KDGene: knowledge graph completion for disease gene prediction using interactional tensor decomposition.

The accurate identification of disease-associated genes is crucial for understanding the molecular mechanisms underlying various diseases. Most current methods focus on constructing biological networks and utilizing machine learning, particularly deep learning, to identify disease genes. However, these methods overlook complex relations among entities in biological knowledge graphs. Such information has been successfully applied in other areas of life science research, demonstrating their effectiveness. Knowledge graph embedding methods can learn the semantic information of different relations within the knowledge graphs. Nonetheless, the performance of existing representation learning techniques, when applied to domain-specific biological data, remains suboptimal. To solve these problems, we construct a biological knowledge graph centered on diseases and genes, and develop an end-to-end knowledge graph completion framework for disease gene prediction using interactional tensor decomposition named KDGene. KDGene incorporates an interaction module that bridges entity and relation embeddings within tensor decomposition, aiming to improve the representation of semantically similar concepts in specific domains and enhance the ability to accurately predict disease genes. Experimental results show that KDGene significantly outperforms state-of-the-art algorithms, whether existing disease gene prediction methods or knowledge graph embedding methods for general domains. Moreover, the comprehensive biological analysis of the predicted results further validates KDGene's capability to accurately identify new candidate genes. This work proposes a scalable knowledge graph completion framework to identify disease candidate genes, from which the results are promising to provide valuable references for further wet experiments. Data and source codes are available at https://github.com/2020MEAI/KDGene.

DrugAI: a multi-view deep learning model for predicting drug-target activating/inhibiting mechanisms.

Understanding the mechanisms of candidate drugs play an important role in drug discovery. The activating/inhibiting mechanisms between drugs and targets are major types of mechanisms of drugs. Owing to the complexity of drug-target (DT) mechanisms and data scarcity, modelling this problem based on deep learning methods to accurately predict DT activating/inhibiting mechanisms remains a considerable challenge. Here, by considering network pharmacology, we propose a multi-view deep learning model, DrugAI, which combines four modules, i.e. a graph neural network for drugs, a convolutional neural network for targets, a network embedding module for drugs and targets and a deep neural network for predicting activating/inhibiting mechanisms between drugs and targets. Computational experiments show that DrugAI performs better than state-of-the-art methods and has good robustness and generalization. To demonstrate the reliability of the predictive results of DrugAI, bioassay experiments are conducted to validate two drugs (notopterol and alpha-asarone) predicted to activate TRPV1. Moreover, external validation bears out 61 pairs of mechanism relationships between natural products and their targets predicted by DrugAI based on independent literatures and PubChem bioassays. DrugAI, for the first time, provides a powerful multi-view deep learning framework for robust prediction of DT activating/inhibiting mechanisms.

DRONet: effectiveness-driven drug repositioning framework using network embedding and ranking learning.

As one of the most vital methods in drug development, drug repositioning emphasizes further analysis and research of approved drugs based on the existing large amount of clinical and experimental data to identify new indications of drugs. However, the existing drug repositioning methods didn't achieve enough prediction performance, and these methods do not consider the effectiveness information of drugs, which make it difficult to obtain reliable and valuable results. In this study, we proposed a drug repositioning framework termed DRONet, which make full use of effectiveness comparative relationships (ECR) among drugs as prior information by combining network embedding and ranking learning. We utilized network embedding methods to learn the deep features of drugs from a heterogeneous drug-disease network, and constructed a high-quality drug-indication data set including effectiveness-based drug contrast relationships. The embedding features and ECR of drugs are combined effectively through a designed ranking learning model to prioritize candidate drugs. Comprehensive experiments show that DRONet has higher prediction accuracy (improving 87.4% on Hit@1 and 37.9% on mean reciprocal rank) than state of the art. The case analysis also demonstrates high reliability of predicted results, which has potential to guide clinical drug development.

Decoding multilevel relationships with the human tissue-cell-molecule network.

Understanding the biological functions of molecules in specific human tissues or cell types is crucial for gaining insights into human physiology and disease. To address this issue, it is essential to systematically uncover associations among multilevel elements consisting of disease phenotypes, tissues, cell types and molecules, which could pose a challenge because of their heterogeneity and incompleteness. To address this challenge, we describe a new methodological framework, called Graph Local InfoMax (GLIM), based on a human multilevel network (HMLN) that we established by introducing multiple tissues and cell types on top of molecular networks. GLIM can systematically mine the potential relationships between multilevel elements by embedding the features of the HMLN through contrastive learning. Our simulation results demonstrated that GLIM consistently outperforms other state-of-the-art algorithms in disease gene prediction. Moreover, GLIM was also successfully used to infer cell markers and rewire intercellular and molecular interactions in the context of specific tissues or diseases. As a typical case, the tissue-cell-molecule network underlying gastritis and gastric cancer was first uncovered by GLIM, providing systematic insights into the mechanism underlying the occurrence and development of gastric cancer. Overall, our constructed methodological framework has the potential to systematically uncover complex disease mechanisms and mine high-quality relationships among phenotypical, tissue, cellular and molecular elements.

Efficacy and safety of Qingda granule versus valsartan capsule in Chinese grade 1 hypertensive patients with low-moderate risk: A randomized, double-blind, double dummy, non-inferiority, multi-center trial.

BACKGROUND: The efficacy and safety of Qingda granule (QDG) in managing blood pressure (BP) among grade 1 hypertensive patients with low-moderate risk remain uncertain. METHODS: In the randomized, double-blind, double dummy, non-inferiority and multicenter trial, 552 patients with grade 1 hypertension at low-moderate risk were assigned at a ratio of 1:1 to receive either QDG or valsartan for 4 weeks, followed up by a subsequent 4 weeks. RESULTS: Post-treatment, clinic systolic/diastolic BPs (SBP/DBP) were reduced by a mean change of 9.18/4.04 mm Hg in the QDG group and 9.85/5.05 mm Hg in the valsartan group (SBP P = 0.47, DBP P = 0.16). Similarly, 24-hour, daytime and nighttime BPs were proportional in both groups (P > 0.05) after 4 weeks treatment. After discontinuing medications for 4 weeks, the mean reduction of clinic SBP/DBP were 0.29/0.57 mm Hg in the QDG group compared to -1.59/-0.48 mm Hg in the valsartan group (SBP P = 0.04, DBP P = 0.04). Simultaneously, the 24-hour SBP/DBP were reduced by 0.9/0.31 mm Hg in the QDG group and -1.66/-1.08 mm Hg in the valsartan group (SBP P = 0.006, DBP P = 0.02). And similar results were observed regarding the outcomes of daytime and nighttime BPs. There was no difference in occurrence of adverse events between two groups (P > 0.05). CONCLUSION: QDG proves to be efficacious for grade 1 hypertension at a low-to-medium risk, even after discontinuation of the medication for 4 weeks. These findings provide a promising option for managing grade 1 hypertension and suggest the potential for maintaining stable BP through intermittent administration of QDG. TRIAL REGISTRATION: ChiCTR2000033890.

Apoptotic bodies encapsulating Ti2N nanosheets for synergistic chemo-photothermal therapy.

Extracellular vesicles (EVs) have great potential in oncology drug delivery because of their unique biological origin. Apoptotic bodies (ABs), as a member of the EV family, offer distinct advantages in terms of size, availability and membrane properties, but have been neglected for a long time. Here, using ABs and Ti2N nanosheets, we propose a novel drug delivery system (Ti2N-DOX@ABs), which exhibit a homologous targeting ability for dual-strategy tumor therapy with intrinsic biological property. The experimental results demonstrate that such a drug delivery system possesses a drug loading capacity of 496.5% and a near-infrared photothermal conversion efficiency of 38.4%. In addition, the investigation of drug internalization process proved that Ti2N-DOX@ABs featured a supreme biocompatibility. Finally, the dual-strategy response based on photothermal and chemotherapeutic effects was studied under near-infrared laser radiation. This work explores the opportunity of apoptosome membranes in nanomedicine systems, which provides a technical reference for cancer-oriented precision medicine research.

Ecological and functional differences of abundant and rare sub-communities in wastewater treatment plants across China.

The microbial community in activated sludge is composed of a small number of abundant sub-community with high abundance and a large number of rare sub-community with limited abundance. Our knowledge regarding the ecological properties of both abundant and rare sub-communities in activated sludge is limited. This article presented an analysis of functional prediction, assembly mechanisms, and biogeographic distribution characteristics of abundant and rare sub-communities in 211 activated sludge samples from 60 wastewater treatment plants across China. Moreover, this study investigated the dominant factors influencing the community structure of these two microbial groups. The results showed that the functions associated with carbon and nitrogen cycling were primarily detected in abundant sub-community, while rare sub-community were primarily involved in sulfur cycling. Both microbial groups were mainly influenced by dispersal limitation, which, to some extent, resulted in a distance-decay relationship in their biogeographic distribution. Moreover, a higher spatial turnover rate of rare sub-communities (0.0887) suggested that spatial differences in microbial community structure among different WWTPs may mainly result from rare sub-community. Moreover, SEM showed that geographic locations affected rare sub-communities greatly, which agreed with their higher dispersal limitation and turnover rate. In contrast, influent characteristics showed stronger correlations with abundant sub-communities, suggesting that abundant sub-community may contribute more to the removal of pollutants. This study enhanced our understanding of abundant and rare microorganisms in activated sludge especially the role of rare species and provided scientific evidence for precise regulation and control of wastewater treatment plants.

STIL/AURKA axis promotes cell proliferation by influencing primary cilia formation in bladder cancer.

BACKGROUND: The primary cilia (PC) is a microtubule-based and nonmotile organelle which protrudes from the surface of almost all mammalian cells. At present, PC has been found to be a deficiency or loss in multiple cancers. Restoring PC could be a novel targeting therapy strategy. Our research showed that PC was reduced in human bladder cancer (BLCA) cells, and PC deficiency promotes cell proliferation. However, the concrete mechanisms remain unknown. SCL/TAL1 interrupting locus (STIL), a PC-related protein, was screened in our previous study and could influence the cell cycle by regulating PC in tumor cells. In this study, we aimed to elucidate the function of STIL for PC to explore the underlying mechanism of PC in BLCA. METHODS: Public database analysis, western blot, and enzyme-linked immunosorbent assay (ELISA) were used to screen genes and explore gene expression alteration. Immunofluorescence and western blot were utilized to investigate PC. Wound healing assay, clone formation assay, and CCK-8 assay were used to explore cell migration, growth, and proliferation. The co-immunoprecipitation and western blot were employed to reveal the interaction of STIL and AURKA. RESULTS: We found that high STIL expression is correlated with poor outcomes of BLCA patients. Further analysis revealed that STIL overexpression could inhibit PC formation, activate SHH signaling pathways, and promote cell proliferation. In contrast, STIL-knockdown could promote PC formation, inactivate SHH signaling, and inhibit cell proliferation. Furthermore, we found that the regulatory functions of STIL for PC depend on AURKA. STIL could influence proteasome activity and maintain AURKA stabilization. AURKA-knockdown could reverse PC deficiency caused by STIL overexpression for PC in BLCA cells. We observed that co-knockdown in STIL and AURKA significantly enhanced PC assembly. CONCLUSION: In summary, our result provides a potential therapy target for BLCA based on the restoration of PC.

The role of the core microorganisms in the microbial interactions in activated sludge.

In order to gain a deeper understanding of the microbial interactions in wastewater treatment plants (WWTPs) in China and clarify the role of the core community in the microbial interactions in activated sludge (AS), this study used a molecular ecological network approach based on random matrix theory to construct co-occurrence networks of the core microorganisms (CoreN), the whole AS community (WholeN) and the microbial communities without the core microorganisms (OtherN), respectively. It was shown that the WholeN had more complex and tighter connections compared with the OtherN, because of its higher total number of nodes, higher average clustering coefficient, and shorter average geodesic distance. The proportions of positive links in the CoreN, WholeN and OtherN were gradually decreased, indicating that the core microorganisms promoted cooperation between AS microorganisms. Moreover, higher robustness after random removal of 50% of the nodes of the WholeN (0.2836 ± 0.0311) was observed than the robustness of the OtherN (0.1152 ± 0.0263). In addition, the vulnerability of OtherN (0.0514) is significantly higher than WholeN (0.0225). Meanwhile, the average ratio of negative/positive cohesion, was significantly decreased when the core microorganisms were removed. These results demonstrated that core community could strengthen the stability of the ecological network in AS. By discerning the key factors affecting ecological network, AS temperature was observed to have a strong correlation with all three networks. Moreover, pollutants in wastewater shown stronger correlations with the CoreN and WholeN, supporting the point that core community play a critical role in pollutant removal in WWTPs to a certain extent.

Wearable SERS Sensor Based on Omnidirectional Plasmonic Nanovoids Array with Ultra-High Sensitivity and Stability.

Surface-enhanced Raman spectroscopy (SERS) is a promising technology for wearable sensors due to its fingerprint spectrum and high detection sensitivity. However, since SERS-activity is sensitive to both the distribution of "hotspots" and excitation angle, it is profoundly challenging to develop a wearable SERS sensor with high stability under various deformations during movements. Herein, inspired by omnidirectional light-harvesting of the compound eye of Xenos Peckii, a wearable SERS sensor is developed using omnidirectional plasmonic nanovoids array (OPNA), which is prepared by assembling a monolayer of metal nanoparticles into the artificial plasmonic compound-eye (APC). Specifically, APC is an interconnected frame containing omnidirectional "pockets" and acts as an "armour", not only rendering a broadband and omnidirectional enhancement of "hotspots" in the delicate nanoparticles array, but also maintaining an integrity of the "hotspots" against external mechanical deformations. Furthermore, an asymmetry super-hydrophilic pattern is fabricated on the surface of OPNA, endowing the hydrophobic OPNA with the ability to spontaneously extract and concentrate the analytes from sweat. Such an armored SERS sensor can enable the wearable and in situ analysis with high sensitivity and stability, exhibiting great potential in point-of-care analysis.

The regulatory module MdBT2-MdMYB88/MdMYB124-MdNRTs regulates nitrogen usage in apple.

Less than 40% of the nitrogen (N) fertilizer applied to soil is absorbed by crops. Thus, improving the N use efficiency of crops is critical for agricultural development. However, the underlying regulation of these processes remains largely unknown, particularly in woody plants. By conducting yeast two-hybrid assays, we identified one interacting protein of MdMYB88 and MdMYB124 in apple (Malus × domestica), namely BTB and TAZ domain protein 2 (MdBT2). Ubiquitination and protein stabilization analysis revealed that MdBT2 ubiquitinates and degrades MdMYB88 and MdMYB124 via the 26S proteasome pathway. MdBT2 negatively regulates nitrogen usage as revealed by the reduced fresh weight, dry weight, N concentration, and N usage index of MdBT2 overexpression calli under low-N conditions. In contrast, MdMYB88 and MdMYB124 increase nitrate absorption, allocation, and remobilization by regulating expression of MdNRT2.4, MdNRT1.8, MdNRT1.7, and MdNRT1.5 under N limitation, thereby regulating N usage. The results obtained illustrate the mechanism of a regulatory module comprising MdBT2-MdMYB88/MdMYB124-MdNRTs, through which plants modulate N usage. These data contribute to a molecular approach to improve the N usage of fruit crops under limited N acquisition.

Abscisic acid insensitive 4 interacts with ICE1 and JAZ proteins to regulate ABA signaling-mediated cold tolerance in apple.

Abscisic acid is involved in the regulation of cold stress response, but its molecular mechanism remains to be elucidated. In this study, we demonstrated that the APETALA2/ethylene responsive factor (AP2/ERF) family protein MdABI4 positively regulates abscisic acid-mediated cold tolerance in apple. We found that MdABI4 interacts with MdICE1, a key regulatory protein involved in the cold stress response, and enhances the transcriptional regulatory function of MdICE1 on its downstream target gene MdCBF1, thus improving abscisic acid-mediated cold tolerance. The jasmonate-ZIM domain (JAZ) proteins MdJAZ1 and MdJAZ2 negatively modulate MdABI4-improved cold tolerance in apple by interacting with the MdABI4 protein. Further investigation showed that MdJAZ1 and MdJAZ2 interfere with the interaction between the MdABI4 and MdICE1 proteins. Together, our data revealed that MdABI4 integrates jasmonic acid and abscisic acid signals to precisely modulate cold tolerance in apple through the JAZ-ABI4-ICE1-CBF regulatory cascade. These findings provide insights into the crosstalk between jasmonic acid and abscisic acid signals in response to cold stress.

A novel HIF1α-STIL-FOXM1 axis regulates tumor metastasis.

BACKGROUND: Metastasis is the major cause of morbidity and mortality in cancer that involves in multiple steps including epithelial-mesenchymal transition (EMT) process. Centrosome is an organelle that functions as the major microtubule organizing center (MTOC), and centrosome abnormalities are commonly correlated with tumor aggressiveness. However, the conclusive mechanisms indicating specific centrosomal proteins participated in tumor progression and metastasis remain largely unknown. METHODS: The expression levels of centriolar/centrosomal genes in various types of cancers were first examined by in silico analysis of the data derived from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and European Bioinformatics Institute (EBI) datasets. The expression of STIL (SCL/TAL1-interrupting locus) protein in clinical specimens was further assessed by Immunohistochemistry (IHC) analysis and the oncogenic roles of STIL in tumorigenesis were analyzed using in vitro and in vivo assays, including cell migration, invasion, xenograft tumor formation, and metastasis assays. The transcriptome differences between low- and high-STIL expression cells were analyzed by RNA-seq to uncover candidate genes involved in oncogenic pathways. The quantitative polymerase chain reaction (qPCR) and reporter assays were performed to confirm the results. The chromatin immunoprecipitation (ChIP)-qPCR assay was applied to demonstrate the binding of transcriptional factors to the promoter. RESULTS: The expression of STIL shows the most significant increase in lung and various other types of cancers, and is highly associated with patients' survival rate. Depletion of STIL inhibits tumor growth and metastasis. Interestingly, excess STIL activates the EMT pathway, and subsequently enhances cancer cell migration and invasion. Importantly, we reveal an unexpected role of STIL in tumor metastasis. A subset of STIL translocate into nucleus and associate with FOXM1 (Forkhead box protein M1) to promote tumor metastasis and stemness via FOXM1-mediated downstream target genes. Furthermore, we demonstrate that hypoxia-inducible factor 1α (HIF1α) directly binds to the STIL promoter and upregulates STIL expression under hypoxic condition. CONCLUSIONS: Our findings indicate that STIL promotes tumor metastasis through the HIF1α-STIL-FOXM1 axis, and highlight the importance of STIL as a promising therapeutic target for lung cancer treatment.

CYP1B1-catalyzed 4-OHE2 promotes the castration resistance of prostate cancer stem cells by estrogen receptor α-mediated IL6 activation.

BACKGROUND: Resistance to androgen deprivation therapy remains a major challenge for the clinical treatment of patients with castration-resistant prostate cancer (CRPC). CYP1B1, a critical enzyme that catalyzes the conversion of estradiol to 4-Hydroxy-17ß-estradiol (4-OHE2), has been reported to promote the development and progression of hormone-related cancer, but its role in CRPC is unclear. METHODS: To explore the underlying mechanism which CYP1B1 promotes the prostate cancer stem cells (PCSCs) characteristics, bioinformatics analyses of human clinical prostate cancer (PCa) datasets were performed. CYP1B1, IL6, and estrogen receptor-α (ERα) expression levels were evaluated in PCa and CRPC tissues via immunohistochemistry. The high-performance liquid chromatography-mass spectrometry assay was carried out to examine intracellular 4-OHE2 levels. Serum-free suspension culture and flow cytometry assays were performed to evaluate PCSCs. Chromatin immunoprecipitation was used to validate that 4-OHE2 recruited ERα to the IL6 promoter. RESULTS: CYP1B1 expression was significantly increased in CRPC tissues and androgen-independent PCa cell lines. CYP1B1+ PCa cells were significantly enriched in bicalutamide-treated LNCaP cells, and CYP1B1 knockdown reduced the cell viability under bicalutamide treatment. In addition, CYP1B1 knockdown decreased the intracellular 4-OHE2 concentration, accompanied by reduced PCSC characteristics. In PCa cells, 4-OHE2 stimulated ERα transcriptional activity and upregulated the expression of IL6 and downstream genes of the IL6-STAT3 signaling. 4-OHE2 increased cell viability under bicalutamide treatment and promoted PCSC characteristics, while IL6 neutralizing antibody reversed these effects. Mechanistically, siERα and the ER antagonist ICI182780 significantly attenuated 4-OHE2-induced IL6 expression, and 4-OHE2 promoted the binding of ERα to the estrogen response element of the IL6 promoter. CONCLUSIONS: Our findings indicate that CYP1B1-catalyzed 4-OHE2 enhanced PCSC characteristics and attenuated bicalutamide sensitivity by ERα-mediated the IL6-STAT3 pathway activation. Our study further emphasizes the role of CYP1B1 in castration resistance and illustrates a novel mechanism of CRPC development. Video Abstract.

The ERα-NRF2 signalling axis promotes bicalutamide resistance in prostate cancer.

BACKGROUND: Bicalutamide is a nonsteroidal antiandrogen widely used as a first-line clinical treatment for advanced prostate cancer (PCa). Although patients initially show effective responses to bicalutamide treatment, resistance to bicalutamide frequently occurs and leads to the development of castration-resistant PCa (CRPC). This research investigated the roles of the oestrogen receptor α (ERα)-nuclear factor E2-related factor 2 (NRF2) signalling pathway in bicalutamide resistance in PCa cells. METHODS: We performed bioinformatic analysis and immunohistochemical staining on normal and cancerous prostate tissue to evaluate ERα and NRF2 expression and their correlation. Gene expression and localization in PCa cell lines were further investigated using real-time reverse transcription PCR/Western blotting and immunofluorescence staining. We treated PCa cells with the ER inhibitor tamoxifen and performed luciferase reporter assays and chromatin immunoprecipitation (ChIP) assays to understand ERα-dependent NRF2 expression. Overexpression and knockdown of ERα and NRF2 were used to explore the potential role of the ERα-NRF2 signalling axis in bicalutamide resistance in PCa cells. RESULTS: We found that the expression of ERα and NRF2 was positively correlated and was higher in human CRPC tissues than in primary PCa tissues. Treatment with oestrogen or bicalutamide increased the expression of ERα and NRF2 as well as NRF2 target genes in PCa cell lines. These effects were blocked by pretreatment with tamoxifen. ChIP assays demonstrated that ERα directly binds to the oestrogen response element (ERE) in the NRF2 promoter. This binding led to increased transcriptional activity of NRF2 in a luciferase reporter assay. Activation of the ERα-NRF2 signalling axis increased the expression of bicalutamide resistance-related genes. Inhibition of this signalling axis by knockdown of ERα or NRF2 downregulated the expression of bicalutamide resistance-related genes and inhibited the proliferation and migration of PCa cells. CONCLUSIONS: We demonstrated the transcriptional interaction between ERα and NRF2 in CRPC tissues and cell lines by showing the direct binding of ERα to the ERE in the NRF2 promoter under oestrogen treatment. Activation of the ERα-NRF2 signalling axis contributes to bicalutamide resistance in PCa cells, suggesting that the ERα-NRF2 signalling axis is a potential therapeutic target for CRPC. Video Abstract.

Novel Colorectal Endoscopic Submucosal Dissection With Double-Endoscope and Snare-Based Traction.

BACKGROUND: Colorectal endoscopic submucosal dissection is technically demanding, and the traction offered by gravity, cap, or clip-with-line during conventional endoscopic submucosal dissection remains unsatisfactory. Robotic systems are still under development and are expensive. We proposed double-scope endoscopic submucosal dissection with strong and adjustable traction offered by snaring the lesion with additional scope. OBJECTIVE: This study aimed to test the novel double-scope endoscopic submucosal dissection with snare-based traction. DESIGN: This was a retrospective study that reviewed double-scope endoscopic submucosal dissection compared with matched conventional endoscopic submucosal dissection, and size, location, morphology, and pathology between groups were compared. SETTINGS: This study was conducted in a referral endoscopy center in a local hospital. PATIENTS: This study included patients with colorectal lesions receiving double-scope endoscopic submucosal dissection and matched conventional endoscopic submucosal dissection. MAIN OUTCOME MEASURES: The pathological completeness, procedure time, and complications were analyzed. RESULTS: Fifteen double-scope endoscopic submucosal dissection procedures, with 11 lesions located in the proximal colon with a median size of 40 mm, were performed. The median procedure time of double-scope endoscopic submucosal dissection was 32.45 (interquartile range, 16.03-38.20) minutes. The time required for second scope insertion was 2.57 (interquartile range, 0.95-6.75) minutes; for snaring, 3.03 (interquartile range, 2.12-6.62) minutes; and for actual endoscopic submucosal dissection, 28.23 (interquartile range, 7.90-37.00) minutes. All lesions were resected completely. No major complication was encountered. The procedure time was significantly shorter than that of 14 matched conventional endoscopic submucosal dissections (54.61 [interquartile range, 33.11-97.25] min; p = 0.021). LIMITATIONS: This was a single-center, single-operator, retrospective case-controlled study with limited cases. CONCLUSIONS: This study confirmed the feasibility of double-scope endoscopic submucosal dissection with snare-based traction to shorten procedure time and to simplify endoscopic submucosal dissection. Additional trials are required.

Triple-color fluorescence co-localization of PD-L1-overexpressing cancer exosomes.

Programed cell death ligand 1 (PD-L1) is a protein biomarker overexpressed on exosomes derived from tumor cells. It plays an important role in tumor diagnosis, screening, evaluation of therapeutic efficacy, and prognosis. In this study, a facile method is presented to detect PD-L1-overexpressing cancer exosomes with high specificity and sensitivity. First, gold nanospheres (GNSs) were attached to the bottom of an eight-well chambered slide by electrostatic adsorption, forming the detection substrate. Then, Cy5-labeled CD63 aptamers (i.e., the capture probes) were modified on the GNSs by Au-S bond. After adding samples containing target exosomes which were stained by membrane dyes DiI in advance, FAM-labeled PD-L1 aptamers (i.e., the immunoprobes) were added to recognize PD-L1 on the target exosomes. By triple-color fluorescence co-localization (TFC) of the Cy5, DiI, and FAM channels, highly sensitive and reliable detection of the PD-L1-overexpressing exosomes was achieved in the concentration range 7.78 × 101 to 7.78 × 104 particles/mL with a detection limit down to 6 particles/mL. The advantages of the proposed detection method include the following; first, the detection substrate is easy to prepare and convenient to clean. Second, the TFC strategy can completely exclude nonspecific reaction sites and thus significantly improves the accuracy. Such a facile and reliable detection method holds a great potential in exosome-based cancer theranostics. In this paper, we proposed a triple-color fluorescence co-localization (TFC) strategy to significantly improve the reliability of exosome detection and the detection substrate is easy to prepare and convenient to clean. In addition, the LOD is down to 6 particles/mL, which is quite low compared with other detection methods.

Overexpression of MdZAT5, an C2H2-Type Zinc Finger Protein, Regulates Anthocyanin Accumulation and Salt Stress Response in Apple Calli and Arabidopsis.

Zinc finger proteins are widely involved and play an important role in plant growth and abiotic stress. In this research, MdZAT5, a gene encoding C2H2-type zinc finger protein, was cloned and investigated. The MdZAT5 was highly expressed in flower tissues by qRT-PCR analyses and GUS staining. Promoter analysis showed that MdZAT5 contained multiple response elements, and the expression levels of MdZAT5 were induced by various abiotic stress treatments. Overexpression of MdZAT5 in apple calli positively regulated anthocyanin accumulation by activating the expressions of anthocyanin biosynthesis-related genes. Overexpression of MdZAT5 in Arabidopsis also enhanced the accumulation of anthocyanin. In addition, MdZAT5 increased the sensitivity to salt stress in apple calli. Ectopic expression of MdZAT5 in Arabidopsis reduced the expression of salt-stress-related genes (AtNHX1 and AtABI1) and improved the sensitivity to salt stress. In conclusion, these results suggest that MdZAT5 plays a positive regulatory role in anthocyanin accumulation and negatively regulates salt resistance.

Biocompatibility and Biological Performance of Additive-Manufactured Bioabsorbable Iron-Based Porous Interference Screws in a Rabbit Model: A 1-Year Observational Study.

This study evaluated the mid-term (12-month) biomechanical, biocompatibility, and biological performance of additive-manufactured bioabsorbable iron-based interference screws (ISs). Two bioabsorbable iron IS types-manufactured using pure iron powder (iron_IS) and using pure iron powder with 0.2 wt% tricalcium phosphate (TCP_IS)-were compared with conventional metallic IS (control) using in vitro biocompatibility and degradation analyses and an in vivo animal study. The in vitro ultimate failure strength was significantly higher for iron_IS and TCP_IS than for control ISs at 3 months post-operatively; however, the difference between groups were nonsignificant thereafter. Moreover, at 3 months after implantation, iron_IS and TCP_IS increased bone volume fraction, bone surface area fraction, and percent intersection surface; the changes thereafter were nonsignificant. Iron_IS and TCP_IS demonstrated degradation over time with increased implant surface, decreased implant volume, and structure thickness; nevertheless, the analyses of visceral organs and biochemistry demonstrated normal results, except for time-dependent iron deposition in the spleen. Therefore, compared with conventional ISs, bioabsorbable iron-based ISs exhibit higher initial mechanical strength. Although iron-based ISs demonstrate high biocompatibility 12 months after implantation, their corrosive iron products may accumulate in the spleen. Because they demonstrate mechanical superiority along with considerable absorption capability after implantation, iron-based ISs may have potential applications in implantable medical-device development in the future.

Quantitative proteomics identifies FOLR1 to drive sorafenib resistance via activating autophagy in hepatocellular carcinoma cells.

Sorafenib is commonly used to treat advanced human hepatocellular carcinoma (HCC). However, clinical efficacy has been limited by drug resistance. In this study, we used label-free quantitative proteomic analysis to systematically investigate the underlying mechanisms of sorafenib resistance in HCC cells. A total of 1709 proteins were confidently quantified. Among them, 89 were differentially expressed and highly enriched in the processes of cell-cell adhesion, negative regulation of apoptosis, response to drug and metabolic processes involving in sorafenib resistance. Notably, folate receptor α (FOLR1) was found to be significantly upregulated in resistant HCC cells. In addition, in vitro studies showed that overexpression of FOLR1 decreased the sensitivity of HCC cells to sorafenib, whereas siRNA-directed knockdown of FOLR1 increased the sensitivity of HCC cells to sorafenib. Immunoprecipitation-mass spectrometry analysis suggested a strong link between FOLR1 and autophagy-related proteins. Further biological experiments found that FOLR1-related sorafenib resistance was accompanied by the activation of autophagy, whereas inhibition of autophagy significantly reduced FOLR1-induced cell resistance. These results suggest the driving role of FOLR1 in HCC resistance to sorafenib, which may be exerted through FOLR1-induced autophagy. Therefore, this study may provide new insights into understanding the mechanism of sorafenib resistance.