Angelicae dahuricae radix alleviates simulated microgravity induced bone loss by promoting osteoblast differentiation.

Bone loss caused by long-duration spaceflight seriously affects the skeletal health of astronauts. There are many shortcomings in currently available treatments for weightlessness-induced bone loss. The aim of this study was to evaluate the preventive effect of Angelica dahuricae Radix (AR) on simulated microgravity-induced bone loss. Here, we established a hind limb unloading (HLU) mouse model and treated HLU mice with AR (2 g/kg) for 4 weeks. Results indicated that AR significantly inhibited simulated microgravity-induced bone loss. In addition, the components in AR were analyzed using UPLC-MS/MS; results showed that a total of 224 compounds were detected in AR, which mainly contained 7 classes of components. Moreover, the network pharmacological predictions suggested that active ingredients of AR might act on PTGS2 to prevent bone loss. These results elucidate the efficacy of AR in preventing microgravity-induced bone loss and its potential for use in protecting the bone health of astronauts.

Targeting non-coding RNAs to overcome osimertinib resistance in EGFR-mutated non-small cell lung cancer.

Osimertinib, a third-generation inhibitor of epidermal growth factor receptor (EGFR) tyrosine kinase, exhibits remarkable efficacy in prolonging the survival of patients with non-small cell lung cancer (NSCLC) carrying EGFR mutations, surpassing the efficacy of first- and second-generation EGFR tyrosine kinases. Nevertheless, the emergence of osimertinib resistance is inevitable, necessitating an investigation into the underlying mechanisms. Increasing evidence has revealed that non-coding RNAs (ncRNAs), including microRNAs, long ncRNAs, and circular RNAs, play a significant role in the development and progression of lung cancer. These ncRNAs regulate essential signaling pathways, offering a novel avenue for understanding the fundamental mechanisms of osimertinib resistance. Recent studies have reported the significant impact of ncRNAs on osimertinib resistance, achieved through various mechanisms that modulate treatment sensitivity. We provide a concise overview of the functions and underlying mechanisms of extensively researched ncRNAs in the development of osimertinib resistance and emphasize their potential clinical application in EGFR-mutated NSCLC resistant to osimertinib. Finally, we discuss the obstacles that must be addressed to effectively translate ncRNA-based approaches into clinical practice.

Regulating TiO2 Deposition Using a Single-Anchored Ligand for High-Efficiency Perovskite Solar Cells.

Planar perovskite solar cells (PSCs), as a promising photovoltaic technology, have been extensively studied, with strong expectations for commercialization. Improving the power conversion efficiency (PCE) of PSCs is necessary to accelerate their practical application, in which the electron transport layer (ETL) plays a key part. Herein, a single-anchored ligand of phenylphosphonic acid (PPA) is utilized to regulate the chemical bath deposition of a TiO2 ETL, further improving the PCE of planar PSCs. The PPA possesses a steric benzene ring and a phosphoric acid group, which can inhibit the particle aggregation of the TiO2 film through steric hindrance, leading to optimized interface (ETL/perovskite) contact. In addition, the incorporated PPA can induce the upshift of the Fermi-level of the TiO2 film, which is beneficial for interfacial electron transport. As a consequence, the PSCs with PPA-TiO2 achieve a PCE of 24.83%, which is higher than that (24.21%) of PSCs with TiO2. In addition, the unencapsulated PSCs with PPA-TiO2 also exhibit enhanced stability when stored in ambient conditions.

BindingSiteDTI: differential-scale binding site modelling for drug-target interaction prediction.

MOTIVATION: Enhanced by contemporary computational advances, the prediction of drug-target interactions (DTIs) has become crucial in developing de novo and effective drugs. Existing deep learning approaches to DTI prediction are frequently beleaguered by a tendency to overfit specific molecular representations, which significantly impedes their predictive reliability and utility in novel drug discovery contexts. Furthermore, existing DTI networks often disregard the molecular size variance between macro molecules (targets) and micro molecules (drugs) by treating them at an equivalent scale that undermines the accurate elucidation of their interaction. RESULTS: We propose a novel DTI network with a differential-scale scheme to model the binding site for enhancing DTI prediction, which is named as BindingSiteDTI. It explicitly extracts multiscale substructures from targets with different scales of molecular size and fixed-scale substructures from drugs, facilitating the identification of structurally similar substructural tokens, and models the concealed relationships at the substructural level to construct interaction feature. Experiments conducted on popular benchmarks, including DUD-E, human, and BindingDB, shown that BindingSiteDTI contains significant improvements compared with recent DTI prediction methods. AVAILABILITY AND IMPLEMENTATION: The source code of BindingSiteDTI can be accessed at https://github.com/MagicPF/BindingSiteDTI.

Tough and Moldable Sustainable Cellulose-Based Structural Materials via Multiscale Interface Engineering.

All-natural materials derived from cellulose nanofibers (CNFs) are expected to be used to replace engineering plastics and have attracted much attention. However, the lack of crack extension resistance and 3D formability of nanofiber-based structural materials hinders their practical applications. Here, a multiscale interface engineering strategy is reported to construct high-performance cellulose-based materials. The sisal microfibers are surface treated to expose abundant active CNFs with positive charges, thereby enhancing their interfacial combination with the negatively charged CNFs. The robust multiscale dual network enables easy molding of multiscale cellulose-based structural materials into complex 3D special-shaped structures, resulting in nearly twofold and fivefold improvements in toughness and impact resistance compared with those of CNFs-based materials. Moreover, this multiscale interface engineering strategy endows cellulose-based structural materials with better comprehensive performance than petrochemical-based plastics and broadens cellulose's potential for lightweight applications as structural materials with lower environmental effects.

A potential therapeutic drug for osteoporosis: prospect for osteogenic LncRNAs.

Long non-coding RNAs (LncRNAs) play essential roles in multiple physiological processes including bone formation. Investigators have revealed that LncRNAs regulated bone formation through various signaling pathways and micro RNAs (miRNAs). However, several problems exist in current research studies on osteogenic LncRNAs, including sophisticated techniques, high cost for in vivo experiment, as well as low homology of LncRNAs between animal model and human, which hindered translational medicine research. Moreover, compared with gene editing, LncRNAs would only lead to inhibition of target genes rather than completely knocking them out. As the studies on osteogenic LncRNA gradually proceed, some of these problems have turned osteogenic LncRNA research studies into slump. This review described some new techniques and innovative ideas to address these problems. Although investigations on osteogenic LncRNAs still have obtacles to overcome, LncRNA will work as a promising therapeutic drug for osteoporosis in the near future.

MiR-12200-5p Targets Multiple Members of Wnt Signaling Pathway to Inhibit Osteoblast Differentiation and Bone Formation.

BACKGROUND: Osteoporosis is widespread and has become an emerging problem in the elderly. MicroRNAs could affect osteoblast differentiation and further regulate the occurrence of osteoporosis by targeting osteogenic differentiation signaling pathways. Our screening study found that miR-12200-5p simultaneously targeted six important factors within the Wnt signaling pathway (Apc, Tcf4, Tcf7, Wnt3a, Wnt5a, and Lrp6), indicating that miR-12200-5p might function as a strong regulator of this pathway. Since the Wnt pathway exists as one of the most essential pathways for osteogenic differentiation, miR-12200-5p may have an important role in the development of osteoporosis. OBJECTIVE: This study intended to explore the regulatory role and corresponding mechanism of miR-12200-5p in osteoblast differentiation. METHODS: We investigated the differentiation of osteoblast after the treatments of miR-12200-5p mimic and inhibitor. The interactions between miR-12200-5p and its target genes were also detected. Furthermore, the rescue effect of miR-12200-5p inhibitor on osteoporosis was evaluated using an ovariectomized osteoporosis mouse model. RESULTS: MiR-12200-5p significantly inhibited osteoblast differentiation, and bound with the 3'-UTR sequences of its target genes (Apc, Tcf4, Tcf7, Wnt3a, Wnt5a, and Lrp6) to reduce the expressions of these genes. The inhibition of miR-12200-5p would almost fully alleviate postmenopausal osteoporosis. CONCLUSION: MiR-12200-5p could strongly repress osteoblast differentiation and bone formation by targeting multiple members of the Wnt signaling pathway simultaneously. The study supplemented the theoretical and experimental basis for researching the mechanism of osteogenic differentiation and inspired the development of novel therapeutic strategies for osteoporosis.

Co-Polymer Carrier with Dual Advantages of Cartilage-Penetrating and Targeting Improves Delivery and Efficacy of MicroRNA Treatment of Osteoarthritis.

Osteoarthritis (OA) is a debilitating joint disease affecting nearly 400 million people with no efficient etiological therapies. OA is primarily identified by cartilage destruction, and gradual degeneration of the whole joint would happen when the OA progresses. Hence, cartilage has been identified as the primary therapeutic target of OA. Unfortunately, numerous barriers block the delivery of therapeutic agents into cartilage, including avascular traits and high hardness of the extracellular matrix. Herein, a cartilage-targeting peptide (CAP) modified polyvinylamine (PVAm)- poly (lactic-co-glycolic acid) (PLGA) copolymer (CAP-PVAm-PLGA) is designed, which can form spherical nanoparticles with the r-miR-140 (CPP-NPs). CPP-NPs possessed enhanced mechanical properties due to the introduction of PLGA to vehicles. Meanwhile, CAP endowed the cartilage targeting which facilitated CPP-NPs localization in cartilage. With such dual advantages, CPP-NPs exhibited outstanding penetrability and accumulation in cartilage even subchondral bone, and can penetrate to a depth of 1000 µm into human cartilage. The degeneration area of cartilage is reduced by 65% and synovial inflammation score by 80% in OA mice, and the microarchitecture of subchondral bone is also ameliorated. These studies established a promising platform for therapeutic RNA delivery in OA therapy that overcame the cartilage barriers.

Nucleic acid amplification with specific signal filtration and magnification for ultrasensitive colorimetric detection.

Recently, sensitive, fast and low cost nucleic acid isothermal amplification technologies (such as loop-mediated isothermal amplification, LAMP) have attracted great attention in the urgent needs of point-of-care testing (POCT) and regular epidemic prevention and control. However, unlike PCR which usually employs TaqMan probe to report specific signals, specific-signal-output strategies in isothermal amplification are immature and visual detection even rare, which limits their popularity in POCT. We hypothesize to address this issue by designing a visual-signal-report system to both filtrate and magnify the target information in isothermal amplification. In this work, we developed a specific signal filtration and magnification colorimetric isothermal sensing platform (SFMC for short) for ultrasensitive detection of DNA and RNA. SFMC consists of two processes: an isothermal amplification with specific signal filtration and a self-replication catalyzed hairpin assembly (SRCHA) for rapid target-specific signal magnification and outputting. With these unique properties, this biosensing platform could detect target DNA as low as 5 copies per reaction and target RNA as low as 10 copies per reaction by naked eyes. Benefited from the excellent colorimetric detection performance, this biosensing platform has been successfully used for African swine fever virus (ASFV) and SARS-CoV-2 detection.

An All-Natural Wood-Inspired Aerogel.

The oriented pore structure of wood endows it with a variety of outstanding properties, among which the low thermal conductivity has attracted researchers to develop wood-like aerogels as excellent thermal insulation materials. However, the increasing demands of environmental protection have put forward new and strict requirements for the sustainability of aerogels. Here, we report an all-natural wood-inspired aerogel consisting of all-natural ingredients and develop a method to activate the surface-inert wood particles to construct the aerogel. The obtained wood-inspired aerogel has channel structure similar to that of natural wood, endowing it with superior thermal insulation properties to most existing commercial sponges. In addition, remarkable fire retardancy and complete biodegradability are integrated. With the above outstanding performances, this sustainable wood-inspired aerogel will be an ideal substitute for the existing commercial thermal insulation materials.

Comprehensive ceRNA network for MACF1 regulates osteoblast proliferation.

BACKGROUND: Previous studies have shown that microtubule actin crosslinking factor 1 (MACF1) can regulate osteoblast proliferation and differentiation through non-coding RNA (ncRNA) in bone-forming osteoblasts. However, the role of MACF1 in targeting the competing endogenous RNA (ceRNA) network to regulate osteoblast differentiation remains poorly understood. Here, we profiled messenger RNA (mRNA), microRNA (miRNA), and long ncRNA (lncRNA) expression in MACF1 knockdown MC3TC­E1 pre­osteoblast cells. RESULTS: In total, 547 lncRNAs, 107 miRNAs, and 376 mRNAs were differentially expressed. Significantly altered lncRNAs, miRNAs, and mRNAs were primarily found on chromosome 2. A lncRNA-miRNA-mRNA network was constructed using a bioinformatics computational approach. The network indicated that mir-7063 and mir-7646 were the most potent ncRNA regulators and mef2c was the most potent target gene. Pathway enrichment analysis showed that the fluid shear stress and atherosclerosis, p53 signaling, and focal adhesion pathways were highly enriched and contributed to osteoblast proliferation. Importantly, the fluid shear stress and atherosclerosis pathway was co-regulated by lncRNAs and miRNAs. In this pathway, Dusp1 was regulated by AK079370, while Arhgef2 was regulated by mir-5101. Furthermore, Map3k5 was regulated by AK154638 and mir-466q simultaneously. AK003142 and mir-3082-5p as well as Ak141402 and mir-446 m-3p were identified as interacting pairs that regulate target genes. CONCLUSION: This study revealed the global expression profile of ceRNAs involved in the differentiation of MC3TC­E1 osteoblasts induced by MACF1 deletion. These results indicate that loss of MACF1 activates a comprehensive ceRNA network to regulate osteoblast proliferation.

Transfer RNAs-derived small RNAs and their application potential in multiple diseases.

The role of tRNAs is best known as adapter components of translational machinery. According to the central dogma of molecular biology, DNA is transcribed to RNA and in turn is translated into proteins, in which tRNA outstands by its role of the cellular courier. Recent studies have led to the revision of the canonical function of transfer RNAs (tRNAs), which indicates that tRNAs also serve as a source for short non-coding RNAs called tRNA-derived small RNAs (tsRNAs). tsRNAs play key roles in cellular processes by modulating complicated regulatory networks beyond translation and are widely involved in multiple diseases. Herein, the biogenesis and classification of tsRNAs were firstly clarified. tsRNAs are generated from pre-tRNAs or mature tRNAs and are classified into tRNA-derived fragments (tRFs) and tRNA halves (tiRNA). The tRFs include five types according to the incision loci: tRF-1, tRF-2, tRF-3, tRF-5 and i-tRF which contain 3' tiRNA and 5' tiRNA. The functions of tsRNAs and their regulation mechanisms involved in disease processes are systematically summarized as well. The mechanisms can elaborate on the specific regulation of tsRNAs. In conclusion, the current research suggests that tsRNAs are promising targets for modulating pathological processes, such as breast cancer, ischemic stroke, respiratory syncytial virus, osteoporosis and so on, and maintain vital clinical implications in diagnosis and therapeutics of various diseases.

MiR-138-5p Targets MACF1 to Aggravate Aging-related Bone Loss.

Senile osteoporosis is one of the major health problems in an aging society. Decreased bone formation due to osteoblast dysfunction may be one of the causes of aging-related bone loss. With increasing evidence suggesting that multiple microRNAs (miRNAs) play important roles in osteoblast function, the relationship between miRNAs and senile osteoporosis has become a popular research topic. Previously, we confirmed that mechanoresponsive miR-138-5p negatively regulated bone anabolic action. In this study, the miR-138-5p level was found to be negatively correlated with BMD and osteogenic markers in bone specimens of senile osteoporotic patients by bioinformatic analysis and experimental verification. Furthermore, high miR-138-5p levels aggravated the decrease of aged osteoblast differentiation in vitro and led to worse bone loss in aged osteoblastic miR-138-5p transgenic mice in vivo. We also previously identified that the target of miR-138-5p, microtubule actin cross-linking factor 1 (MACF1), could attenuate senile osteoporosis. Here, miR-138-5p was demonstrated to regulate aged osteoblast differentiation by targeting MACF1. Finally, the therapeutic inhibition of miR-138-5p counteracted the decrease in bone formation and aging-related bone loss in aged mice. Overall, our results highlight the crucial roles and the molecular mechanism of miR-138-5p in aging-related bone loss and may provide a powerful therapeutic target for ameliorating senile osteoporosis.

ß-Ecdysterone Enhanced Bone Regeneration Through the BMP-2/SMAD/RUNX2/Osterix Signaling Pathway.

Bone defects are a global public health problem. However, the available methods for inducing bone regeneration are limited. The application of traditional Chinese herbs for bone regeneration has gained popularity in recent years. ß-ecdysterone is a plant sterol similar to estrogen, that promotes protein synthesis in cells; however, its function in bone regeneration remains unclear. In this study, we investigated the function of ß-ecdysterone on osteoblast differentiation and bone regeneration in vitro and in vivo. MC3T3-E1 cells were used to test the function of ß-ecdysterone on osteoblast differentiation and bone regeneration in vitro. The results of the Cell Counting Kit-8 assay suggested that the proliferation of MC3T3-E1 cells was promoted by ß-ecdysterone. Furthermore, ß-ecdysterone influenced the expression of osteogenesis-related genes, and the bone regeneration capacity of MC3T3-E1 cells was detected by polymerase chain reaction, the alkaline phosphatase (ALP) test, and the alizarin red test. ß-ecdysterone could upregulate the expression of osteoblastic-related genes, and promoted ALP activity and the formation of calcium nodules. We also determined that ß-ecdysterone increased the mRNA and protein levels of components of the BMP-2/Smad/Runx2/Osterix pathway. DNA sequencing further confirmed these target effects. ß-ecdysterone promoted bone formation by enhancing gene expression of the BMP-2/Smad/Runx2/Osterix signaling pathway and by enrichment biological processes. For in vivo experiments, a femoral condyle defect model was constructed by drilling a bone defect measuring 3 mm in diameter and 4 mm in depth in the femoral condyle of 8-week-old Sprague Dawley male rats. This model was used to further assess the bone regenerative functions of ß-ecdysterone. The results of micro-computed tomography showed that ß-ecdysterone could accelerate bone regeneration, exhibiting higher bone volume, bone surface, and bone mineral density at each observation time point. Immunohistochemistry confirmed that the ß-ecdysterone also increased the expression of collagen, osteocalcin, and bone morphogenetic protein-2 in the experiment group at 4 and 8 weeks. In conclusion, ß-ecdysterone is a new bone regeneration regulator that can stimulate MC3T3-E1 cell proliferation and induce bone regeneration through the BMP-2/Smad/Runx2/Osterix pathway. This newly discovered function of ß-ecdysterone has revealed a new direction of osteogenic differentiation and has provided novel therapeutic strategies for treating bone defects.

Long noncoding RNA Lnc-DIF inhibits bone formation by sequestering miR-489-3p.

Osteoporosis has become a high incident bone disease along with the aging of human population. Long noncoding RNAs (LncRNAs) play an important role in osteoporosis incidence. In this study, we screened out an LncRNA negatively correlated with osteoblast differentiation, which was therefore named Lnc-DIF (differentiation inhibiting factor). Functional analysis proved that Lnc-DIF inhibited bone formation. A special structure containing multiple 53 nucleotide repeats was found in the trailing end of Lnc-DIF. Our study suggested that this repeat sequence could sequester multiple miR-489-3p and inhibit bone formation through miR-489-3p/SMAD2 axis. Moreover, siRNA of Lnc-DIF would rescue bone formation in both aging and ovariectomized osteoporosis mice. This study revealed a kind of LncRNA that could function as a sponge and regulate multiple miRNAs. RNA therapy techniques that target these LncRNAs could manipulate its downstream miRNA-target pathway with significantly higher efficiency and specificity. This provided potential therapeutic insight for RNA-based therapy for osteoporosis.

Polyvinylamine with moderate binding affinity as a highly effective vehicle for RNA delivery.

Polymeric carriers for RNA therapy offer potential advantages in terms of low immunogenicity, promoting modifiability and accelerating intracellular transport. However, balancing high transfection efficacy with low toxicity remains challenging with polymer-based vehicles; indeed, polyethyleneimine (PEI) remains the "gold standard" polymer for this purpose despite its significant toxicity limitations. Herein, we demonstrate the potential of polyvinylamine (PVAm), a commodity high-charge cationic polymer used in the papermaking industry and has similar structure with PEI, as an alternative carrier for RNA delivery. High levels of transfection of normal, tumor, and stem cells with a variety of RNA cargoes including small interfering RNA (siRNA), microRNA (miRNA), and recombinant RNA can be achieved in vitro under the proper complex conditions. While, both the anti-tumor effect achieved in a xenograft osteosarcoma model and lipid-lowering activity observed in a hyperlipidemia mice indicate the potential for highly effective in vivo activity. Of note, both the transfection efficiency and the cytotoxicity of PVAm compare more favorably with those of PEI, with PVAm offering the additional advantages of simpler purification and significantly lower cost. In addition, the mechanism for the difference in transfection efficiency between PVAm and PEI is explored by molecular docking as well as analyzing the process of association and dissociation between polymers (PVAm and PEI) and nucleic acids. Our research provides a novel, non-toxic, and cost-effective carrier candidate for next generation RNA therapy, and elucidates the potential mechanism of PVAm for its efficient delivery of RNA.

Novel machine learning models outperform risk scores in predicting hepatocellular carcinoma in patients with chronic viral hepatitis.

BACKGROUND & AIMS: Accurate hepatocellular carcinoma (HCC) risk prediction facilitates appropriate surveillance strategy and reduces cancer mortality. We aimed to derive and validate novel machine learning models to predict HCC in a territory-wide cohort of patients with chronic viral hepatitis (CVH) using data from the Hospital Authority Data Collaboration Lab (HADCL). METHODS: This was a territory-wide, retrospective, observational, cohort study of patients with CVH in Hong Kong in 2000-2018 identified from HADCL based on viral markers, diagnosis codes, and antiviral treatment for chronic hepatitis B and/or C. The cohort was randomly split into training and validation cohorts in a 7:3 ratio. Five popular machine learning methods, namely, logistic regression, ridge regression, AdaBoost, decision tree, and random forest, were performed and compared to find the best prediction model. RESULTS: A total of 124,006 patients with CVH with complete data were included to build the models. In the training cohort (n = 86,804; 6,821 HCC), ridge regression (area under the receiver operating characteristic curve [AUROC] 0.842), decision tree (0.952), and random forest (0.992) performed the best. In the validation cohort (n = 37,202; 2,875 HCC), ridge regression (AUROC 0.844) and random forest (0.837) maintained their accuracy, which was significantly higher than those of HCC risk scores: CU-HCC (0.672), GAG-HCC (0.745), REACH-B (0.671), PAGE-B (0.748), and REAL-B (0.712) scores. The low cut-off (0.07) of HCC ridge score (HCC-RS) achieved 90.0% sensitivity and 98.6% negative predictive value (NPV) in the validation cohort. The high cut-off (0.15) of HCC-RS achieved high specificity (90.0%) and NPV (95.6%); 31.1% of patients remained indeterminate. CONCLUSIONS: HCC-RS from the ridge regression machine learning model accurately predicted HCC in patients with CVH. These machine learning models may be developed as built-in functional keys or calculators in electronic health systems to reduce cancer mortality. LAY SUMMARY: Novel machine learning models generated accurate risk scores for hepatocellular carcinoma (HCC) in patients with chronic viral hepatitis. HCC ridge score was consistently more accurate than existing HCC risk scores. These models may be incorporated into electronic medical health systems to develop appropriate cancer surveillance strategies and reduce cancer death.