A scalable approach to characterize pleiotropy across thousands of human diseases and complex traits using GWAS summary statistics.

Genome-wide association studies (GWASs) across thousands of traits have revealed the pervasive pleiotropy of trait-associated genetic variants. While methods have been proposed to characterize pleiotropic components across groups of phenotypes, scaling these approaches to ultra-large-scale biobanks has been challenging. Here, we propose FactorGo, a scalable variational factor analysis model to identify and characterize pleiotropic components using biobank GWAS summary data. In extensive simulations, we observe that FactorGo outperforms the state-of-the-art (model-free) approach tSVD in capturing latent pleiotropic factors across phenotypes while maintaining a similar computational cost. We apply FactorGo to estimate 100 latent pleiotropic factors from GWAS summary data of 2,483 phenotypes measured in European-ancestry Pan-UK BioBank individuals (N = 420,531). Next, we find that factors from FactorGo are more enriched with relevant tissue-specific annotations than those identified by tSVD (p = 2.58E-10) and validate our approach by recapitulating brain-specific enrichment for BMI and the height-related connection between reproductive system and muscular-skeletal growth. Finally, our analyses suggest shared etiologies between rheumatoid arthritis and periodontal condition in addition to alkaline phosphatase as a candidate prognostic biomarker for prostate cancer. Overall, FactorGo improves our biological understanding of shared etiologies across thousands of GWASs.

GVHD targets organoid-forming bile duct stem cells via a TGF-ß-dependent manner.

Graft-versus-host disease (GVHD) is a major life-threatening complication that occurs after allogeneic hematopoietic cell transplantation (HCT). While adult tissue stem cells have been identified as targets of GVHD in the skin and gut, their role in hepatic GVHD is yet to be clarified. In the current study, we explored the fate of bile duct stem cells (BDSCs), capable of generating liver organoids in vitro, during hepatic GVHD after allogeneic HCT. We observed a significant expansion of biliary epithelial cells (BECs) upon injury early after allogeneic HCT. Organoid-forming efficiency from the bile duct was also significantly increased early after allogeneic HCT. Subsequently, the organoid-forming efficiency from bile ducts was markedly decreased in association with the reduction of BECs and the elevation of plasma concentrations of bilirubin, suggesting that GVHD targets BDSCs and impairs the resilience of BECs. The growth of liver organoids in the presence of liver-infiltrating mononuclear cells from allogeneic recipients, but not from syngeneic recipients, significantly reduced in a TGF--dependent manner. Administration of SB-431542, an inhibitor of TGF-ß signaling, from day 14 to day 28 protected organoid-forming BDSCs against GVHD and mitigated biliary dysfunction after allogeneic HCT, suggesting that BDSCs are a promising therapeutic target for hepatic GVHD.

Advanced Cardiac Patches for the Treatment of Myocardial Infarction.

Myocardial infarction is a cardiovascular disease characterized by a high incidence rate and mortality. It leads to various cardiac pathophysiological changes, including ischemia/reperfusion injury, inflammation, fibrosis, and ventricular remodeling, which ultimately result in heart failure and pose a significant threat to global health. Although clinical reperfusion therapies and conventional pharmacological interventions improve emergency survival rates and short-term prognoses, they are still limited in providing long-lasting improvements in cardiac function or reversing pathological progression. Recently, cardiac patches have gained considerable attention as a promising therapy for myocardial infarction. These patches consist of scaffolds or loaded therapeutic agents that provide mechanical reinforcement, synchronous electrical conduction, and localized delivery within the infarct zone to promote cardiac restoration. This review elucidates the pathophysiological progression from myocardial infarction to heart failure, highlighting therapeutic targets and various cardiac patches. The review considers the primary scaffold materials, including synthetic, natural, and conductive materials, and the prevalent fabrication techniques and optimal properties of the patch, as well as advanced delivery strategies. Last, the current limitations and prospects of cardiac patch research are considered, with the goal of shedding light on innovative products poised for clinical application.

Designing antimicrobial peptides using deep learning and molecular dynamic simulations.

With the emergence of multidrug-resistant bacteria, antimicrobial peptides (AMPs) offer promising options for replacing traditional antibiotics to treat bacterial infections, but discovering and designing AMPs using traditional methods is a time-consuming and costly process. Deep learning has been applied to the de novo design of AMPs and address AMP classification with high efficiency. In this study, several natural language processing models were combined to design and identify AMPs, i.e. sequence generative adversarial nets, bidirectional encoder representations from transformers and multilayer perceptron. Then, six candidate AMPs were screened by AlphaFold2 structure prediction and molecular dynamic simulations. These peptides show low homology with known AMPs and belong to a novel class of AMPs. After initial bioactivity testing, one of the peptides, A-222, showed inhibition against gram-positive and gram-negative bacteria. The structural analysis of this novel peptide A-222 obtained by nuclear magnetic resonance confirmed the presence of an alpha-helix, which was consistent with the results predicted by AlphaFold2. We then performed a structure-activity relationship study to design a new series of peptide analogs and found that the activities of these analogs could be increased by 4-8-fold against Stenotrophomonas maltophilia WH 006 and Pseudomonas aeruginosa PAO1. Overall, deep learning shows great potential in accelerating the discovery of novel AMPs and holds promise as an important tool for developing novel AMPs.

Calcineurin inhibitor inhibits tolerance induction by suppressing terminal exhaustion of donor T cells after allo-HCT.

Calcineurin inhibitor-based graft-versus-host disease (GVHD) prophylaxis is standard in allogeneic hematopoietic stem cell transplantation (HCT) but fails to induce long-term tolerance without chronic GVHD (cGVHD) in a considerable number of patients. In this study, we addressed this long-standing question in mouse models of HCT. After HCT, alloreactive donor T cells rapidly differentiated into PD-1+ TIGIT+ terminally exhausted T cells (terminal Tex). GVHD prophylaxis with cyclosporine (CSP) suppressed donor T-cell expression of TOX, a master regulator to promote differentiation of transitory exhausted T cells (transitory Tex), expressing both inhibitory receptors and effector molecules, into terminal Tex, and inhibited tolerance induction. Adoptive transfer of transitory Tex, but not terminal Tex, into secondary recipients developed cGVHD. Transitory Tex maintained alloreactivity and thus PD-1 blockade restored graft-versus-leukemia (GVL) activity of transitory Tex and not terminal Tex. In conclusion, CSP inhibits tolerance induction by suppressing the terminal exhaustion of donor T cells, while maintaining GVL effects to suppress leukemia relapse.

FLUXestimator: a webserver for predicting metabolic flux and variations using transcriptomics data.

Quantitative assessment of single cell fluxome is critical for understanding the metabolic heterogeneity in diseases. Unfortunately, laboratory-based single cell fluxomics is currently impractical, and the current computational tools for flux estimation are not designed for single cell-level prediction. Given the well-established link between transcriptomic and metabolomic profiles, leveraging single cell transcriptomics data to predict single cell fluxome is not only feasible but also an urgent task. In this study, we present FLUXestimator, an online platform for predicting metabolic fluxome and variations using single cell or general transcriptomics data of large sample-size. The FLUXestimator webserver implements a recently developed unsupervised approach called single cell flux estimation analysis (scFEA), which uses a new neural network architecture to estimate reaction rates from transcriptomics data. To the best of our knowledge, FLUXestimator is the first web-based tool dedicated to predicting cell-/sample-wise metabolic flux and metabolite variations using transcriptomics data of human, mouse and 15 other common experimental organisms. The FLUXestimator webserver is available at http://scFLUX.org/, and stand-alone tools for local use are available at https://github.com/changwn/scFEA. Our tool provides a new avenue for studying metabolic heterogeneity in diseases and has the potential to facilitate the development of new therapeutic strategies.

Reactive granulopoiesis depends on T-cell production of IL-17A and neutropenia-associated alteration of gut microbiota.

Granulopoiesis in the bone marrow adjusts cellular output as demand for neutrophils changes. Reactive granulopoiesis is induced by profound neutropenia, but its mechanism remains to be clarified. We herein explored its mechanisms using mouse models of syngeneic hematopoietic stem cell transplantation (SCT) and 5-fluorouracil-induced neutropenia. After SCT, T cell production of IL-17A was up-regulated. Neutrophil recovery was significantly delayed in IL-17A-deficient or T cell-deficient RAG1-/- mice, and adoptive transfer of wild-type (WT) T cells facilitated neutrophil engraftment. Gut decontamination with oral antibiotics suppressed T cell production of IL-17A and impaired neutrophil recovery. Transplantation of fecal microbiota collected from neutropenic, not naive, mice promoted neutrophil recovery in these mice, suggesting that neutropenia-associated microbiota had a potential to stimulate reactive granulopoiesis. Our study uncovered a cross talk between gut microbiota and neutropenia after SCT and chemotherapy.

Graphdiyne Enabled Nitrogen Vacancy Formation in Copper Nitride for Efficient Ammonia Synthesis.

The electrocatalytic reduction of nitrate is promising for sustainable ammonia synthesis but suffers from slow reduction kinetics and multiple competing reactions. Here, we report a catalyst featuring copper nitride (Cu3N) anchored on a novel graphdiyne support (termed Cu3N/GDY), which is used for electrocatalytic reduction of nitrate to produce ammonia. The GDY absorbed hydrogen and enabled nitrogen (N) vacancy formation in Cu3N for the fast nitrate reduction reaction (NO3RR). Further, the distinct absorption sites formed by GDY and N vacancy enabled the excellent selectivity and stability of NO3RR. Notably, the Cu3N/GDY catalyst achieved a high ammonia yield (YNH3) up to 35280 µg h-1 mgcat.-1 and a high Faradaic efficiency (FE) of 98.1% using 0.1 M NO3- at -0.9 V versus a reversible hydrogen electrode (RHE). Using electron paramagnetic resonance (EPR) technology and in situ X-ray absorption fine structure (XAFS) spectroscopy measurement, we visualized the N vacancy formation in Cu3N and electrocatalytic NO3RR enabled by GDY. These findings show the promise of GDY in sustainable ammonia synthesis and highlight the efficacy of Cu3N/GDY as a catalyst.

Machine Learning-Assisted High-Throughput Identification and Quantification of Protein Biomarkers with Printed Heterochains.

Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of multi-material heterochains, which show improved sensitivity, throughput, and accuracy compared to standard ELISA kits. By controlling the material combination and the number of ligand nanoparticles (NPs), we observe robust near-field enhancement as well as both strong electromagnetic resonance in polymer-semiconductor heterochains. In particular, their optical signals show a linear response to the coordination number of the semiconductor NPs in a wide range. Accordingly, a visible nanophotonic biosensor is developed by functionalizing antibodies on central polymer chains that can identify target proteins attached to semiconductor NPs. This allows for the specific detection of multiple protein biomarkers from healthy people and pancreatic cancer patients in one step with an ultralow detection limit (1 pg/mL). Furthermore, rapid and high-throughput quantification of protein expression levels in diverse clinical samples such as buffer, urine, and serum is achieved by combining a neural network algorithm, with an average accuracy of 97.3%. This work demonstrates that the heterochain-based biosensor is an exemplary candidate for constructing next-generation diagnostic tools and suitable for many clinical settings.

Reducing Quantitative Uncertainty Caused by Data Processing in Untargeted Metabolomics.

Processing liquid chromatography-mass spectrometry-based metabolomics data using computational programs often introduces additional quantitative uncertainty, termed computational variation in a previous work. This work develops a computational solution to automatically recognize metabolic features with computational variation in a metabolomics data set. This tool, AVIR (short for "Accurate eValuation of alIgnment and integRation"), is a support vector machine-based machine learning strategy (https://github.com/HuanLab/AVIR). The rationale is that metabolic features with computational variation have a poor correlation between chromatographic peak area and peak height-based quantifications across the samples in a study. AVIR was trained on a set of 696 manually curated metabolic features and achieved an accuracy of 94% in a 10-fold cross-validation. When tested on various external data sets from public metabolomics repositories, AVIR demonstrated an accuracy range of 84%-97%. Finally, tested on a large-scale metabolomics study, AVIR clearly indicated features with computational variation and thus guided us to manually correct them. Our results show that 75.3% of the samples with computational variation had a relative intensity difference of over 20% after correction. This demonstrates the critical role of AVIR in reducing computational variation to improve quantitative certainty in untargeted metabolomics analysis.

Artificial Intelligence-Enhanced Waveguide "Photonic Nose"- Augmented Sensing Platform for VOC Gases in Mid-Infrared.

On-chip nanophotonic waveguide sensor is a promising solution for miniaturization and label-free detection of gas mixtures utilizing the absorption fingerprints in the mid-infrared (MIR) region. However, the quantitative detection and analysis of organic gas mixtures is still challenging and less reported due to the overlapping of the absorption spectrum. Here,an Artificial-Intelligence (AI) assisted waveguide "Photonic nose" is presented as an augmented sensing platform for gas mixture analysis in MIR. With the subwavelength grating cladding supported waveguide design and the help of machine learning algorithms, the MIR absorption spectrum of the binary organic gas mixture is distinguished from arbitrary mixing ratio and decomposed to the single-component spectra for concentration prediction. As a result, the classification of 93.57% for 19 mixing ratios is realized. In addition, the gas mixture spectrum decomposition and concentration prediction show an average root-mean-square error of 2.44 vol%. The work proves the potential for broader sensing and analytical capabilities of the MIR waveguide platform for multiple organic gas components toward MIR on-chip spectroscopy.

Hypertension, microvascular obstruction and infarct size in patients with STEMI undergoing PCI: Pooled analysis from 7 cardiac magnetic resonance imaging studies.

BACKGROUND: Mortality after ST-segment elevation myocardial infarction (STEMI) is increased in patients with hypertension. The mechanisms underlying this association are uncertain. We sought to investigate whether patients with STEMI and prior hypertension have greater microvascular obstruction (MVO) and infarct size (IS) compared with those without hypertension. METHODS: We pooled individual patient data from 7 randomized trials of patients with STEMI undergoing primary percutaneous coronary intervention (PCI) in whom cardiac magnetic resonance imaging was performed within 1 month after reperfusion. The associations between hypertension and MVO, IS, and mortality were assessed in multivariable adjusted models. RESULTS: Among 2174 patients (61.3 ± 12.6 years, 76% male), 1196 (55.0%) had hypertension. Patients with hypertension were older, more frequently diabetic and had more extensive coronary artery disease than those without hypertension. MVO and IS measured as percent LV mass were not significantly different in patients with and without hypertension (adjusted differences 0.1, 95% CI -0.3 to 0.6, P = .61 and -0.2, 95% CI -1.5 to 1.2, P = .80, respectively). Hypertension was associated with a higher unadjusted risk of 1-year death (hazard ratio [HR] 2.28, 95% CI 1.44-3.60, P < .001), but was not independently associated with higher mortality after multivariable adjustment (adjusted HR 1.04, 95% CI 0.60-1.79, P = .90). CONCLUSION: In this large-scale individual patient data pooled analysis, hypertension was not associated with larger IS or MVO after primary PCI for STEMI.

A novel antimicrobial peptide S24 combats serious wound infections caused by Pseudomonas aeruginosa and Acinetobacter baumannii.

OBJECTIVES: Pseudomonas aeruginosa and Acinetobacter baumannii are ranked as top-priority organisms by WHO. Antimicrobial peptides (AMPs) are promising antimicrobial agents that are highly effective against serious bacterial infections. METHODS: In our previous study, a series of α-helical AMPs were screened using a novel multiple-descriptor strategy. The current research suggested that S24 exhibited strong antimicrobial activity against major pathogenic bacteria, and displayed minimal haemolysis, good serum stability and maintained salt resistance. RESULTS: We found that S24 exerted an antimicrobial effect by destroying outer membrane permeability and producing a strong binding effect on bacterial genomic DNA that inhibits genomic DNA migration. Furthermore, S24 exerted a strong ability to promote healing in wound infected by P. aeruginosa, A. baumannii and mixed strains in a mouse model. CONCLUSIONS: Overall, S24 showed good stability under physiological conditions and excellent antimicrobial activity, suggesting it may be a potential candidate for the development of serious bacterial infection treatment.

Chronic Excess Iodine Intake Inhibits Bone Reconstruction Leading to Osteoporosis in Rats.

BACKGROUND: Although iodine modulates bone metabolism in the treatment of thyroid disease, the effect of iodine intake on bone metabolism remains less known. OBJECTIVE: This study evaluated the effect of excess iodine intake in rats on bone reconstruction in the 6th and 12th month of intervention. METHOD: Rats were treated with different doses of iodinated water: the normal group (NI, 6.15 µg/d), 5-fold high iodine group (5HI, 30.75 µg/d), 10-fold high iodine group (10HI, 61.5 µg/d), 50-fold high iodine group (50HI, 307.5 µg/d), and 100-fold high iodine group (100HI, 615 µg/d). Thyroid hormone concentrations were determined by a chemiluminescent immunoassay. Morphometry and microstructure of bone trabecula were observed by hematoxylin and eosin staining and microcomputed tomography, respectively. Alkaline phosphatase (ALP) and tartrate-resistant acid phosphatase (TRAP) staining were performed to evaluate the activity of osteoblasts and osteoclasts, respectively. RESULTS: The 24-h urine iodine concentration increased with iodine intake. The rats in the HI groups had higher serum thyroid-stimulating hormone and decreased serum free thyroxine concentrations in the 12th month than the NI group (all P < 0.05). The percentage of the trabecular bone area and osteoblast perimeter in the 100HI group were significantly lower than those in the NI group (P < 0.05). Increased structure model index was observed in the 50HI and 100HI groups compared with the NI group in the 6th month and increased trabecular separation in the 12th month (all P < 0.05). ALP and TRAP staining revealed osteoblastic bone formation was reduced, and the number of TRAP+ multinucleated cells decreased with increasing iodine intake. CONCLUSIONS: Excess iodine intake may increase the risk of hypothyroidism in rats. Chronic excess iodine intake can lead to abnormal changes in skeletal structure, resulting in reduced activity of osteoblasts and osteoclasts, which inhibits the process of bone reconstruction and may lead to osteoporosis.

Solution Combustion Synthesis of Submicron-Sized Titanium Niobium Oxide Anodes for High-Rate and Ultrastable Lithium-Ion Batteries.

Recently, the development of high-rate performance lithium-ion batteries is crucial for the development of next-generation energy storage systems. Nanoarchitecturing of the electrode material is a common strategy to improve the effective Li+ diffusion transport rate. However, this method often results in a reduction of volumetric energy density and battery stability. In this work, we propose a different strategy by synthesizing submicron-sized Ti2Nb10O29 (s-TNO) as a durable high-rate anode material using a facile and scalable solution combustion method, eliminating the dependence nanoarchitectures. The s-TNO electrode material exhibits a large tunnel structure and an excellent pseudocapacitive performance. The results show that this electrode material delivers a commendable reversible capacity of 238.7 mAh g-1 at 0.5 C and retains 78.2% of its capacity after 10,000 cycles at 10 C. This work provides a valuable guide for the synthesis of submicron-structured electrode materials using the solution combustion method, particularly for high-capacity, high-rate, and high-stability electrode materials.

Achieving Superior Electromagnetic-Absorbing Performances in the Hexagonal Flake BaFe12O19@PVDF Composites.

Combining magnetic and dielectric materials to form a composite can significantly improve its impedance matching and electromagnetic wave absorption performance. Furthermore, composite materials with a core-shell structure hold promise in meeting the demand for lightweight and highly electromagnetic-absorbing properties. In this study, uniform hexagonal flake barium ferrite (BaFe12O19) was prepared using the hydrothermal method. Subsequently, BaFe12O19@PVDF composites were synthesized by the sol-gel method. By adjusting the mass ratio of BaFe12O19 and PVDF, the shell size of the BaFe12O19@PVDF composite material was controlled, and its electromagnetic absorption performance was enhanced. The shell thickness of BaFe12O19@PVDF is 19.64 nm when the BaFe12O19: PVDF mass ratio is 1:1.0, and the optimal impedance matching is obtained at 13.4 GHz. Meanwhile, at a thickness of 1.5 mm, the minimum reflection loss (RLmin) reached -58.04 dB, and an effective absorption bandwidth (EAB) (RL ≤ -10 dB) of 5.53 GHz was achieved within the frequency range of 11.65 to 15.63 GHz and from 16.36 to 17.91 GHz. Besides, the composites with a matching thickness of 3.5 mm show a maximum EAB of 15.90 GHz when the mass ratio of BaFe12O19 to PVDF is 1:1.2. Within the frequency range of 2-18 GHz, the coverage of reflection loss less than -10 dB is 99.38%, almost achieving full coverage. These results demonstrate that BaFe12O19@PVDF composites exhibit excellent electromagnetic-absorbing performances, making them an excellent candidate for electromagnetic wave absorption in 5G communications.

The expression and clinical significance of CFAP65 in colon cancer.

BACKGROUND: CFAP65 (cilia and flagella associated protein 65) is a fundamental protein in the development and formation of ciliated flagella, but few studies have focused on its role in cancer. This study aimed to investigate the prognostic significance of CFAP65 in colon cancer. METHODS: The functionally enriched genes related to CFAP65 were analyzed through the Gene Ontology (GO) database. Subsequently, CFAP65 expression levels in colon cancer were evaluated by reverse transcription and quantitative polymerase chain reaction (RT-qPCR) and immunoblotting in 20 pairs of frozen samples, including tumors and their matched paratumor tissue. Furthermore, protein expression of CFAP65 in 189 colon cancer patients were assessed via immunohistochemical staining. The correlations between CFAP65 expression and clinical features as well as long-term survival were statistically analyzed. RESULTS: CFAP65-related genes are significantly enriched on cellular processes of cell motility, ion channels, and GTPase-associated signaling. The expression of CFAP65 was significantly higher in colon cancer tissue compared to paratumor tissue. The proportion of high expression and low expression of CFAP65 in the clinical samples of colon cancer were 61.9% and 38.1%, respectively, and its expression level was not associated with the clinical parameters including gender, age, tumor location, histological differentiation, tumor stage, vascular invasion and mismatch repair deficiency. The five-year disease-free survival rate of the patients with CFAP65 low expression tumors was significantly lower than that those with high expression tumors (56.9% vs. 72.6%, P = 0.03), but the overall survival rate has no significant difference (69% vs. 78.6%, P = 0.171). The cox hazard regression analysis model showed that CFAP65 expression, tumor stage and tumor location were independent prognostic factors. CONCLUSIONS: In conclusion, we demonstrate CFAP65 is a potential predictive marker for tumor progression in colon cancer.

Discovery of potential components characteristic by conjugated enone from the branches and leaves of Croton lauioides with anti-neuroinflammatory activity via regulating the NF-κB pathway.

In this study, the chemical composition and pharmacological activity of Croton lauioides were investigated for the first time. The bioactive and HPLC-UV guided isolation led to the discovery of twenty-three conjugated enone-type components (1-23), including nine previously unknown sesquiterpenoid derivatives (1-4, 9-10, 12-14). Notably, compounds 1 and 12 are epoxides containing an endoperoxide bridge (1) or a unique dioxaspiro core (12), respectively. Compounds 2-7 are non-benzenoid aromatics featuring a tropone function, while 9-11 possess a rare rearranged scaffold with tropone shift into benzene. Extensive characterization was performed using NMR spectra, HRESIMS data, and electronic circular dichroism (ECD) calculations. Furthermore, we evaluated the bioactivities of all isolated compounds against neuroinflammation in LPS-stimulated BV-2 microglial cells. Remarkably, most sesquiterpenoid derivatives exhibited significant NO inhibit activities, and compound 5 showed the most potent effect with an IC50 value of 0.14 ± 0.04 µM. Structure-activity relationship (SAR) analysis revealed that sesquiterpenoids modified with endocyclic enone conjugation may serve as a key pharmacophore for NO inhibition, particularly involving aromatic tropone moiety. The qPCR and Western blot results demonstrated that 5 exerted an inhibitory effect on the mRNA levels of iNOS, TNF-α and COX-2 in a time-dependent manner, as well as suppressed the protein expression of iNOS, TNF-α, COX-2. In mechanism, 5 could prevented activation of NF-κB pathway by suppressing phosphorylation of p65 and IκB-α. These findings revealed C. lauioides might be a promising resource for drug candidate development targeting neuroinflammation.

Responsive mechanism of Hemerocallis citrina Baroni to complex saline-alkali stress revealed by photosynthetic characteristics and antioxidant regulation.

KEY MESSAGE: Saline-alkali stress induces oxidative damage and photosynthesis inhibition in H. citrina, with a significant downregulation of the expression of photosynthesis- and antioxidant-related genes at high concentration. Soil salinization is a severe abiotic stress that impacts the growth and development of plants. In this study, Hemerocallis citrina Baroni was used to investigate its responsive mechanism to complex saline-alkali stress (NaCl:Na2SO4:NaHCO3:Na2CO3 = 1:9:9:1) for the first time. The growth phenotype, photoprotective mechanism, and antioxidant system of H. citrina were studied combining physiological and transcriptomic techniques. KEGG enrichment and GO analyses revealed significant enrichments of genes related to photosynthesis, chlorophyll degradation and antioxidant enzyme activities, respectively. Moreover, weighted gene co-expression network analysis (WGCNA) found that saline-alkali stress remarkably affected the photosynthetic characteristics and antioxidant system. A total of 29 key genes related to photosynthesis and 29 key genes related to antioxidant enzymes were discovered. High-concentration (250 mmol L-1) stress notably inhibited the expression levels of genes related to light-harvesting complex proteins, photosystem reaction center activity, electron transfer, chlorophyll synthesis, and Calvin cycle in H. citrina leaves. However, most of them were insignificantly changed under low-concentration (100 mmol L-1) stress. In addition, H. citrina leaves under saline-alkali stress exhibited yellow-brown necrotic spots, increased cell membrane permeability and accumulation of reactive oxygen species (ROS) as well as osmolytes. Under 100 mmol L-1 stress, ROS was eliminate by enhancing the activities of antioxidant enzymes. Nevertheless, 250 mmol L-1 stress down-regulated the expression levels of genes encoding antioxidant enzymes, and key enzymes in ascorbate-glutathione (AsA-GSH) cycle as well as thioredoxin-peroxiredoxin (Trx-Prx) pathway, thus inhibiting the activities of these enzymes. In conclusion, 250 mmol L-1 saline-alkali stress caused severe damage to H. citrina mainly by inhibiting photosynthesis and ROS scavenging capacity.

Gouqi-derived nanovesicles (GqDNVs) inhibited dexamethasone-induced muscle atrophy associating with AMPK/SIRT1/PGC1α signaling pathway.

With the increasing trend of global aging, sarcopenia has become a significant public health issue. Goji berry, also known as "Gou qi zi" in China, is a traditional Chinese herb that can enhance the structure and function of muscles and bones. Otherwise, previous excellent publications illustrated that plant-derived exosome-like nanoparticles can exert good bioactive functions in different aging or disease models. Thus, we issued the hypothesis that Gouqi-derived nanovesicles (GqDNVs) may also have the ability to improve skeletal muscle health, though the effect and its mechanism need to be explored. Hence, we have extracted GqDNVs from fresh berries of Lycium barbarum L. (goji) and found that the contents of GqDNVs are rich in saccharides and lipids. Based on the pathway annotations and predictions in non-targeted metabolome analysis, GqDNVs are tightly associated with the pathways in metabolism. In muscle atrophy model mice, intramuscular injection of GqDNVs improves the cross-sectional area of the quadriceps muscle, grip strength and the AMPK/SIRT1/PGC1α pathway expression. After separately inhibiting AMPK or PGC1α in C2C12 cells with dexamethasone administration, we have found that the activated AMPK plays the chief role in improving cell proliferation induced by GqDNVs. Furthermore, the energy-targeted metabolome analysis in the quadriceps muscle demonstrates that the GqDNVs up-regulate the metabolism of amino sugar and nucleotide sugar, autophagy and oxidative phosphorylation process, which indicates the activation of muscle regeneration. Besides, the Spearman rank analysis shows close associations between the quality and function of skeletal muscle, metabolites and expression levels of AMPK and SIRT1. In this study, we provide a new founding that GqDNVs can improve the quality and function of skeletal muscle accompanying the activated AMPK/SIRT1/PGC1α signaling pathway. Therefore, GqDNVs have the effect of anti-aging skeletal muscle as a potential adjuvant or complementary method or idea in future therapy and research.