The pore-rhizosheath shapes maize root architecture by enhancing root distribution in macropores.

Pores and old root-channels are preferentially used by roots to allow them to penetrate hard soils. However, there are few studies that have accounted for the effects of pore-rhizosheath on root growth. In this study, we developed an approach by adding the synthetic root exudates using a porous stainless tube with 0.1-mm micropores through a peristaltic pump to reproduce the rhizosheath around the artificial pore, and investigated the effects of pores with and without rhizosheaths on maize root growth in a dense soil. The results indicated that the artificial rhizosheath was about 2.69 mm wide in the region surrounding the pores. The rhizosheath had a higher content of organic carbon, total nitrogen, and abundance of Actinobacteria than that of the bulk soil. Compared with the artificial macropores, the artificial root-pores with a rhizosheath increased the opportunities for root utilisation of the pores space, promoting steeper and deeper root growth. It is concluded that the pore-rhizosheath has a significant impact on root architecture by enhancing root distribution in macropores.

Long-term effects of Omicron BA.2 breakthrough infection on immunity-metabolism balance: a 6-month prospective study.

There have been reports of long coronavirus disease (long COVID) and breakthrough infections (BTIs); however, the mechanisms and pathological features of long COVID after Omicron BTIs remain unclear. Assessing long-term effects of COVID-19 and immune recovery after Omicron BTIs is crucial for understanding the disease and managing new-generation vaccines. Here, we followed up mild BA.2 BTI convalescents for six-month with routine blood tests, proteomic analysis and single-cell RNA sequencing (scRNA-seq). We found that major organs exhibited ephemeral dysfunction and recovered to normal in approximately six-month after BA.2 BTI. We also observed durable and potent levels of neutralizing antibodies against major circulating sub-variants, indicating that hybrid humoral immunity stays active. However, platelets may take longer to recover based on proteomic analyses, which also shows coagulation disorder and an imbalance between anti-pathogen immunity and metabolism six-month after BA.2 BTI. The immunity-metabolism imbalance was then confirmed with retrospective analysis of abnormal levels of hormones, low blood glucose level and coagulation profile. The long-term malfunctional coagulation and imbalance in the material metabolism and immunity may contribute to the development of long COVID and act as useful indicator for assessing recovery and the long-term impacts after Omicron sub-variant BTIs.

A Hybrid Controller for Musculoskeletal Robots Targeting Lifting Tasks in Industrial Metaverse.

In manufacturing, musculoskeletal robots have gained more attention with the potential advantages of flexibility, robustness, and adaptability over conventional serial-link rigid robots. Focusing on the fundamental lifting tasks, a hybrid controller is proposed to overcome control challenges of such robots for widely applications in industry. The metaverse technology offers an available simulated-reality-based platform to verify the proposed method. The hybrid controller contains two main parts. A muscle-synergy-based radial basis function (RBF) network is proposed as the feedforward controller, which is able to characterize the phasic and the tonic muscle synergies simultaneously. The adaptive dynamic programming (ADP) is applied as the feedback controller to address the optimal control problem. The actor-critic structure is applied in the ADP-based controller, where the critic network is trained to approximate the optimal performance index and the actor network is trained to compute the optimal muscle excitations. Furthermore, the convergence and stability of the ADP algorithm are also analyzed. Finally, experiments have been designed to verify the effectiveness of this hybrid controller on an upper limb musculoskeletal system, and the comparisons with other controllers are also illustrated. The results show that the proposed controller can obtain a satisfactory performance for lifting tasks.

Assessment of vaccinations and breakthrough infections after adjustment of the dynamic zero-COVID-19 strategy in China: an online survey.

Coronavirus disease 2019 (COVID-19) cases in China has grown rapidly after adjustment of the dynamic zero-COVID-19 strategy. However, how different vaccination states affect symptoms, severity and post COVID conditions was unclear. Here, we used an online questionnaire to investigate the infection status of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among 11,897 participants, with 55.55% positive and 28.42% negative. The common COVID-19 symptoms were fatigue (73.31%), cough (70.02%), fever (65.25%) and overall soreness (58.64%); self-reported asymptomatic infection accounted for 0.7% of participants. The persistent symptoms at 1 month after infection included fatigue (48.7%), drowsiness (34.3%), cough (30.1%), decreased exercise ability (23.1%) and pharyngeal discomfort (19.4%), which was reduced by more than 200% at 2 months. Participants with complications such as chronic obstructive pulmonary disease, respiratory diseases, diabetes, hypertension, etc. have a higher proportion of hospitalization and longer recovery time (p < = 0.01). Multiple vaccination statuses reduced the infection (p < 0.001) and severity rates (p = 0.022) by varying degrees as well as reduced the risk of high fever (>39.1 °C), chills, diarrhea and ageusia/anosmia, respectively (p < 0.05). Vaccination may enhance some upper respiratory symptoms, including sore throat, nasal congestion and runny nose, respectively (p < 0.05). Participants who had been vaccinated within 3 months were better protected by helping reduce their risk of overall soreness, chills and ageusia/anosmia, respectively (p < 0.05). In conclusion, our work has updated the epidemic characteristics of the breakthrough infection (BTI) wave after the dynamic zero-COVID-19 strategy, providing data and insights on how different vaccination statuses affect COVID-19 symptoms and disease prognosis.

Mechanistic insights into super-enhancer-driven genes as prognostic signatures in patients with glioblastoma.

BACKGROUND: Glioblastoma (GBM) is one of the most common malignant brain tumors in adults and is characterized by high aggressiveness and rapid progression, poor treatment, high recurrence rate, and poor prognosis. Although super-enhancer (SE)-driven genes haven been recognized as prognostic markers for several cancers, whether it can be served as effective prognostic markers for patients with GBM has not been evaluated. METHODS: We first combined histone modification data with transcriptome data to identify SE-driven genes associated with prognosis in patients with GBM. Second, we developed a SE-driven differentially expressed genes (SEDEGs) risk score prognostic model by univariate Cox analysis, KM survival analysis, multivariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression. Its reliability in predicting was verified by two external data sets. Third, through mutation analysis, immune infiltration, we explored the molecular mechanisms of prognostic genes. Next, Genomics of Drug Sensitivity in Cancer (GDSC) and the Connectivity Map (cMap) database were employed to assess different sensitivities to chemotherapeutic agents and small-molecule drug candidates between high- and low-risk patients. Finally, SEanalysis database was chosen to identify SE-driven transcription factors (TFs) regulating prognostic markers which will reveal a potential SE-driven transcriptional regulatory network. RESULTS: First, we developed a 11-gene risk score prognostic model (NCF2, MTHFS, DUSP6, G6PC3, HOXB2, EN2, DLEU1, LBH, ZEB1-AS1, LINC01265, and AGAP2-AS1) selected from 1,154 SEDEGs, which is not only an independent prognostic factor for patients, but also can effectively predict the survival rate of patients. The model can effectively predict 1-, 2- and 3-year survival of patients and was validated in external Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) datasets. Second, the risk score was positively correlated with the infiltration of regulatory T cell, CD4 memory activated T cell, activated NK cell, neutrophil, resting mast cell, M0 macrophage, and memory B cell. Third, we found that high-risk patients showed higher sensitivity than low-risk patients to both 27 chemotherapeutic agents and 4 small-molecule drug candidates which might benefit further precision therapy for GBM patients. Finally, 13 potential SE-driven TFs imply how SE regulates GBM patient's prognosis. CONCLUSION: The SEDEG risk model not only helps to elucidate the impact of SEs on the course of GBM, but also provides a bright future for prognosis determination and choice of treatment for GBM patients.

Integrative single-cell sequencing analysis distinguishes survival-associated cells from the breast cancer microenvironment.

BACKGROUND: Breast cancer shows a highly complex tumor microenvironment by containing various cell types. Identifying prognostic cell populations in the tumor microenvironment will improve the mechanistical understanding of breast cancer and facilitate the development of new breast cancer therapies by targeting the tumor microenvironment. The development of single-cell sequencing reveals various cell types, states, and lineages within the context of heterogenous breast tumors, but identifying phenotype-associated subpopulations is challenging. RESULTS: Here, we applied Scissor (single-cell identification of subpopulations with bulk Sample phenotype correlation) to integrate single cell and bulk data of breast cancer, and found that MHC-deficient tumor cells, FABP5+ macrophages, and COL1A1+ cancer-associated fibroblasts (CAFs) were detrimental to patient survival, while T cells and dendritic cells were the main protective cells. MHC-deficient tumor cells show strong downregulation of MHC expression for immune evasion by downregulating interferon and JAK-STATs signaling. FABP5+ macrophages show low antigen-presenting activity via associating with lipid metabolism. Our data suggest that COL1A1+ CAFs may block T-cell immune infiltration through cell interaction in breast tumor microenvironment. CONCLUSION: Taken together, our study reveals survival-associated subpopulations in breast tumor microenvironment. Importantly, subpopulations related to immune evasion of breast cancer is uncovered.

The Tumor Stemness Indice mRNAsi can Act as Molecular Typing Tool for Lung Adenocarcinoma.

Due to the high heterogeneity, lung adenocarcinoma (LUAD) cannot be distinguished into precise molecular subtypes, thereby resulting in poor therapeutic effect and low 5-year survival rate clinically. Although the tumor stemness score (mRNAsi) has been shown to accurately characterize the similarity index of cancer stem cells (CSCs), whether mRNAsi can serve as an effective molecular typing tool for LUAD isn't reported to date. In this study, we first demonstrate that mRNAsi is significantly correlated with the prognosis and disease degree of LUAD patients, i.e., the higher the mRNAsi, the worse the prognosis and the higher the disease degree. Second, we identify 449 mRNAsi-related genes based on both weighted gene co-expression network analysis (WGCNA) and univariate regression analysis. Third, our results display that 449 mRNAsi-related genes can accurately distinguish the LUAD patients into two molecular subtypes: ms-H subtype (with high mRNAsi) and ms-L subtype (with low mRNAsi), particularly the ms-H subtype has a worse prognosis. Remarkably, significant differences in clinical characteristics, immune microenvironment, and somatic mutation exist between the two molecular subtypes, which might lead to the poorer prognosis of the ms-H subtype patients than that of the ms-L subtype ones. Finally, we establish a prognostic model containing 8 mRNAsi-related genes, which can effectively predict the survival rate of LUAD patients. Taken together, our work provides the first molecular subtype related to mRNAsi in LUAD, and reveals that these two molecular subtypes, the prognostic model and marker genes may have important clinical value for effectively monitoring and treating LUAD patients.

Novel insight into the underlying dysregulation mechanisms of immune cell-to-cell communication by analyzing multitissue single-cell atlas of two COVID-19 patients.

How does SARS-CoV-2 cause lung microenvironment disturbance and inflammatory storm is still obscure. We here performed the single-cell transcriptome sequencing from lung, blood, and bone marrow of two dead COVID-19 patients and detected the cellular communication among them. Our results demonstrated that SARS-CoV-2 infection increase the frequency of cellular communication between alveolar type I cells (AT1) or alveolar type II cells (AT2) and myeloid cells triggering immune activation and inflammation microenvironment and then induce the disorder of fibroblasts, club, and ciliated cells, which may cause increased pulmonary fibrosis and mucus accumulation. Further study showed that the increase of T cells in the lungs may be mainly recruited by myeloid cells through ligands/receptors (e.g., ANXA1/FPR1, C5AR1/RPS19, and CCL5/CCR1). Interestingly, we also found that certain ligands/receptors (e.g., ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1) are significantly activated and shared among lungs, blood and bone marrow of COVID-19 patients, implying that the dysregulation of ligands/receptors may lead to immune cell's activation, migration, and the inflammatory storm in different tissues of COVID-19 patients. Collectively, our study revealed a possible mechanism by which the disorder of cell communication caused by SARS-CoV-2 infection results in the lung inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

Polytonic Drug Release via Multi-Hierarchical Microstructures Enabled by Nano-Metamaterials.

″Nano-metamaterials″, rationally designed novel class metamaterials with multilevel microarchitectures and both characteristic sizes and whole sizes at the nanoscale, are introduced into the area of drug delivery system (DDS), and the relationship between release profile and treatment efficacy at the single-cell level is revealed for the first time. Fe3+ -core-shell-corona nano-metamaterials (Fe3+ -CSCs) are synthesized using a dual-kinetic control strategy. The hierarchical structure of Fe3+ -CSCs, with a homogeneous interior core, an onion-like shell, and a hierarchically porous corona. A novel polytonic drug release profile occurred, which consists of three sequential stages: burst release, metronomic release, and sustained release. The Fe3+ -CSCs results in overwhelming accumulation of lipid reactive oxygen species (ROS), cytoplasm ROS, and mitochondrial ROS in tumor cells and induces unregulated cell death. This cell death modality causes cell membranes to form blebs, seriously corrupting cell membranes to significantly overcome the drug-resistance issues. It is first demonstrated that nano-metamaterials of well-defined microstructures can modulate drug release profile at the single cell level, which in turn alters the downstream biochemical reactions and subsequent cell death modalities. This concept has significant implications in the drug delivery area and can serve to assist in designing potential intelligent nanostructures for novel molecular-based diagnostics and therapeutics.

Early peripheral blood MCEMP1 and HLA-DRA expression predicts COVID-19 prognosis.

BACKGROUND: Mass vaccination has dramatically reduced the incidence of severe COVID-19, with most cases now presenting as self-limiting upper respiratory tract infections. However, those with co-morbidities, the elderly and immunocompromised, as well as the unvaccinated, remain disproportionately vulnerable to severe COVID-19 and its sequelae. Furthermore, as the effectiveness of vaccination wanes with time, immune escape SARS-CoV-2 variants could emerge to cause severe COVID-19. Reliable prognostic biomarkers for severe disease could be used as early indicator of re-emergence of severe COVID-19 as well as for triaging of patients for antiviral therapy. METHODS: We performed a systematic review and re-analysis of 7 publicly available datasets, analysing a total of 140 severe and 181 mild COVID-19 patients, to determine the most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients. In addition, we included an independent cohort where blood transcriptomics of COVID-19 patients were prospectively and longitudinally monitored previously, to track the time in which these gene expression changes occur before nadir of respiratory function. Single cell RNA-sequencing of peripheral blood mononuclear cells from publicly available datasets was then used to determine the immune cell subsets involved. FINDINGS: The most consistent differentially regulated genes in peripheral blood of severe COVID-19 patients were MCEMP1, HLA-DRA and ETS1 across the 7 transcriptomics datasets. Moreover, we found significantly heightened MCEMP1 and reduced HLA-DRA expression as early as four days before the nadir of respiratory function, and the differential expression of MCEMP1 and HLA-DRA occurred predominantly in CD14+ cells. The online platform which we developed is publicly available at https://kuanrongchan-covid19-severity-app-t7l38g.streamlitapp.com/, for users to query gene expression differences between severe and mild COVID-19 patients in these datasets. INTERPRETATION: Elevated MCEMP1 and reduced HLA-DRA gene expression in CD14+ cells during the early phase of disease are prognostic of severe COVID-19. FUNDING: K.R.C is funded by the National Medical Research Council (NMRC) of Singapore under the Open Fund Individual Research Grant (MOH-000610). E.E.O. is funded by the NMRC Senior Clinician-Scientist Award (MOH-000135-00). J.G.H.L. is funded by the NMRC under the Clinician-Scientist Award (NMRC/CSAINV/013/2016-01). S.K. is funded by the NMRC under the Transition Award. This study was sponsored in part by a generous gift from The Hour Glass.

A Dual-Kinetic Control Strategy for Designing Nano-Metamaterials: Novel Class of Metamaterials with Both Characteristic and Whole Sizes of Nanoscale.

Increasingly intricate in their multilevel multiscale microarchitecture, metamaterials with unique physical properties are challenging the inherent constraints of natural materials. Their applicability in the nanomedicine field still suffers because nanomedicine requires a maximum size of tens to hundreds of nanometers; however, this size scale has not been achieved in metamaterials. Therefore, "nano-metamaterials," a novel class of metamaterials, are introduced, which are rationally designed materials with multilevel microarchitectures and both characteristic sizes and whole sizes at the nanoscale, investing in themselves remarkably unique and significantly enhanced material properties as compared with conventional nanomaterials. Microarchitectural regulation through conventional thermodynamic strategy is limited since the thermodynamic process relies on the frequency-dependent effective temperature, Teff (ω), which limits the architectural regulation freedom degree. Here, a novel dual-kinetic control strategy is designed to fabricate nano-metamaterials by freezing a high-free energy state in a Teff (ω)-constant system, where two independent dynamic processes, non-solvent induced block copolymer (BCP) self-assembly and osmotically driven self-emulsification, are regulated simultaneously. Fe3+ -"onion-like core@porous corona" (Fe3+ -OCPCs) nanoparticles (the products) have not only architectural complexity, porous corona and an onion-like core but also compositional complexity, Fe3+ chelating BCP assemblies. Furthermore, by using Fe3+ -OCPCs as a model material, a microstructure-biological performance relationship is manifested in nano-metamaterials.

Characteristics of lymphocyte subset alterations in COVID-19 patients with different levels of disease severity.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a respiratory disorder caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which had rapidly spread all over the world and caused public health emergencies in the past two years. Although the diagnosis and treatment for COVID-19 have been well defined, the immune cell characteristics and the key lymphocytes subset alterations in COVID-19 patients have not been thoroughly investigated. METHODS: The levels of immune cells including T cells, B cells, and natural killer (NK) cells in 548 hospitalized COVID-19 patients, and 30 types of lymphocyte subsets in 125 hospitalized COVID-19 patients admitted to Wuhan Huoshenshan Hospital of China were measured using flow cytometry. The relationship between lymphocytes subsets with the cytokine interleukin-6 (IL-6) and the characteristics of lymphocyte subsets in single-cell RNA sequencing (scRNA-seq) data obtained from peripheral blood mononuclear cells (PBMCs) were also analysed in COVID-19 patients. RESULTS: In this study, we found that patients with critical COVID-19 infection exhibited an overall decline in lymphocytes including CD4+ T cells, CD8+ T cells, total T cells, B cells, and NK cells compared to mild and severe patients. However, the number of lymphocyte subsets, such as CD21low CD38low B cells, effector T4 cells, and PD1+ depleted T8 cells, was moderately increased in critical COVID-19 patients compared to mild cases. Notably, except for effector memory T4 cells, plasma blasts and Tregs, the number of all lymphocyte subsets was markedly decreased in COVID-19 patients with IL-6 levels over 30-fold higher than those in healthy cases. Moreover, scRNA-seq data showed obvious differences in the distribution and numbers of lymphocyte subsets between COVID-19 patients and healthy persons, and subsets-specific marker genes of lymphocyte subsets including CD4, CD19, CCR7, and IL7R, were markedly decreased in COVID-19 patients compared with those in healthy cases. CONCLUSION: A comprehensive decrease in immune cell and lymphocyte subsets in critical COVID-19 patients, and peripheral lymphocyte subset alterations showed a clear association with clinical characteristics.

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq.

BACKGROUND: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. METHODS: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. RESULTS: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor-ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. CONCLUSIONS: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.

mRNAsi-related genes can effectively distinguish hepatocellular carcinoma into new molecular subtypes.

Background: Recent studies have shown that the mRNA expression-based stemness index (mRNAsi) can accurately quantify the similarity of cancer cells to stem cells, and mRNAsi-related genes are used as biomarkers for cancer. However, mRNAsi-driven tumor heterogeneity is rarely investigated, especially whether mRNAsi can distinguish hepatocellular carcinoma (HCC) into different molecular subtypes is still largely unknown. Methods: Using OCLR machine learning algorithm, weighted gene co-expression network analysis, consistent unsupervised clustering, survival analysis and multivariate cox regression etc. to identify biomarkers and molecular subtypes related to tumor stemness in HCC. Results: We firstly demonstrate that the high mRNAsi is significantly associated with the poor survival and high disease grades in HCC. Secondly, we identify 212 mRNAsi-related genes that can divide HCC into three molecular subtypes: low cancer stemness cell phenotype (CSCP-L), moderate cancer stemness cell phenotype (CSCP-M) and high cancer stemness cell phenotype (CSCP-H), especially over-activated ribosomes, spliceosomes and nucleotide metabolism lead to the worst prognosis for the CSCP-H subtype patients, while activated amino acids, fatty acids and complement systems result in the best prognosis for the CSCP-L subtype. Thirdly, we find that three CSCP subtypes have different mutation characteristics, immune microenvironment and immune checkpoint expression, which may cause the differential prognosis for three subtypes. Finally, we identify 10 robust mRNAsi-related biomarkers that can effectively predict the survival of HCC patients. Conclusions: These novel cancer stemness-related CSCP subtypes and biomarkers in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy of HCC patients.

Transcriptomic and epigenomic analyses explore the potential role of H3K4me3 in neomycin-induced cochlear Lgr5+ progenitor cell regeneration of hair cells.

Currently, adult cochlear hair cells (HCs) lack the capacity to regenerate, particularly the hearing damage caused by the HC damage are hard to recover. Remarkably, Lgr5+ inner ear progenitor cells can be activated to proliferate and regenerate hair cells (HCs) in response to injury, but the epigenetic regulatory roles in HC regeneration from Lgr5+ progenitor cells remain unresolved to date. We here investigate the possible roles of H3K4me3 modification in Lgr5+ progenitor cell proliferation and HC regeneration, and identify these differentially expressed genes associated with different binding regions between untreated Lgr5+ progenitor cells (ULPs) and neomycin-treated Lgr5+ progenitor cells (NLPs). Especially, H3K4me3 modification drives 12 genes involved in regulating proliferation and HC regeneration. Interestingly, we find that transcription factors Zeb1, Fev and Prdm5 are enriched in distinct peaks, implying their probable important roles in modulating neomycin-induced Lgr5+ progenitor cell proliferation and HC regeneration. Overall, our study demonstrates the underlying roles of H3k4me3 modification in Lgr5+ progenitor cell proliferation and HCs regeneration, and provides candidate H3K4me3 modification targets and regulators for subsequent studies.

Spatiotemporal Release of Reactive Oxygen Species and NO for Overcoming Biofilm Heterogeneity.

The heterogeneity in biofilms is a major challenge in biofilm therapies due to different susceptibility of bacteria and extracellular polymeric substances (EPS) to antibacterial agents. Here, we describe a therapeutic strategy that overcame biofilm heterogeneity, where antibacterial agent (NO) and EPS dispersant (reactive oxygen species (ROS)-inducing Fe3+ ) were separately loaded in the yolk and shell compartment of a yolk-shell nanoplatform. Compared with traditional combinational chemotherapies which suffer from inconsistent pharmacokinetics profiles, this strategy drew on the pharmacokinetic complementarity of ROS and NO, where ROS with a short diffusion distance and a high redox potential corrupted the EPS, facilitating NO, which has a long diffusion distance and a broad antimicrobial spectrum, to penetrate the biofilm and eliminate the resident bacteria. Additionally, the construction of a three-dimensional spherical biofilm model is novel and clinically relevant.

Isolation and functional diversification of dihydroflavonol 4-Reductase gene HvDFR from Hosta ventricosa indicate its role in driving anthocyanin accumulation.

Anthocyanins are natural colorants are synthesized in a branch of the flavonoid pathway. Dihydroflavonol-4reductase (DFR) catalyzes dihydroflavonoids into anthocyanins biosynthesis, which is a key regulatory enzyme of anthocyanin biosynthesis in plants. Hosta ventricosa is an ornamental plant with elegant flowers and rich colorful leaves. How the function of HvDFR contributes to the anthocyanins biosynthesis is still unknown. In this study, the DFR homolog was identified from H. ventricosa and sequence analysis showed that HvDFR possessed the conserved NADPH binding and catalytic domains. A phylogenetic analysis showed that HvDFR was close to the clade formed with MaDFR and HoDFR in Asparagaceae. Gene expression analysis revealed that HvDFR was constitutive expressed in all tissues and expressed highly in flower as well as was positively correlated with anthocyanin content. In addition, the subcellular location of HvDFR showed that is in the nucleus and cell membrane. Overexpression of HvDFR in transgenic tobacco lines enhanced the anthocyanins accumulation along with the key genes upregulated, such as F3H, F3'H, ANS, and UFGT. Our results indicated a functional activity of the HvDFR, which provide an insight into the regulation of anthocyanins content in H. ventricosa.

Transcription Factors and Methylation Drive Prognostic miRNA Dysregulation in Hepatocellular Carcinoma.

Many dysregulated microRNAs (miRNAs) have been suggested to serve as oncogenes or tumor suppressors to act as diagnostic and prognostic factors for HCC patients. However, the dysregulated mechanisms of miRNAs in HCC remain largely unknown. Herein, we firstly identify 114 disordered mature miRNAs in HCC, 93 of them are caused by dysregulated transcription factors, and 10 of them are driven by the DNA methylation of their promoter regions. Secondly, we find that seven up-regulated miRNAs (miR-9-5p, miR-452-5p, miR-452-3p, miR-1180-3p, miR-4746-5p, miR-3677-3 and miR-4661-5p) can promote tumorigenesis via inhibiting multiple tumor suppressor genes participated in metabolism, which may act as oncogenes, and seven down-regulated miRNAs (miR-99-5p, miR-5589-5p, miR-5589-3p, miR-139-5p, miR-139-3p, miR-101-3p and miR-125b-5p) can suppress abnormal cell proliferation via suppressing a number of oncogenes involved in cancer-related pathways, which may serve as tumor suppressors. Thirdly, our findings reveal a mechanism that transcription factor and miRNA interplay can form various regulatory loops to synergistically control the occurrence and development of HCC. Finally, our results demonstrate that this key transcription factor FOXO1 can activate a certain number of tumor suppressor miRNAs to improve the survival of HCC patients, suggesting FOXO1 as an effective therapeutic target for HCC patients. Overall, our study not only reveals the dysregulated mechanisms of miRNAs in HCC, but provides several novel prognostic biomarkers and potential therapeutic targets for HCC patients.

Analyzing master regulators and scRNA-seq of COVID-19 patients reveals an underlying anti-SARS-CoV-2 mechanism of ZNF proteins.

Studies have demonstrated that both mortality and severe illness rates exist significant difference in different gender COVID-19 patients, but the reasons are still very mysterious to date. Here, we firstly find that the survival outcome of female patients is better to male patients through analyzing the 3044 COVID-19 cases. Secondly, we identify many important master regulators [e.g. STAT1/STAT2 and zinc finger (ZNF) proteins], in particular female patients can express more ZNF proteins and stronger transcriptional activities than male patients in response to SARS-CoV-2 infection. Thirdly, we discover that ZNF protein activity is significantly negative correlation with the SARS-CoV-2 load of COVID-19 patients, and ZNF proteins as transcription factors can also activate their target genes to participate in anti-SARS-CoV-2 infection. Fourthly, we demonstrate that ZNF protein activity is positive correlation with the abundance of multiple immune cells of COVID-19 patients, implying that the highly ZNF protein activity might promote the abundance and the antiviral activity of multiple immune cells to effectively suppress SARS-CoV-2 infection. Taken together, our study proposes an underlying anti-SARS-COV-2 role of ZNF proteins, and differences in the amount and activity of ZNF proteins might be responsible for the distinct prognosis of different gender COVID-19 patients.