Constructing a Stable Conductive Network for High-Performance Silicon-Based Anode in Lithium-Ion Batteries.

The application of carbon nanotubes to silicon nanoparticles has been used to improve the electrical conductivity of silicon-carbon anodes and prevent agglomeration of silicon nanoparticles during cycling. In this study, the composites are synthesized through an uncomplicated technique that involves the ultrasonication mixing of pyrene derivatives and carbon nanotubes and the formation of complexes with silicon nanoparticles in ultrasonic dispersion and magnetic stirring and then treated under vacuum. When the prepared composites are applied as lithium-ion battery anodes, the Si@(POH-AOCNTs) electrode displays a high reversible capacity of 3254.7 mAh g-1 at a current density of 0.1 A g-1. Furthermore, it exhibits excellent cycling stability with a specific capacity of 1195.8 mAh g-1 after 500 cycles at 1.0 A g-1. The superior electrochemical performance may be attributed to a large π-conjugated electron system of pyrene derivatives, which prompts the formation of a homogeneous CNTs conductive network and ensures the effective electron transfer, while the interaction between hydroxyl functional groups of hydroxypyrene and binder synergizes with CNTs network to further enhance the cycling stability of the composite.

Utilization of gene manipulation system for advancing the biotechnological potential of halophiles: A review.

Halophiles are salt-loving microorganisms known to have their natural resistance against media contamination even when cultivated in nonsterile and continuous bioprocess system, thus acting as promising cell factories for Next Generation of Industrial Biotechnology (NGIB). NGIB - a successor to the traditional industrial biotechnology, is a more sustainable and efficient bioprocess technology while saving energy and water in a more convenient way as well as reducing the investment cost and skilled workforce requirement. Numerous studies have achieved intriguing outcomes during synthesis of different metabolite using halophiles such as polyhydroxyalkanoates (PHA), ectoine, biosurfactants, and carotenoids. Present-day development in genetic maneuverings have shown optimistic effects on the industrial applications of halophiles. However, viable and competent genetic manipulation system and gene editing tools are critical to accelerate the process of halophile engineering. With the aid of such powerful gene manipulation systems, exclusive microbial chassis are being crafted with desirable features to breed another innovative area of research such as synthetic biology. This review provides an aerial perspective on how the expansion of adaptable gene manipulation toolkits in halophiles are contributing towards biotechnological advancement, and also focusses on their subsequent application for production improvement. This current methodical and comprehensive review will definitely help the scientific fraternity to bridge the gap between challenges and opportunities in halophile engineering.

Cinobufotalin prevents bone loss induced by ovariectomy in mice through the BMPs/SMAD and Wnt/ß-catenin signaling pathways.

BACKGROUND: Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength. However, current anti-resorptive drugs carry a risk of various complications. The deep learning-based efficacy prediction system (DLEPS) is a forecasting tool that can effectively compete in drug screening and prediction based on gene expression changes. This study aimed to explore the protective effect and potential mechanisms of cinobufotalin (CB), a traditional Chinese medicine (TCM), on bone loss. METHODS: DLEPS was employed for screening anti-osteoporotic agents according to gene profile changes in primary osteoporosis. Micro-CT, histological and morphological analysis were applied for the bone protective detection of CB, and the osteogenic differentiation/function in human bone marrow mesenchymal stem cells (hBMMSCs) were also investigated. The underlying mechanism was verified using qRT-PCR, Western blot (WB), immunofluorescence (IF), etc. RESULTS: A safe concentration (0.25 mg/kg in vivo, 0.05 µM in vitro) of CB could effectively preserve bone mass in estrogen deficiency-induced bone loss and promote osteogenic differentiation/function of hBMMSCs. Both BMPs/SMAD and Wnt/ß-catenin signaling pathways participated in CB-induced osteogenic differentiation, further regulating the expression of osteogenesis-associated factors, and ultimately promoting osteogenesis. CONCLUSION: Our study demonstrated that CB could significantly reverse estrogen deficiency-induced bone loss, further promoting osteogenic differentiation/function of hBMMSCs, with BMPs/SMAD and Wnt/ß-catenin signaling pathways involved.

Deep Learning-Predicted Dihydroartemisinin Rescues Osteoporosis by Maintaining Mesenchymal Stem Cell Stemness through Activating Histone 3 Lys 9 Acetylation.

Maintaining the stemness of bone marrow mesenchymal stem cells (BMMSCs) is crucial for bone homeostasis and regeneration. However, in vitro expansion and bone diseases impair BMMSC stemness, limiting its functionality in bone tissue engineering. Using a deep learning-based efficacy prediction system and bone tissue sequencing, we identify a natural small-molecule compound, dihydroartemisinin (DHA), that maintains BMMSC stemness and enhances bone regeneration. During long-term in vitro expansion, DHA preserves BMMSC stemness characteristics, including its self-renewal ability and unbiased differentiation. In an osteoporosis mouse model, oral administration of DHA restores the femur trabecular structure, bone density, and BMMSC stemness in situ. Mechanistically, DHA maintains BMMSC stemness by promoting histone 3 lysine 9 acetylation via GCN5 activation both in vivo and in vitro. Furthermore, the bone-targeted delivery of DHA by mesoporous silica nanoparticles improves its therapeutic efficacy in osteoporosis. Collectively, DHA could be a promising therapeutic agent for treating osteoporosis by maintaining BMMSC stemness.

Prim-O-glucosylcimifugin ameliorates aging-impaired endogenous tendon regeneration by rejuvenating senescent tendon stem/progenitor cells.

Adult tendon stem/progenitor cells (TSPCs) are essential for tendon maintenance, regeneration, and repair, yet they become susceptible to senescence with age, impairing the self-healing capacity of tendons. In this study, we employ a recently developed deep-learning-based efficacy prediction system to screen potential stemness-promoting and senescence-inhibiting drugs from natural products using the transcriptional signatures of stemness. The top-ranked candidate, prim-O-glucosylcimifugin (POG), a saposhnikovia root extract, could ameliorate TPSC senescent phenotypes caused by long-term passage and natural aging in rats and humans, as well as restore the self-renewal and proliferative capacities and tenogenic potential of aged TSPCs. In vivo, the systematic administration of POG or the local delivery of POG nanoparticles functionally rescued endogenous tendon regeneration and repair in aged rats to levels similar to those of normal animals. Mechanistically, POG protects TSPCs against functional impairment during both passage-induced and natural aging by simultaneously suppressing nuclear factor-κB and decreasing mTOR signaling with the induction of autophagy. Thus, the strategy of pharmacological intervention with the deep learning-predicted compound POG could rejuvenate aged TSPCs and improve the regenerative capacity of aged tendons.

Ataluren prevented bone loss induced by ovariectomy and aging in mice through the BMP-SMAD signaling pathway.

Both estrogen deficiency and aging may lead to osteoporosis. Developing novel drugs for treating osteoporosis is a popular research direction. We screened several potential therapeutic agents through a new deep learning-based efficacy prediction system (DLEPS) using transcriptional profiles for osteoporosis. DLEPS screening led to a potential novel drug examinee, ataluren, for treating osteoporosis. Ataluren significantly reversed bone loss in ovariectomized mice. Next, ataluren significantly increased human bone marrow-derived mesenchymal stem cell (hBMMSC) osteogenic differentiation without cytotoxicity, indicated by the high expression index of osteogenic differentiation genes (OCN , BGLAP, ALP, COL1A, BMP2, RUNX2). Mechanistically, ataluren exerted its function through the BMP-SMAD pathway. Furthermore, it activated SMAD phosphorylation but osteogenic differentiation was attenuated by BMP2-SMAD inhibitors or small interfering RNA of BMP2. Finally, ataluren significantly reversed bone loss in aged mice. In summary, our findings suggest that the DLEPS-screened ataluren may be a therapeutic agent against osteoporosis by aiding hBMMSC osteogenic differentiation.

Nuclear lamina erosion-induced resurrection of endogenous retroviruses underlies neuronal aging.

The primate frontal lobe (FL) is sensitive to aging-related neurocognitive decline. However, the aging-associated molecular mechanisms remain unclear. Here, using physiologically aged non-human primates (NHPs), we depicted a comprehensive landscape of FL aging with multidimensional profiling encompassing bulk and single-nucleus transcriptomes, quantitative proteome, and DNA methylome. Conjoint analysis across these molecular and neuropathological layers underscores nuclear lamina and heterochromatin erosion, resurrection of endogenous retroviruses (ERVs), activated pro-inflammatory cyclic GMP-AMP synthase (cGAS) signaling, and cellular senescence in post-mitotic neurons of aged NHP and human FL. Using human embryonic stem-cell-derived neurons recapitulating cellular aging in vitro, we verified the loss of B-type lamins inducing resurrection of ERVs as an initiating event of the aging-bound cascade in post-mitotic neurons. Of significance, these aging-related cellular and molecular changes can be alleviated by abacavir, a nucleoside reverse transcriptase inhibitor, either through direct treatment of senescent human neurons in vitro or oral administration to aged mice.

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma.

Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

Halomonas spp., as chassis for low-cost production of chemicals.

Halomonas spp. are the well-studied platform organisms or chassis for next-generation industrial biotechnology (NGIB) due to their contamination-resistant nature combined with their fast growth property. Several Halomonas spp. have been studied regarding their genomic information and molecular engineering approaches. Halomonas spp., especially Halomonas bluephagenesis, have been engineered to produce various biopolyesters such as polyhydroxyalkanoates (PHA), proteins including surfactants and enzymes, small molecular compounds including amino acids and derivates, as well as organic acids. This paper reviews all the progress reported in the last 10 years regarding this robust microbial cell factory. KEY POINTS: • Halomonas spp. are robust chassis for low-cost production of chemicals • Genomic information of some Halomonas spp. has been revealed • Molecular tools and approaches for Halomonas spp. have been developed • Halomonas spp. are becoming more and more important for biotechnology.

The genetic algorithm-aided three-stage ensemble learning method identified a robust survival risk score in patients with glioma.

Ensemble learning is a kind of machine learning method which can integrate multiple basic learners together and achieve higher accuracy. Recently, single machine learning methods have been established to predict survival for patients with cancer. However, it still lacked a robust ensemble learning model with high accuracy to pick out patients with high risks. To achieve this, we proposed a novel genetic algorithm-aided three-stage ensemble learning method (3S score) for survival prediction. During the process of constructing the 3S score, double training sets were used to avoid over-fitting; the gene-pairing method was applied to reduce batch effect; a genetic algorithm was employed to select the best basic learner combination. When used to predict the survival state of glioma patients, this model achieved the highest C-index (0.697) as well as area under the receiver operating characteristic curve (ROC-AUCs) (first year = 0.705, third year = 0.825 and fifth year = 0.839) in the combined test set (n = 1191), compared with 12 other baseline models. Furthermore, the 3S score can distinguish survival significantly in eight cohorts among the total of nine independent test cohorts (P < 0.05), achieving significant improvement of ROC-AUCs. Notably, ablation experiments demonstrated that the gene-pairing method, double training sets and genetic algorithm make sure the robustness and effectiveness of the 3S score. The performance exploration on pan-cancer showed that the 3S score has excellent ability on survival prediction in five kinds of cancers, which was verified by Cox regression, survival curves and ROC curves together. To enable its clinical adoption, we implemented the 3S score and other two clinical factors as an easy-to-use web tool for risk scoring and therapy stratification in glioma patients.

The landscape of aging.

Aging is characterized by a progressive deterioration of physiological integrity, leading to impaired functional ability and ultimately increased susceptibility to death. It is a major risk factor for chronic human diseases, including cardiovascular disease, diabetes, neurological degeneration, and cancer. Therefore, the growing emphasis on "healthy aging" raises a series of important questions in life and social sciences. In recent years, there has been unprecedented progress in aging research, particularly the discovery that the rate of aging is at least partly controlled by evolutionarily conserved genetic pathways and biological processes. In an attempt to bring full-fledged understanding to both the aging process and age-associated diseases, we review the descriptive, conceptual, and interventive aspects of the landscape of aging composed of a number of layers at the cellular, tissue, organ, organ system, and organismal levels.

Robust prognostic model based on immune infiltration-related genes and clinical information in ovarian cancer.

Immune infiltration of ovarian cancer (OV) is a critical factor in determining patient's prognosis. Using data from TCGA and GTEx database combined with WGCNA and ESTIMATE methods, 46 genes related to OV occurrence and immune infiltration were identified. Lasso and multivariate Cox regression were applied to define a prognostic score (IGCI score) based on 3 immune genes and 3 types of clinical information. The IGCI score has been verified by K-M curves, ROC curves and C-index on test set. In test set, IGCI score (C-index = 0.630) is significantly better than AJCC stage (C-index = 0.541, p < 0.05) and CIN25 (C-index = 0.571, p < 0.05). In addition, we identified key mutations to analyse prognosis of patients and the process related to immunity. Chi-squared tests revealed that 6 mutations are significantly (p < 0.05) related to immune infiltration: BRCA1, ZNF462, VWF, RBAK, RB1 and ADGRV1. According to mutation survival analysis, we found 5 key mutations significantly related to patient prognosis (p < 0.05): CSMD3, FLG2, HMCN1, TOP2A and TRRAP. RB1 and CSMD3 mutations had small p-value (p < 0.1) in both chi-squared tests and survival analysis. The drug sensitivity analysis of key mutation showed when RB1 mutation occurs, the efficacy of six anti-tumour drugs has changed significantly (p < 0.05).

Oridonin Delays Aging Through the AKT Signaling Pathway.

Aging is a major risk factor for chronic diseases and disability in humans. Nowadays, no effective anti-aging treatment is available clinically. In this study, oridonin was selected based on the drug screening strategy similar to Connectivity MAP (CMAP) but upon transcriptomes of 102 traditional Chinese medicines treated cell lines. Oridonin is a diterpenoid isolated from Rabdosia rubescens. As reported, Oridonin exhibits a variety of pharmacological activities, including antitumor, antibacterial and anti-inflammatory activities. Here, we found that oridonin inhibited cellular senescence in human diploid fibroblasts (2BS and WI-38), manifested by decreased senescence-associated ß-galactosidase (SA-ß-gal) staining. Compared with the elderly control group, the positive cell rate in the oridonin intervention group was reduced to 48.5%. Notably, oridonin prolonged the lifespan of yeast by 48.9%, and extended the average life span of naturally aged mice by 21.6%. Our mice behavior experiments exhibited that oridonin significantly improved the health status of naturally aged mice. In addition, oridonin also delayed doxorubicin-induced cellular senescence and mouse senescence. Compared with the model group, the percentage of SA-ß-gal positive cells in the oridonin treatment group was reduced to 59.8%. It extended the average lifespan of mice by 53.8% and improved healthspan. Mechanistically, we showed that oridonin delayed aging through the AKT signaling pathway and reversed the genetic changes caused by doxorubicin-induced cell senescence. Therefore, oridonin is a potential candidate for the development of anti-aging drugs.

Deficiency of exopolysaccharides and O-antigen makes Halomonas bluephagenesis self-flocculating and amenable to electrotransformation.

Halomonas bluephagenesis, a haloalkaliphilic bacterium and native polyhydroxybutyrate (PHB) producer, is a non-traditional bioproduction chassis for the next generation industrial biotechnology (NGIB). A single-sgRNA CRISPR/Cas9 genome editing tool is optimized using dual-sgRNA strategy to delete large DNA genomic fragments (>50 kb) with efficiency of 12.5% for H. bluephagenesis. The non-essential or redundant gene clusters of H. bluephagenesis, including those encoding flagella, exopolysaccharides (EPSs) and O-antigen, are sequentially deleted using this improved genome editing strategy. Totally, ~3% of the genome is reduced with its rapid growth and high PHB-production ability unaffected. The deletion of EPSs and O-antigen gene clusters shows two excellent properties from industrial perspective. Firstly, the EPSs and O-antigen deleted mutant rapidly self-flocculates and precipitates within 20 min without centrifugation. Secondly, DNA transformation into the mutant using electroporation becomes feasible compared to the wild-type H. bluephagenesis. The genome-reduced H. bluephagenesis mutant reduces energy and carbon source requirement to synthesize PHB comparable to its wild type. The H. bluephagenesis chassis with a reduced genome serves as an improved version of a NGIB chassis for productions of polyhydroxyalkanoates (PHA) or other chemicals.

Single-layered phase-change metasurfaces achieving efficient wavefront manipulation and reversible chiral transmission.

Efficient control of the phase and polarization of light is of significant importance in modern optics and photonics. However, traditional methods are often accompanied with cascaded and bulky designs that cannot fulfill the ongoing demand for further integrations. Here, a single-layered metasurface composed of nonvolatile phase-change material Ge2Sb2Se4Te1 (GSST) is proposed with tunable spin-orbit interactions in subwavelength scale. According to the spin-dependent destructive or constructive interference, asymmetric transmission for circularly polarized incidence (extinction ratio > 8:1) can be achieved when GSST is in an amorphous state. Moreover, when GSST changes to crystalline state, reversed chiral transmission (extinction ratio > 12:1) can be observed due to the existence of intrinsic chirality. In addition, as the average cross-polarized transmitted amplitude is larger than 85%, arbitrary wavefront manipulations can be achieved in both states simultaneously based on the theory of Pancharatnam-Berry phase. As a proof of concept, several functional metasurface devices are designed and characterized to further demonstrate the validation of our design methodology. It is believed that these multifunctional devices with ultrahigh compactness are promising for various applications including chiroptical spectroscopy, EM communication, chiral imaging, and information encryption.

Multistate Nonvolatile Metamirrors with Tunable Optical Chirality.

Compared with conventional mirrors that behave as isotropic electromagnetic (EM) reflectors, metamirrors composed of periodically aligned artificial meta-atoms exhibit increased degrees of freedom for EM manipulations. However, the functionality of most metamirrors is fixed by design, and how to achieve active EM control is still elusive. Here, we propose a multistate metamirror based on the nonvolatile phase change material Ge2Sb2Te5 (GST) with four distinct functionalities that can be realized in the infrared region by exploiting the temperature-activated phase transition. When varying the crystallinity of GST, the metamirror has the capability to perform as a right-handed circular polarization chiral mirror, a narrowband achiral mirror, a left-handed circular polarization chiral mirror, or a broadband achiral mirror, respectively. The inner physics is further explained by the construction or cancellation of extrinsic two-dimensional chirality. As a proof of concept, experimental verification is carried out and the measured results agree well with their simulated counterparts. Such a multifunctional tunable metamirror could address a wide range of applications from sensing and spectroscopy to analytical chemistry and imaging.

Expression and Prognostic Characteristics of Ferroptosis-Related Genes in Colon Cancer.

Ferroptosis is a new type of programmed cell death, which occurs with iron dependence. Previous studies have showed that ferroptosis plays an important regulatory role in the occurrence and development of tumors. Colon cancer is one of the major morbidities and causes of mortality in the world. This study used RNA-seq and colon cancer clinical data to explore the relationship between ferroptosis-related genes and colon cancer. Based on the fifteen prognostic ferroptosis-related genes, two molecular subgroups of colon cancer were identified. Surprisingly, we also found cluster2 was characterized by lower mutation burden and expression of checkpoint genes, better survival, and higher expression of NOX1. Moreover, cluster2 has fewer BRAF mutations. We also found the expression of NOX1 is related to the status of BRAF. Finally, using 15 ferroptosis-related genes from The Cancer Genome Atlas cohort, we constructed a prognosis model, and this model may be used to predict the prognosis of patients in clinics.