Opposite Mechanical Preference of Bone/Nerve Regeneration in 3D-Printed Bioelastomeric Scaffolds/Conduits Consistently Correlated with YAP-Mediated Stem Cell Osteo/Neuro-Genesis.

To systematically unveil how substrate stiffness, a critical factor in directing cell fate through mechanotransduction, correlates with tissue regeneration, novel biodegradable and photo-curable poly(trimethylene carbonate) fumarates (PTMCFs) for fabricating elastomeric 2D substrates and 3D bone scaffolds/nerve conduits, are presented. These substrates and structures with adjustable stiffness serve as a unique platform to evaluate how this mechanical cue affects the fate of human umbilical cord mesenchymal stem cells (hMSCs) and hard/soft tissue regeneration in rat femur bone defect and sciatic nerve transection models; whilst, decoupling from topographical and chemical cues. In addition to a positive relationship between substrate stiffness (tensile modulus: 90-990 kPa) and hMSC adhesion, spreading, and proliferation mediated through Yes-associated protein (YAP), opposite mechanical preference is revealed in the osteogenesis and neurogenesis of hMSCs as they are significantly enhanced on the stiff and compliant substrates, respectively. In vivo tissue regeneration demonstrates the same trend: bone regeneration prefers the stiffer scaffolds; while, nerve regeneration prefers the more compliant conduits. Whole-transcriptome analysis further shows that upregulation of Rho GTPase activity and the downstream genes in the compliant group promote nerve repair, providing critical insight into the design strategies of biomaterials for stem cell regulation and hard/soft tissue regeneration through mechanotransduction.

Automatic marker-based alignment method for a nano-resolution full-field transmission X-ray microscope.

Driven by the development of X-ray optics, the spatial resolution of the full-field transmission X-ray microscope (TXM) has reached tens of nanometers and plays an important role in promoting the development of biomedicine and materials science. However, due to the thermal drift and the radial/axial motion error of the rotation stage, TXM computed tomography (CT) data are often associated with random image jitter errors along the horizontal and vertical directions during CT measurement. A nano-resolution 3D structure information reconstruction is almost impossible without a prior appropriate alignment process. To solve this problem, a fully automatic gold particle marker-based alignment approach without human intervention was proposed in this study. It can automatically detect, isolate, and register gold particles for projection image alignment with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. Simulated and experimental results confirmed the reliability and robustness of this method.

Genomic and metabonomic methods reveal the probiotic functions of swine-derived Ligilactobacillus salivarius.

BACKGROUND: As substitutes for antibiotics, probiotic bacteria protect against digestive infections caused by pathogenic bacteria. Ligilactobacillus salivarius is a species of native lactobacillus found in both humans and animals. Herein, a swine-derived Ligilactobacillus salivarius was isolated and shown to colonize the ileal mucous membrane, thereby promoting nutritional digestion, absorption, and immunity. To evaluate its probiotic role, the entire genome was sequenced, the genetic information was annotated, and the metabolic information was analyzed. RESULTS: The phylogenetic relationship indicated that the bacteria was closer to L. salivarius MT573555.1 and MT585431.1. Functional genes included transporters, membrane proteins, enzymes, heavy metal resistance proteins, and putative proteins; metabolism-related genes were the most abundant. The six types of metabolic pathways secreted by L. salivarius were mainly composed of secretory transmembrane proteins and peptides. The secretory proteins of L. salivarius were digestive enzymes, functional proteins that regulate apoptosis, antibodies, and hormones. Non-targeted metabolomic analysis of L. salivarius metabolites suggested that ceramide, pyrrolidone- 5- carboxylic acid, N2-acetyl-L-ornithine, 2-ethyl-2-hydroxybutyric acid, N-lactoyl-phenylalanine, and 12 others were involved in antioxidation, repair of the cellular membrane, anticonvulsant, hypnosis, and appetite inhibition. Metabolites of clavaminic acid, antibiotic X14889C, and five other types of bacteriocins were identified, namely phenyllactic acid, janthitrem G, 13-demethyl tacrolimus, medinoside E, and tertonasin. The adherence and antioxidation of L. salivarius were also predicted. No virulence genes were found. CONCLUSION: The main probiotic properties of L. salivarius were identified using genomic, metabonomic, and biochemical assays, which are beneficial for porcine feeding. Our results provided deeper insights into the probiotic effects of L. salivarius.

Device-Performance-Driven Heterogeneous Multiparty Learning for Arbitrary Images.

Multiparty learning (MPL) is an emerging framework for privacy-preserving collaborative learning. It enables individual devices to build a knowledge-shared model and remaining sensitive data locally. However, with the continuous increase of users, the heterogeneity gap between data and equipment becomes wider, which leads to the problem of model heterogeneous. In this article, we concentrate on two practical issues: data heterogeneous problem and model heterogeneous problem, and propose a novel personal MPL method named device-performance-driven heterogeneous MPL (HMPL). First, facing the data heterogeneous problem, we focus on the problem of various devices holding arbitrary data sizes. We introduce a heterogeneous feature-map integration method to adaptively unify the various feature maps. Meanwhile, to handle the model heterogeneous problem, as it is essential to customize models for adapting to the various computing performances, we propose a layer-wise model generation and aggregation strategy. The method can generate customized models based on the device's performance. In the aggregation process, the shared model parameters are updated through the rules that the network layers with the same semantics are aggregated with each other. Extensive experiments are conducted on four popular datasets, and the result demonstrates that our proposed framework outperforms the state of the art (SOTA).

Deep-learning-based ring artifact correction for tomographic reconstruction.

X-ray tomography has been widely used in various research fields thanks to its capability of observing 3D structures with high resolution non-destructively. However, due to the nonlinearity and inconsistency of detector pixels, ring artifacts usually appear in tomographic reconstruction, which may compromise image quality and cause nonuniform bias. This study proposes a new ring artifact correction method based on the residual neural network (ResNet) for X-ray tomography. The artifact correction network uses complementary information of each wavelet coefficient and a residual mechanism of the residual block to obtain high-precision artifacts through low operation costs. In addition, a regularization term is used to accurately extract stripe artifacts in sinograms, so that the network can better preserve image details while accurately separating artifacts. When applied to simulation and experimental data, the proposed method shows a good suppression of ring artifacts. To solve the problem of insufficient training data, ResNet is trained through the transfer learning strategy, which brings advantages of robustness, versatility and low computing cost.

HRD1 functions as a tumor suppressor in ovarian cancer by facilitating ubiquitination-dependent SLC7A11 degradation.

The E3 ubiquitin ligase 3-hydroxy-3-methylglutaryl reductase degradation (HRD1) was found to be a tumor suppressor in diverse types of cancers; we aimed to explore its expression pattern and biological function in ovarian cancer (OC). HRD1 expression in OC tumor tissues was detected using quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC). The overexpression plasmid of HRD1 was transfected into OC cells. Cell proliferation, colony formation, and apoptosis were analyzed using bromodeoxy uridineassay, colony formation assay, and flow cytometry, respectively. OC mice models were established to explore the effect of HRD1 on OC in vivo. Ferroptosis was evaluated by malondialdehyde, reactive oxygen species, and intracellular ferrous iron. Expressions offerroptosis-related factors were examined using qRT-PCR and western blot. Erastin and Fer-1 were, respectively, employed to promote or inhibit ferroptosis in OC cells. Online bioinformatics tool and co-immunoprecipitation assay were performed to predict and verify the interactive genes of HRD1 in OC cells, respectively. Gain-of-function studies were carried out to determine the roles of HRD1 in cell proliferation, apoptosis, and ferroptosis in vitro. HRD1 was under-expressed in OC tumor tissues. The overexpression of HRD1 inhibited OC cell proliferation and colony formation in vitro and suppressed OC tumor growth in vivo. The overexpression of HRD1 promoted cell apoptosis and ferroptosis in OC cell lines. HRD1 interacted with the solute carrier family 7 member 11 (SLC7A11) in OC cells, and HRD1 regulated the stability and ubiquitination in OC. SLC7A11 overexpression recovered the effect of HRD1 overexpression in OC cell lines. HRD1 inhibited tumor formation and promoted ferroptosis in OC through enhancing SLC7A11 degradation.

Feature detection network-based correction method for accurate nano-tomography reconstruction.

Driven by the development of advanced x-ray optics such as Fresnel zone plates, nano-resolution full-field transmission x-ray microscopy (Nano-CT) has become a powerful technique for the non-destructive volumetric inspection of objects and has long been developed at different synchrotron radiation facilities. However, Nano-CT data are often associated with random sample jitter because of the drift or radial/axial error motion of the rotation stage during measurement. Without a proper sample jitter correction process prior to reconstruction, the use of Nano-CT in providing accurate 3D structure information for samples is almost impossible. In this paper, to realize accurate 3D reconstruction for Nano-CT, a correction method based on a feature detection neural network, which can automatically extract target features from a projective image and precisely correct sample jitter errors, is proposed, thereby resulting in high-quality nanoscale 3D reconstruction. Compared with other feature detection methods, even if the target feature is overlapped by other high-density materials or impurities, the proposed Nano-CT correction method still acquires sub-pixel accuracy in geometrical correction and is more suitable for Nano-CT reconstruction because of its universal and faster correction speed. The simulated and experimental datasets demonstrated the reliability and validity of the proposed Nano-CT correction method.

Deep-learning-based image registration for nano-resolution tomographic reconstruction.

Nano-resolution full-field transmission X-ray microscopy has been successfully applied to a wide range of research fields thanks to its capability of non-destructively reconstructing the 3D structure with high resolution. Due to constraints in the practical implementations, the nano-tomography data is often associated with a random image jitter, resulting from imperfections in the hardware setup. Without a proper image registration process prior to the reconstruction, the quality of the result will be compromised. Here a deep-learning-based image jitter correction method is presented, which registers the projective images with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. This development is demonstrated and validated using synthetic and experimental datasets. The method is effective and readily applicable to a broad range of applications. Together with this paper, the source code is published and adoptions and improvements from our colleagues in this field are welcomed.

Synergistic effect of the anti-PD-1 antibody with blood stable and reduction sensitive curcumin micelles on colon cancer.

Curcumin (1,7-bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione) is a potent anticancer drug with versatile biological activities, while the clinical translation of curcumin is severely limited due to its hydrophobicity, rapid elimination, and metabolism in the blood circulation. Herein, we aim to unravel the potential of curcumin as a synergistic agent with immunotherapy in the treatment of cancers. In an effort to minimize premature release and improve the systemic bioavailability, a superior blood stable and reduction sensitive curcumin micellar formulation, of which the release can be triggered by cancer cells, is rationally designed. We have synthesized a telodendrimer (mPEG-PLA-(LA)4) capable of forming reversible disulfide crosslinked micelles (DCMs). The curcumin loaded DCMs (Cur/DCMs) are spherical with a uniform size of 24.6 nm. The in vitro release profile demonstrates that curcumin releases significantly slower from DCMs than that from non-crosslinked micelles (NCMs), while the release can be accelerated with the increasing concentration of reducing agent glutathione (GSH). Intravenous administration of Cur/DCMs stably retains curcumin in the bloodstream and efficiently improves the systemic bioavailability. Furthermore, Cur/DCMs exhibit synergistic anticancer efficacy when combined with the anti-PD-1 antibody in an MC-38 colon cancer xenograft model. Our results potentiate the integration of blood stable curcumin nanoformulation and immunotherapy for cancer treatment.

RNA-binding protein RALY reprogrammes mitochondrial metabolism via mediating miRNA processing in colorectal cancer.

OBJECTIVE: Dysregulated cellular metabolism is a distinct hallmark of human colorectal cancer (CRC). However, metabolic programme rewiring during tumour progression has yet to be fully understood. DESIGN: We analysed altered gene signatures during colorectal tumour progression, and used a complex of molecular and metabolic assays to study the regulation of metabolism in CRC cell lines, human patient-derived xenograft mouse models and tumour organoid models. RESULTS: We identified a novel RNA-binding protein, RALY (also known as hnRNPCL2), that is highly associated with colorectal tumour aggressiveness. RALY acts as a key regulatory component in the Drosha complex, and promotes the post-transcriptional processing of a specific subset of miRNAs (miR-483, miR-676 and miR-877). These miRNAs systematically downregulate the expression of the metabolism-associated genes (ATP5I, ATP5G1, ATP5G3 and CYC1) and thereby reprogramme mitochondrial metabolism in the cancer cell. Analysis of The Cancer Genome Atlas (TCGA) reveals that increased levels of RALY are associated with poor prognosis in the patients with CRC expressing low levels of mitochondrion-associated genes. Mechanistically, induced processing of these miRNAs is facilitated by their N6-methyladenosine switch under reactive oxygen species (ROS) stress. Inhibition of the m6A methylation abolishes the RALY recognition of the terminal loop of the pri-miRNAs. Knockdown of RALY inhibits colorectal tumour growth and progression in vivo and in organoid models. CONCLUSIONS: Collectively, our results reveal a critical metabolism-centric role of RALY in tumour progression, which may lead to cancer therapeutics targeting RALY for treating CRC.

Downregulated Long Noncoding RNA GAS5 Fails to Function as Decoy of CEBPB, Resulting in Increased GDF15 Expression and Rapid Ovarian Cancer Cell Proliferation.

Introduction: Growth differentiation factor 15 (GDF15), a newly identified member of transforming growth factor (GDF) superfamily, is upregulated in ovarian (OV) cancer. Upregulated GDF15 positively correlates with poor prognosis of OV cancer. Thus, elucidation of the mechanism underlying GDF15 overexpression is important. Method and Results: PROMO and JASPAR prediction software were used to find transcription factors for GDF15 expression. Data from TCGA database were analyzed to find long noncoding RNAs (lncRNAs) that were also abnormally expressed in OV cancer and had associations with GDF15 expression. Transcription factor CEBPB was predicted as an important regulator of GDF15, confirmed by luciferase reporter assay. However, CEBPB expression was not significantly changed in OV cancer. Data from TCGA database showed that lncRNA GAS5 is downregulated in OV cancer and its expression is negatively correlated with GDF15 expression. RPISeq showed high affinity of GAS5 to CEBPB and this was confirmed by RNA-binding protein immunoprecipitation assay. GAS5 overexpression increased its binding to CEBPB and consequently downregulated GDF15. GAS5 overexpression and GDF15 knockdown decreased viability and increased apoptosis of OV cancer cells, but CEBPB overexpression had opposite effects. However, simultaneous GAS5 and CEBPB overexpression or CEBPB overexpression together with GDF15 knockdown had no effect on cell viability and apoptosis. Conclusion: GAS5 functions as decoy of CEBPB, blocking transcription-promoting effect of CEBPB on GDF15.

Fingerprintable Hydrogel from Dual Reversible Cross-Linking Networks with Different Relaxation Times.

Most of the chemical hydrogels are stretchable, and deformed hydrogels may be recovered when the strain is removed. Such a hydrogel with viscoelastic property cannot be remolded under mild conditions. Here, we demonstrated that a combination of dual reversible cross-linking with different relaxation time scales could be used to develop a remoldable hydrogel responding to mild external stress. We fabricated the hydrogel with the surface-primary amine-rich silica nanodots (ca. 2.0 nm) and benzaldehyde-terminated poly(ethylene oxide)-poly(propylene oxide) (PPO)-poly(ethylene oxide) triblock copolymers (BAF127) at low temperature (<10 °C) to form the chemical cross-linking by Schiff-base bonding. Increasing temperature (>15 °C) induced the formation of physical cross-linking between the hydrophobic PPO segments. The latter network is weak and shows fast relaxation, whereas the former shows slow relaxation. The unique structural characteristics provides this hydrogel high stretchability and self-healability, as well as moldability. In particular, we demonstrated that this transparent hydrogel can keep the fine three-dimensional patterns of a fingerprint, which may be applied for collecting digital information of fingerprints for identification.

Multi-Task Learning Based Network Embedding.

The goal of network representation learning, also called network embedding, is to encode the network structure information into a continuous low-dimensionality embedding space where geometric relationships among the vectors can reflect the relationships of nodes in the original network. The existing network representation learning methods are always single-task learning, in which case these methods focus on preserving the proximity of nodes from one aspect. However, the proximity of nodes is dependent on both the local and global structure, resulting in a limitation on the node embeddings learned by these methods. In order to solve this problem, in this paper, we propose a novel method, Multi-Task Learning-Based Network Embedding, termed MLNE. There are two tasks in this method so as to preserve the proximity of nodes. The aim of the first task is to preserve the high-order proximity between pairwise nodes in the whole network. The second task is to preserve the low-order proximity in the one-hop area of each node. By jointly learning these tasks in the supervised deep learning model, our method can obtain node embeddings that can sufficiently reflect the roles that nodes play in networks. In order to demonstrate the efficacy of our MLNE method over existing state-of-the-art methods, we conduct experiments on multi-label classification, link prediction, and visualization in five real-world networks. The experimental results show that our method performs competitively.

HOXD-AS1 promotes cell proliferation, migration and invasion through miR-608/FZD4 axis in ovarian cancer.

Evidence is accumulating that long non-coding RNAs (lncRNAs) exert crucial roles in the incidence and progression of tumors. HOXD cluster antisense RNA 1 (HOXD-AS1), a cancer-related lncRNA, has been frequently reported to be involved in tumorigenesis and dysregulated in multiple types of human cancers; however, little is known about its role in ovarian cancer (OC). This study aimed to explore the role of HOXD-AS1 in OC and elucidate the potential mechanism involved. In the current study, HOXD-AS1 was observed to be upregulated in both OC tissues and cell lines. Besides, elevated expression of HOXD-AS1 was found to be associated with poor prognosis of OC patients. Furthermore, functional studies demonstrated that HOXD-AS1 promoted OC cell proliferation and colony formation, and enhanced the migration and invasion capabilities of OC cells. Mechanistically, HOXD-AS1 was detected to positively regulate the expression of frizzled family receptor 4 (FZD4) by competitively binding to miR-608. Taken together, HOXD4-AS1 exerts tumor-promoting functions through miR-608/FZD4 axis in OC. Our findings indicate that HOXD-AS1 may be used as a promising therapeutic target and a novel prognostic biomarker for OC.

Enhancing robustness of interdependent network under recovery based on a two-layer-protection strategy.

The robustness of coupled networks has attracted great attention recently, because the spread of failures from one network to its coupled network makes the coupled networks more vulnerable. Most existing achievements mainly focused on the integrity properties of coupled networks. However, failures also exist when networks are being reconstructed. Moreover, existing node-protection methods which aim to enhance the robustness of coupled networks only protect the influential nodes in one layer. In this paper, firstly, a two-layer-protection strategy is proposed to enhance the robustness of coupled networks under their reconstruction. Secondly, we adopt five strategies based on different centralities to select influential nodes, and propose a two-layer vision for each of them. Lastly, experiments on three different coupled networks show that by applying the two-layer-protection strategy, the robustness of coupled networks can be enhanced more efficiently compared with other methods which only protect nodes in one layer.

Curcumin-Loaded Blood-Stable Polymeric Micelles for Enhancing Therapeutic Effect on Erythroleukemia.

Curcumin has high potential in suppressing many types of cancer and overcoming multidrug resistance in a multifaceted manner by targeting diverse molecular targets. However, the rather low systemic bioavailability resulted from its poor solubility in water and fast metabolism/excretion in vivo has hampered its applications in cancer therapy. To increase the aqueous solubility of curcumin while retaining the stability in blood circulation, here we report curcumin-loaded copolymer micelles with excellent in vitro and in vivo stability and antitumor efficacy. The two copolymers used for comparison were methoxy-poly(ethylene glycol)-block-poly(ε-caprolactone) (mPEG-PCL) and N-(tert-butoxycarbonyl)-l-phenylalanine end-capped mPEG-PCL (mPEG-PCL-Phe(Boc)). In vitro cytotoxicity evaluation against human pancreatic SW1990 cell line showed that the delivery of curcumin in mPEG-PCL-Phe(Boc) micelles to cancer cells was efficient and dosage-dependent. The pharmacokinetics in ICR mice indicated that intravenous (i.v.) administration of curcumin/mPEG-PCL-Phe(Boc) micelles could retain curcumin in plasma much better than curcumin/mPEG-PCL micelles. Biodistribution results in Sprague-Dawley rats also showed higher uptake and slower elimination of curcumin into liver, lung, kidney, and brain, and lower uptake into heart and spleen of mPEG-PCL-Phe(Boc) micelles, as compared with mPEG-PCL micelles. Further in vivo efficacy evaluation in multidrug-resistant human erythroleukemia K562/ADR xenograft model revealed that i.v. administration of curcumin-loaded mPEG-PCL-Phe(Boc) micelles significantly delayed tumor growth, which was attributed to the improved stability of curcumin in the bloodstream and increased systemic bioavailability. The mPEG-PCL-Phe(Boc) micellar system is promising in overcoming the key challenge of curcumin's to promote its applications in cancer therapy.

UV light- and thermo-responsive supramolecular aggregates with tunable morphologies from the inclusion complexation of dendritic/linear polymers.

UV light- and thermo-responsive supramolecular aggregates with tunable morphologies were obtained through the inclusion complexation between a ß-CD containing dendritic host polymer and an azobenzene containing linear guest polymer. Morphologies of the aggregates could be adjusted by changing the molar ratio of host/guest polymers in the supramolecular polymers.

Effects of testosterone on the expression levels of AMH, VEGF and HIF-1α in mouse granulosa cells.

The present study aimed to investigate the effects of testosterone on mouse granulosa cell morphology, and the expression levels of anti-Müllerian hormone (AMH), vascular endothelial growth factor (VEGF) and hypoxia-inducible factor-1α (HIF-1α). Mouse granulosa cells were isolated and identified, and their morphology was examined using hematoxylin and eosin, F-actin, and follicle-stimulating hormone receptor staining. The mRNA expression levels of AMH, VEGF and HIF-1α were examined using reverse transcription-quantitative polymerase chain reaction, and their protein secretion levels were investigated using enzyme-linked immunosorbent assays. Testosterone treatment did not affect granulosa cell morphology; however, it significantly increased the mRNA expression levels of AMH and VEGF, and the protein secretion levels of AMH, VEGF and HIF-1α. These results suggested that testosterone was able to regulate the functions of granulosa cells by upregulating the expression levels of AMH, VEGF and HIF-1α.

Environmentally relevant impacts of nano-TiO2 on abiotic degradation of bisphenol A under sunlight irradiation.

Understanding the effects of nano-TiO2 particles on the environmental behaviors of organic pollutants in natural aquatic environments is of paramount importance considering that large amount of nano-TiO2 is being released in the environment. In this study, the effect of nano-TiO2 on the degradation of bisphenol A (BPA) in water was investigated under simulated solar light irradiation. The results indicated that nano-TiO2 at environmentally relevant concentration (1 mg/L) could significantly facilitate the abiotic degradation of BPA (also at low concentration) under mild solar light irradiation, with the pseudo first-order rate constant (kobs) for BPA degradation raised by 1-2 orders of magnitude. As reflected by the inhibition experiments, hydroxyl radicals (OHs) and superoxide radical species were the predominant active species responsible for BPA degradation. The reaction was affected by water pH, and the degradation rate was higher at acidic or alkaline conditions than that at neutral condition. Humic acid (HA) also affected the reaction rate, depending on its concentration. At lower concentration (the mass ratio of HA/nano-TiO2 was 0.1:1), HA improved the dispersion and stability of nano-TiO2 in aquatic environment. As a result, the yield of OHs by nano-TiO2 under sunlight irradiation increased and BPA degradation was facilitated. When the HA concentration increased, a coating of HA formed on the surface of nano-TiO2. Although nano-TiO2 became more stable, the light absorption by nano-TiO2 was significantly reduced due to the strong light absorption of the HA coated on the surface. As a consequence, the yield of OH decreased and BPA degradation was depressed. The results imply that nano-TiO2 at low concentration may distinctly mediate BPA degradation, and can contribute to the natural attenuation of some organic pollutants in aquatic environment with low level of HA. However, this process would be significantly reduced in the presence of high level of HA.

CO2-breathing and piercing polymersomes as tunable and reversible nanocarriers.

Despite numerous studies on utilizing polymeric vesicles as nanocapsules, fabrication of tunable molecular pathways on transportable vesicle walls remains challenging. Traditional methods for building penetrated channels on vesicular membrane surface often involve regulating the solvent polarity or photo-cross-linking. Herein, we developed a neat, green approach of stimulation by using CO2 gas as "molecular drill" to pierce macroporous structures on the membrane of polymersomes. By simply introducing CO2/N2 gases into the aqueous solution of self-assemblies without accumulating any byproducts, we observed two processes of polymeric shape transformation: "gas breathing" and "gas piercing." Moreover, the pathways in terms of dimension and time were found to be adjustable simply by controlling the CO2 stimulation level for different functional encapsulated molecules in accumulation, transport, and releasing. CO2-breathing and piercing of polymersomes offers a promising functionality to tune nanocapsules for encapsulating and releasing fluorescent dyes and bioactive molecules in living systems and also a unique platform to mimic the structural formation of nucleus pore complex and the breathing process in human beings and animals.