modulation depth can reach 51% by adjusting the conductivity of VO2. The theoretical results based on the two-particle model show excellent agreement with the simulated results. Moreover, the change of polarization angle has little effect on the EIT effect and the proposed metasurfaces show polarization-insensitive characteristics. The slow light effect of the proposed metasurfaces can also be dynamically controlled by tuning the conductivity of VO2. Due to the high Q value of the transparent window, the proposed metasurfaces exhibit excellent sensing performance, and the sensitivity is 0.172 THz RIU-1. Our study provides a method for the fabrication of EIT metasurfaces and has a broad application prospect in slow light devices, sensors, and modulators.

Tunable and three-dimensional dual-band metamaterial absorber based on electromagnetically induced transparency with vanadium dioxide.

A tunable and three-dimensional dual-band metamaterial absorber based on electromagnetically induced transparency (EIT) is proposed. The unit cell of the metamaterial absorber consisted of a cut wire (CW), two split ring resonators (SRRs), a metal plate and a patterned vanadium dioxide (VO2) film. The two absorption peaks could be dynamically controlled by tuning the conductivity of VO2 with the maximum absorptions of 97.5% at 1.05 THz and 96.5% at 1.16 THz. The physical mechanism of the metamaterial absorber was explained by the electric field, magnetic field, power loss density and surface current distributions. In addition, the metamaterial absorber exhibited a wide polarization angle for y-polarization wave and x-polarization wave and showed good robustness against oblique incidence. Moreover, the metamaterial absorber exhibited a high fault tolerance with a variation in the geometric parameters. Our work provides a novel method for the fabrication of multi-band metamaterial absorbers and has promising applications in terahertz sensors, modulators and filters.

Nitrifier adaptation to low energy flux controls inventory of reduced nitrogen in the dark ocean.

Ammonia oxidation to nitrite and its subsequent oxidation to nitrate provides energy to the two populations of nitrifying chemoautotrophs in the energy-starved dark ocean, driving a coupling between reduced inorganic nitrogen (N) pools and production of new organic carbon (C) in the dark ocean. However, the relationship between the flux of new C production and the fluxes of N of the two steps of oxidation remains unclear. Here, we show that, despite orders-of-magnitude difference in cell abundances between ammonia oxidizers and nitrite oxidizers, the two populations sustain similar bulk N-oxidation rates throughout the deep waters with similarly high affinities for ammonia and nitrite under increasing substrate limitation, thus maintaining overall homeostasis in the oceanic nitrification pathway. Our observations confirm the theoretical predictions of a redox-informed ecosystem model. Using balances from this model, we suggest that consistently low ammonia and nitrite concentrations are maintained when the two populations have similarly high substrate affinities and their loss rates are proportional to their maximum growth rates. The stoichiometric relations between the fluxes of C and N indicate a threefold to fourfold higher C-fixation efficiency per mole of N oxidized by ammonia oxidizers compared to nitrite oxidizers due to nearly identical apparent energetic requirements for C fixation of the two populations. We estimate that the rate of chemoautotrophic C fixation amounts to ∼1 × 1013 to ∼2 × 1013 mol of C per year globally through the flux of ∼1 × 1014 to ∼2 × 1014 mol of N per year of the two steps of oxidation throughout the dark ocean.

Oridonin ameliorates acetaminophen-induced acute liver injury through ATF4/PGC-1α pathway.

Acetaminophen (APAP) overdose-induced acute liver injury (ALI) causes hepatocyte cell death, oxidative stress, and inflammation. Oridonin (Ori), a covalent NLRP3-inflammasome inhibitor, ameliorates APAP-induced ALI through an unclear molecular mechanism. This study found that Ori decreased hepatic cytochrome P450 2E1 level and increased glutathione content to prevent APAP metabolism, and then reduced the necrotic area, improved liver function, and inhibited APAP-induced proinflammatory cytokines and oxidative stress. Ori also decreased activating transcription factor 4 (ATF4) protein levels and increased peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) to reduce APAP-induced endoplasmic reticulum stress activation and mitochondrial dysfunction. Furthermore, western blot and luciferase assay found that ATF4 inhibited transcription in the PGC-1α promoter -507 to -495 region to reduce PGC-1α levels, while ATF4 knockdown neutralized the hepatoprotective effect of Ori. Molecular docking showed that Ori bound to ATF4's amino acid residue glutamate 302 through 6, 7, and 18 hydroxyl bands. Our findings demonstrated that Ori prevented metabolic activation of APAP and further inhibited the ATF4/PGC-1α pathway to alleviate APAP overdose-induced hepatic toxicity, which illuminated its potential therapeutic effects on ALI.

An Effective Approach to Improve the Automatic Segmentation and Classification Accuracy of Brain Metastasis by Combining Multi-phase Delay Enhanced MR Images.

The objective of this study is to analyse the diffusion rule of the contrast media in multi-phase delayed enhanced magnetic resonance (MR) T1 images using radiomics and to construct an automatic classification and segmentation model of brain metastases (BM) based on support vector machine (SVM) and Dpn-UNet. A total of 189 BM patients with 1047 metastases were enrolled. Contrast-enhanced MR images were obtained at 1, 3, 5, 10, 18, and 20 min following contrast medium injection. The tumour target volume was delineated, and the radiomics features were extracted and analysed. BM segmentation and classification models in the MR images with different enhancement phases were constructed using Dpn-UNet and SVM, and differences in the BM segmentation and classification models with different enhancement times were compared. (1) The signal intensity for BM decreased with time delay and peaked at 3 min. (2) Among the 144 optimal radiomics features, 22 showed strong correlation with time (highest R-value = 0.82), while 41 showed strong correlation with volume (highest R-value = 0.99). (3) The average dice similarity coefficients of both the training and test sets were the highest at 10 min for the automatic segmentation of BM, reaching 0.92 and 0.82, respectively. (4) The areas under the curve (AUCs) for the classification of BM pathology type applying single-phase MRI was the highest at 10 min, reaching 0.674. The AUC for the classification of BM by applying the six-phase image combination was the highest, reaching 0.9596, and improved by 42.3% compared with that by applying single-phase images at 10 min. The dynamic changes of contrast media diffusion in BM can be reflected by multi-phase delayed enhancement based on radiomics, which can more objectively reflect the pathological types and significantly improve the accuracy of BM segmentation and classification.

[Alterations of ß-γ coupling of scalp electroencephalography during epilepsy].

Uncovering the alterations of neural interactions within the brain during epilepsy is important for the clinical diagnosis and treatment. Previous studies have shown that the phase-amplitude coupling (PAC) can be used as a potential biomarker for locating epileptic zones and characterizing the transition of epileptic phases. However, in contrast to the θ-γ coupling widely investigated in epilepsy, few studies have paid attention to the ß-γ coupling, as well as its potential applications. In the current study, we use the modulation index (MI) to calculate the scalp electroencephalography (EEG)-based ß-γ coupling and investigate the corresponding changes during different epileptic phases. The results show that the ß-γ coupling of each brain region changes with the evolution of epilepsy, and in several brain regions, the ß-γ coupling decreases during the ictal period but increases in the post-ictal period, where the differences are statistically significant. Moreover, the alterations of ß-γ coupling between different brain regions can also be observed, and the strength of ß-γ coupling increases in the post-ictal period, where the differences are also significant. Taken together, these findings not only contribute to understanding neural interactions within the brain during the evolution of epilepsy, but also provide a new insight into the clinical treatment.

Astrocyte reactivation in medial prefrontal cortex contributes to obesity-promoted depressive-like behaviors.

BACKGROUND: Little is known about how the obesogenic environment influences emotional states associated with glial responses and neuronal function. Here, we investigated glial reactivation and neuronal electrophysiological properties in emotion-related brain regions of high-fat diet (HFD) and ob/ob mice under chronic stress. METHODS: The glial reactivation and neuronal activities in emotion-related brain regions were analyzed among normal diet mice (ND), HFD mice, wild-type mice, and ob/ob mice. To further activate or inhibit astrocytes in medial prefrontal cortex (mPFC), we injected astrocytes specific Gq-AAV or Gi-AAV into mPFC and ongoing treated mice with CNO. RESULTS: The results showed that obesogenic factors per se had no significant effect on neuronal activities in emotion-related brain regions, or on behavioral performance. However, exposure to a chronic stressor profoundly reduced the frequency of spontaneous inhibitory postsynaptic currents (sIPSCs) and spontaneous excitatory postsynaptic currents (sEPSCs) in the mPFC; depressive-like behaviors were seen, accompanied by significant upregulation of astrocyte reactivation. We identified resilient and susceptible mice among chronic social defeat stress-exposed HFD mice. As expected, astrocyte reactivity was upregulated, while neuronal activity was depressed, in the mPFC of susceptible compared to resilient mice. Furthermore, activating astrocytes resulted in similar levels of neuronal activity and depressive-like behaviors between resilient and susceptible mice. Additionally, inhibiting astrocyte reactivation in the mPFC of HFD mice upregulated neuronal activities and inhibited depressive-like behaviors. CONCLUSIONS: These observations indicate that obesogenic factors increase the risk of depression, and improve our understanding of the pathological relationship between obesity and depression.

Identification of OsPK5 involved in rice glycolytic metabolism and GA/ABA balance for improving seed germination via genome-wide association study.

Seed germination plays a pivotal role in the plant life cycle, and its precise regulatory mechanisms are not clear. In this study, 19 quantitative trait loci (QTLs) associated with rice seed germination were identified through genome-wide association studies (GWAS) of the following traits in 2016 and 2017: germination rate (GR) at 3, 5, and 7 days after imbibition (DAI) and germination index (GI). Two major stable QTLs, qSG4 and qSG11.1, were found to be associated with GR and GI over 2 continuous years. Furthermore, OsPK5, encoding a pyruvate kinase, was shown to be a crucial regulator of seed germination in rice, and might be a causal gene of the key QTL qSG11.1, on chromosome 11. Natural variation in OsPK5 function altered the activity of pyruvate kinase. The disruption of OsPK5 function resulted in slow germination and seedling growth during seed germination, blocked glycolytic metabolism, caused glucose accumulation, decreased energy levels, and affected the GA/ABA balance. Taken together, our results provide novel insights into the roles of OsPK5 in seed germination, and facilitate its application in rice breeding to improve seed vigour.

Distributions and trends of the global burden of COPD attributable to risk factors by SDI, age, and sex from 1990 to 2019: a systematic analysis of GBD 2019 data.

BACKGROUND: Global distributions and trends of the risk-attributable burdens of chronic obstructive pulmonary disease (COPD) have rarely been systematically explored. To guide the formulation of targeted and accurate strategies for the management of COPD, we analyzed COPD burdens attributable to known risk factors. METHODS: Using detailed COPD data from the Global Burden of Disease study 2019, we analyzed disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), and deaths attributable to each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. The population attributable fraction (PAF) and summary exposure value (SEV) of each risk factor are also presented. RESULTS: From 1990 to 2019, the age-standardized DALY and death rates of COPD attributable to smoking and household air pollution, occupational particles, secondhand smoke, and low temperature presented consistently declining trends in almost all socio-demographic index (SDI) regions. However, the decline in YLD was not as dramatic as that of the death rate. In contrast, the COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure showed undesirable increasing trends in the low- and low-middle-SDI regions. In addition, the age-standardized DALY and death rates attributable to each risk factor except household air pollution and low temperature were the highest in the low-middle-SDI region. In 2019, the COPD burden attributable to smoking ambient particulate matter, ozone, occupational particles, low and high temperature was obviously greater in males than in females. Meanwhile, the most important risk factors for female varied across regions (low- and low-middle-SDI regions: household air pollution; middle-SDI region: ambient particles; high-middle- and high-SDI region: smoking). CONCLUSIONS: Increasing trends of COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure in the low-middle- and low-SDI regions call for an urgent need to implement specific and effective measures. Moreover, considering the gender differences in COPD burdens attributable to some risk factors such as ambient particulate matter and ozone with similar SEV, further research on biological differences between sexes in COPD and relevant policy-making of disease prevention are required.

p75NTR Promotes Astrocyte Proliferation in Response to Cortical Stab Wound.

Astrogliosis after brain trauma can have a significant impact on functional recovery. However, little is known about the mechanisms underlying astrocyte proliferation and subsequent astrogliosis. In this study, we established a cortical stab wound injury mouse model and observed dramatic astrocyte activation and nerve growth factor receptor (p75NTR) upregulation near the lesion. We also found profound alterations in the cell cycle of astrocytes near the lesion, with a switch from a mitotically quiescent (G0) phase to the G2/M and S phases. However, no changes in the level of astrocyte apoptosis were observed. Cell cycle progression to the G2/M and S phases and CDK2 protein levels in response to cortical stab wound was inhibited after p75NTR knockdown in mouse astrocytes. Conversely, p75NTR overexpression in mouse astrocytes was sufficient in promoting cell cycle progression. In conclusion, our results suggested that p75NTR upregulation in astrocytes after brain injury induces cell cycle entry by promoting CDK2 expression and promoting astrocyte proliferation. Our findings provided a better understanding of astrocytic responses after cortical stab wound injury in mice.