Long noncoding RNAs HAND2-AS1 ultrasound microbubbles suppress hepatocellular carcinoma progression by regulating the miR-873-5p/tissue inhibitor of matrix metalloproteinase-2 axis.

BACKGROUND: Increasing data indicated that long noncoding RNAs (lncRNAs) were directly or indirectly involved in the occurrence and development of tumors, including hepatocellular carcinoma (HCC). Recent studies had found that the expression of lncRNA HAND2-AS1 was downregulated in HCC tissues, but its role in HCC progression is unclear. Ultrasound targeted microbubble destruction mediated gene transfection is a new method to overexpress genes. AIM: To study the role of ultrasound microbubbles (UTMBs) mediated HAND2-AS1 in the progression of HCC, in order to provide a new reference for the treatment of HCC. METHODS: In vitro, we transfected HAND2-AS1 siRNA into HepG2 cells by UTMBs, and detected cell proliferation, apoptosis, invasion and epithelial-mesenchymal transition (EMT) by cell counting kit-8 assay, flow cytometry, Transwell invasion assay and Western blotting, respectively. In addition, we transfected miR-837-5p mimic into UTMBs treated cells and observed the changes of cell behavior. Next, the UTMBs treated HepG2 cells were transfected together with miR-837-5p mimic and tissue inhibitor of matrix metalloproteinase-2 (TIMP2) overexpression vector, and we detected cell proliferation, apoptosis, invasion and EMT. In vivo, we established a mouse model of subcutaneous transplantation of HepG2 cells and observed the effect of HAND2-AS1 silencing on tumor formation ability. RESULTS: We found that UTMBs carrying HAND2-AS1 restricted cell proliferation, invasion, and EMT, encouraged apoptosis, and HAND2-AS1 silencing eliminated the effect of UTMBs. Additionally, miR-873-5p targets the gene HAND2-AS1, which also targets the 3'UTR of TIMP2. And miR-873-5p mimic counteracted the impact of HAND2-AS1. Further, miR-873-5p mimic solely or in combination with pcDNA-TIMP2 had been transformed into HepG2 cells exposed to UTMBs. We discovered that TIMP2 reversed the effect of miR-873-5p mimic caused by the blocked signalling cascade for matrix metalloproteinase (MMP) 2/MMP9. In vivo results showed that HAND2-AS1 silencing significantly inhibited tumor formation in mice. CONCLUSION: LncRNA HAND2-AS1 promotes TIMP2 expression by targeting miR-873-5p to inhibit HepG2 cell growth and delay HCC progression.

CD206 modulates the role of M2 macrophages in the origin of metastatic tumors.

Tumor metastasis is a key factor affecting the life of patients with malignant tumors. For the past hundred years, scientists have focused on how to kill cancer cells and inhibit their metastasis in vivo, but few breakthroughs have been made. Here we hypothesized a novel mode for cancer metastasis. We show that the phagocytosis of apoptotic tumor cells by macrophages leads to their polarization into the M2 phenotype, and that the expression of stem cell related as well as drug resistance related genes was induced. Therefore, it appears that M2 macrophages have "defected" and have been transformed into the initial "metastatic cancer cells", and thus are the source, at least in part, of the distal tissue tumor metastasis. This assumption is supported by the presence of fused cells with characteristics of both macrophage and tumor cell observed in the peripheral blood and ascites of patients with ovarian cancer. By eliminating the expression of CD206 in M2 macrophages using siRNA, we show that the growth and metastasis of tumors was suppressed using both in vitro cell line and with experimental in vivo mouse models. In summary, we show that M2 macrophages in the blood circulation underwent a "change of loyalty" to become "cancer cells" that transformed into distal tissue metastasis, which could be suppressed by the knockdown of CD206 expression.

Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images.

Knowledge of protein expression in mammalian brains at regional and cellular levels can facilitate understanding of protein functions and associated diseases. As the mouse brain is a typical mammalian brain considering cell type and structure, several studies have been conducted to analyze protein expression in mouse brains. However, labeling protein expression using biotechnology is costly and time-consuming. Therefore, automated models that can accurately recognize protein expression are needed. Here, we constructed machine learning models to automatically annotate the protein expression intensity and cellular location in different mouse brain regions from immunofluorescence images. The brain regions and sub-regions were segmented through learning image features using an autoencoder and then performing K-means clustering and registration to align with the anatomical references. The protein expression intensities for those segmented structures were computed on the basis of the statistics of the image pixels, and patch-based weakly supervised methods and multi-instance learning were used to classify the cellular locations. Results demonstrated that the models achieved high accuracy in the expression intensity estimation, and the F1 score of the cellular location prediction was 74.5%. This work established an automated pipeline for analyzing mouse brain images and provided a foundation for further study of protein expression and functions.

Long head of biceps tendon transposition for massive and irreparable rotator cuff tears: A systematic review and meta-analysis.

BACKGROUND: Superior capsular reconstruction (SCR) with long head of biceps tendon (LHBT) transposition was developed to massive and irreparable rotator cuff tears (MIRCTs); however, the outcomes of this technique remain unclear. AIM: To perform a systematic review of biomechanical outcomes and a meta-analysis of clinical outcomes after LHBT transposition for MIRCTs. METHODS: We performed a systematic electronic database search on PubMed, EMBASE, and Cochrane Library. Studies of SCR with LHBT transposition were included according to the inclusion and exclusion criteria. Biomechanical studies were assessed for main results and conclusions. Included clinical studies were evaluated for quality of methodology. Data including study characteristics, cohort demographics, and outcomes were extracted. A meta-analysis was conducted of the clinical outcomes. RESULTS: According to our inclusion and exclusion criteria, a total of six biomechanical studies were identified and reported an overall improvement in subacromial contact pressures and prevention of superior humeral migration without limiting range of motion (ROM) after LHBT transposition for MIRCTs. A total of five clinical studies were included in the meta-analysis of LHBT transposition outcomes, consisting of 253 patients. The results indicated that compared to other surgical methods for MIRCTs, LHBT transposition had advantages of more significant improvement in ROM (forward flexion mean difference [MD] = 6.54, 95% confidence interval [CI]: 3.07-10.01; external rotation [MD = 5.15, 95%CI: 1.59-8.17]; the acromiohumeral distance [AHD] [MD = 0.90, 95%CI: 0.21-1.59]) and reducing retear rate (odds ratio = 0.27, 95%CI: 0.15-0.48). No significant difference in American Shoulder and Elbow Surgeons score, visual analogue scale score, and University of California at Los Angles score was demonstrated between these two groups for MIRCTs. CONCLUSION: In general, SCR with LHBT transposition was a reliable and economical technique for treating MIRCTs, both in terms of biomechanical and clinical outcomes, with comparable clinical outcomes, improved ROM, AHD, and reduced the retear rates compared to conventional SCR and other established techniques. More high-quality randomized controlled studies on the long-term outcomes of SCR with LHBT transposition are required to further assess.

Synergistic effects of electroactive antibacterial material and electrical stimulation in enhancing skin tissue regeneration: A next-generation dermal wound dressing.

OBJECTIVE: We aimed to develop an electroactive antibacterial material for the treatment of skin wound diseases. METHOD: To this aim, we modified chitosan (CS), a biocompatible polymer, by coupling it with graphene (rGO) and an antimicrobial polypeptide DOPA-PonG1. The material's effect on skin injury healing was studied in combination with external electrical stimulation (EEM). The structure, surface composition, and hydrophilicity of the modified CS materials were evaluated using scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and contact angle measurements. We studied NIH3T3 cells cultured with modified materials and subjected to EEM to assess viability, adhesion, and tissue repair-related gene expression. RESULTS: SEM data demonstrated that rGO was distributed uniformly on the surface of the CS material, increasing surface roughness, and antimicrobial peptides had minimal impact on surface morphology. FTIR confirmed the uniform distribution of rGO and antibacterial peptides on the material surface. Both rGO and DOPA-PonG1 enhanced the hydrophilicity of CS materials, with rGO also improving tensile strength. The dual modification of CS with rGO and DOPA-PonG1 synergistically increased antibacterial efficacy. Cellular events and gene expression relevant to tissue repair process were enhanced by these modifications. Furthermore, EEM accelerated epidermal regeneration more than the material alone. In a rat skin wound model, DOPA-PonG1@CS/rGO dressing combined with electrical stimulation exhibited accelerated healing of skin defect. CONCLUSION: Overall, our results demonstrate that CS materials modified with rGO and DOPA-PonG1 have increased hydrophilicity, antibacterial characteristics, and tissue regeneration capacities. This modified material in conjunction with EEM hold promise for the clinical management for dermal wounds.

Suppression of SAMSN1 contributes to neuroprotection in neonatal rats suffering from hypoxic-ischemic encephalopathy injury.

This article aims to detect the effect of SAM domain, SH3 domain, and nuclear localization signal 1 (SAMSN1) in neonatal rats with neurological dysfunction induced by hypoxia and ischemia (HI). The HI model was created using 7-day postnatal rats. Zea-longa score was utilized to validate the neurological injury after HI. Then, the differentially expressed genes (DEGs) were detected by gene sequencing and bioinformatics analysis methods. The oxygen and glucose deprivation (OGD) models were established in the SY5Y cells and fetal human cortical neurons. In addition, SAMSN1-small interfering RNA, methyl thiazolyl tetrazolium assay, and cell growth curve were employed to evaluate the cell viability variation. Obviously, Zea-longa scores increased in rats with HI insult. Subsequently, SAMSN1 was screened out, and it was found that SAMSN1 was strikingly upregulated in SY5Y cells and fetal neurons post-OGD. Interestingly, we found that SAMSN1 silencing could markedly enhance cell viability and cell growth after OGD. These data suggested that downregulation of SAMSN1 may exert a neuroprotective effect on damaged neurons after HI by improving cell viability and cell survival, which provides a potential theoretical basis for clinical trials in the future to treat neonatal hypoxic-ischemic encephalopathy.

[In vitro study on cytotoxicity, osteogenic potential and antibacterial activity of silicate root canal sealers].

PURPOSE: To evaluate the in vitro biocompatibility and antibacterial activity of a new type of strontium silicate-based C-Root SP root canal sealer, and to provide a reference for clinical selection of sealers. METHODS: C-Root SP, iRoot SP and AH Plus extracts were prepared, L929 cells and MC3T3-E1 cells were cultured in vitro, and the cytotoxicity and osteogenic potential of the three sealers were compared. Fresh sealers were mixed with Enterococcus faecalis solution and the antibacterial activity of the sealer was determined by direct contact text (DCT). SPSS 25.0 software package was used for statistical analysis. RESULTS: At 24, 48, and 72 h, the cytotoxicity of the sealers in each group were significantly different (P＜0.01). Compared with AH Plus, the cytotoxicity of C-Root SP was lower (P＜0.01). C-Root SP was superior to AH Plus in promoting the activity of alkaline phosphatase(ALP) (P＜0.01). iRoot SP was the strongest in promoting the formation of mineralized nodules, followed by C-Root SP, and the weakest was AH Plus(P＜0.01). C-Root SP inhibited the growth of Enterococcus faecalis, and its antibacterial rate was significantly higher than AH Plus(P＜0.01). CONCLUSIONS: The strontium silicate root canal sealer C-Root SP has low cytotoxicity, certain osteogenic potential and antibacterial activity against Enterococcus faecalis, so it can be used for root canal filling.

4D-DIA quantitative proteomics revealed the core mechanism of diabetic retinopathy after berberine treatment.

OBJECTIVE: To reveal the core mechanism of berberine (BBR) in the treatment of diabetic retinopathy (DR), by using Four-dimensional independent data acquisition (4D-DIA) proteomics combined bioinformatics analysis with experimental validation. METHODS: DR injury model was established by injecting streptozotocin intraperitoneally. At 8 weeks after BBR administration, optical coherence tomography (OTC) photos and Hematoxylin-eosin staining from retina in each group were performed, then the retina was collected for 4D-DIA quantitative proteomics detection. Moreover, difference protein analysis, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI) network, as well as molecular docking was performed, respectively. In the part of experiment, Western blot (WB) and immunofluorescent staining was used to confirm the change and distribution of carbonic anhydrase 1 (CA1), one of the most important molecules from quantitative PCR detection. Lastly, RNA knockdown was used to determine the crucial role of CA1 in retinal pigment epithelial cells (RPEs) administrated with berberine. RESULTS: OCT detection showed that the outer nucleus, inner layer and outer accessory layer of RPEs were thinned in DR group, compared with in sham one, while they were thickened after berberine administration, when compared with in DR group. 10 proteins were screened out by using proteomic analysis and Venny cross plot, in which, denn domain containing 1A (DENND1A) and UTP6 small subunit processome component (UTP6) was down-regulated, while ATPase copper transporting alpha (ATP7A), periplakin (PPL), osteoglycin (OGN), nse1 Homolog (NSMCE1), membrane metalloendopeptidase (MME), lim domain only 4 (LMO4), CA1 and fibronectin 1 (FN1) was up-regulated in DR group, and the BBR treatment can effectively reverse their expressions. PPI results showed that 10 proteins shared interactions with each other, but only ATP7A, FN1 and OGN exhibited directly associated with each other. Moreover, we enlarged the linked relation up to 15 genes in network, based on 10 proteins found from proteomics detection, so as to perform deep GO and KEGG analysis. As a result, the most important biological process is involving rRNA processing; the most important cell component is small subunit processor; the most important molecular function is Phospholipid binding; the KEGG pathway was Ribosome biogenesis in eukaryotes. Moreover, molecular docking showed that LMO4, ATP7A, PPL, NSMCE1, MME, CA1 could form a stable molecular binding pattern with BBR. Of these, the mRNA expression of CA1, PPL and ATP7A and the protein level of CA1 was increased in DR, and decreased in BBR group. Lastly, CA1 RNA knockdown confirmed the crucial role of CA1 in RPE administered with BBR. CONCLUSION: The present findings confirmed the role of BBR in DR treatment and explained associated molecular network mechanism, in which, CA1 could be considered as a crucial candidate in the protection of RPEs with berberine treatment.

A practical preparation of bicyclic boronates via metal-free heteroatom-directed alkenyl sp2-C‒H borylation.

Bicyclic boronates play critical roles in the discovery of functional materials and antibacterial agents, especially against deadly bacterial pathogens. Their practical and convenient preparation is in high demand but with great challenge. Herein, we report an efficient strategy for the preparation of bicyclic boronates through metal-free heteroatom-directed alkenyl sp2-C‒H borylation. This synthetic approach exhibits good functional group compatibility, and the corresponding boronates bearing halides, aryls, acyclic and cyclic frameworks are obtained with high yields (43 examples, up to 95% yield). Furthermore, a gram-scale experiment is conducted, and downstream transformations of the bicyclic boronates are pursued to afford natural products, drug scaffolds, and chiral hemiboronic acid catalysts.

[Assessing the Environmental and Health Co-benefits of Accelerated Energy Transition and Industrial Restructuring: A Case Study of the BTHS Region].

The Beijing-Tianjin-Hebei-Shandong Region (BTHS Region) is a crucial area for China to achieve synergy between pollution reduction and carbon emissions reduction. The demand for coordinated emissions reduction through source control measures such as energy transition and industrial restructuring are becoming increasingly necessary owing to the limited emissions reductions potential of end-of-pipe control measures. An assessment of the emissions reductions potential through strengthening the end-of-pipe control in the BTHS Region, as well as the environmental and health co-benefits from accelerated energy transition and industrial restructuring, was conducted using scenario simulation analysis based on the REACH model. The results showed that the rapid implementation of the best available end-of-pipe control technologies in the BTHS Region would result in 3.3 µg·m-3 reduction in PM2.5 concentration in 2035, but this would not be sufficient to achieve the PM2.5 concentration control targets. Accelerating the energy transition and the industrial restructuring are necessary for the BTHS Region to achieve air quality standards, which would reduce the PM2.5 concentrations by 6.3 µg·m-3 in 2035. The environmental and health co-benefits brought by the accelerated transition could partially or entirely offset the additional socio-economic cost (compared to that of the current policy efforts) of approximately 0.9%-2.5% of the total regional GDP in achieving the PM2.5 concentration control target paid by the four provinces.

Evaluating emission reduction potential at the "30-60 Dual Carbon targets" over China from a view of wind power under climate change.

Large-scale wind energy development is one of the main paths to achieving China's carbon peak and neutrality goals. How will the wind power and corresponding carbon abatement potential (CAP) in China change when China reaches the timing of its reduction carbon targets? This issue has not been well addressed. In this paper, a weighted multi-model ensemble with 14 global climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) is used to evaluate the spatio-temporal characteristics of wind speed over China during the baseline period (2004-2014). Then, we further analyze the changes in wind power and corresponding CAP due to the climate change over China in the two-level years (2030 and 2060) under the SSP2-4.5 and SSP5-8.5 scenarios. The results show that the wind capacity factor over China will have a trend of decreasing in most regions of China and increasing in the southeast in 2060. Overall, climate change will have a slight impact on the CAP of wind power in 2030, with an increase in some southern provinces. However, the CAP of wind power will decrease significantly in most regions of China in 2060 under the SSP2-4.5 scenario, especially in Shanxi, Inner Mongolia, Ningxia, and Liaoning, by more than 5 %. Under the SSP5-8.5 scenario, the CAP will decrease significantly in the southwest and northwest regions, such as Sichuan and Qinghai, by 9.86 % and 8.19 % respectively. Central and South provinces such as Hunan and Hubei will increase by about 5 %. In terms of seasonal changes, the CAP of wind power will decrease significantly in summer under the SSP2-4.5 scenario (about -5.24 %) and SSP5-8.5 scenario (about -6.50 %).These findings can help policymakers make decisions as they establish plans for wind power expansion while taking the effects of climate change into account as they work toward China's carbon neutrality goal.

Compact conformal tattoo-polymer antenna for on-body wireless power transfer.

This paper presents a 35.0 × 35.0 × 2.7 mm3 compact, low-profile, and lightweight wearable antenna for on-body wireless power transfer. The proposed antenna can be easily printed on a piece of flexible tattoo paper and transformed onto a PDMS substrate, making the entire antenna structure conform to the human body for achieving a better user experience. Here, a layer of frequency selective surface (FSS) is inserted in between the antenna and human tissue, which has successfully reduced the loading effects of the tissue, with 13.8 dB improvement on the antenna gain. Also, the operating frequency of the rectenna is not affected much by deformation. To maximize the RF-DC conversion efficiency, a matching loop, a matching stub, and two coupled lines are integrated with the antenna for tuning the rectenna so that a wide bandwidth (~ 24%) can be achieved without the use of any external matching networks. Measurement results show that the proposed rectenna can achieve a maximum conversion efficiency of 59.0% with an input power of 5.75 µW/cm2 and can even exceed 40% for a low input power of 1.0 µW/cm2 with a 20 kΩ resistive load, while many other reported rectennas can only achieve a high PCE at a high power density level, which is not always practical for a wearable antenna.

Rapid screening of sensory attributes of mackerel using big data mining techniques and rapid sensory evaluation methods.

The present study aimed to investigate the potential of big data mining technology in conjunction with rapid sensory evaluation methods for the swift screening of sensory attributes of three kinds of frozen mackerel. Specifically, two rapid sensory evaluation methods, namely ideal profile method (IPM) and check-all-that-apply (CATA), were implemented and compared with the conventional descriptive analysis method. The results revealed that eight sensory attributes based on consumer network evaluations demonstrated significant consistency during the training process (p < .05). Notably, the application of web-based sensory attributes yielded highly comparable results between IPM and traditional descriptive analysis (0.915). Moreover, the results of the IPM preference map were in closer agreement with those of traditional descriptive analysis. While traditional sensory evaluation boasts high accuracy and a greater ability to detect nuances, the evolution of sensory evaluation technology has shifted its focus toward consumers. Rapid sensory evaluation analysis technology supports the collection of information directly from consumers, even by untrained or semi-trained groups, thereby presenting broad prospects for product qualitative analysis.

Prediction of Multimorbidity in Brazil: Latest Fifth of a Century Population Study.

BACKGROUND: Multimorbidity is characterized by the co-occurrence of 2 or more chronic diseases and has been a focus of the health care sector and health policy makers due to its severe adverse effects. OBJECTIVE: This paper aims to use the latest 2 decades of national health data in Brazil to analyze the effects of demographic factors and predict the impact of various risk factors on multimorbidity. METHODS: Data analysis methods include descriptive analysis, logistic regression, and nomogram prediction. The study makes use of a set of national cross-sectional data with a sample size of 877,032. The study used data from 1998, 2003, and 2008 from the Brazilian National Household Sample Survey, and from 2013 and 2019 from the Brazilian National Health Survey. We developed a logistic regression model to assess the influence of risk factors on multimorbidity and predict the influence of the key risk factors in the future, based on the prevalence of multimorbidity in Brazil. RESULTS: Overall, females were 1.7 times more likely to experience multimorbidity than males (odds ratio [OR] 1.72, 95% CI 1.69-1.74). The prevalence of multimorbidity among unemployed individuals was 1.5 times that of employed individuals (OR 1.51, 95% CI 1.49-1.53). Multimorbidity prevalence increased significantly with age. People over 60 years of age were about 20 times more likely to have multiple chronic diseases than those between 18 and 29 years of age (OR 19.6, 95% CI 19.15-20.07). The prevalence of multimorbidity in illiterate individuals was 1.2 times that in literate ones (OR 1.26, 95% CI 1.24-1.28). The subjective well-being of seniors without multimorbidity was 15 times that among people with multimorbidity (OR 15.29, 95% CI 14.97-15.63). Adults with multimorbidity were more than 1.5 times more likely to be hospitalized than those without (OR 1.53, 95% CI 1.50-1.56) and 1.9 times more likely need medical care (OR 1.94, 95% CI 1.91-1.97). These patterns were similar in all 5 cohort studies and remained stable for over 21 years. A nomogram model was used to predict multimorbidity prevalence under the influence of various risk factors. The prediction results were consistent with the effects of logistic regression; older age and poorer participant well-being had the strongest correlation with multimorbidity. CONCLUSIONS: Our study shows that multimorbidity prevalence varied little in the past 2 decades but varies widely across social groups. Identifying populations with higher rates of multimorbidity prevalence may improve policy making around multimorbidity prevention and management. The Brazilian government can create public health policies targeting these groups, and provide more medical treatment and health services to support and protect the multimorbidity population.

Nature-inspired catalytic asymmetric rearrangement of cyclopropylcarbinyl cation.

In nature, cyclopropylcarbinyl cation is often involved in cationic cascade reactions catalyzed by natural enzymes to produce a great number of structurally diverse natural substances. However, mimicking this natural process with artificial organic catalysts remains a daunting challenge in synthetic chemistry. We report a small molecule-catalyzed asymmetric rearrangement of cyclopropylcarbinyl cations, leading to a series of chiral homoallylic sulfide products with good to excellent yields and enantioselectivities (up to 99% enantiomeric excess). In the presence of a chiral SPINOL-derived N-triflyl phosphoramide catalyst, the dehydration of prochiral cyclopropylcarbinols occurs rapidly to generate symmetrical cyclopropylcarbinyl cations, which are subsequently trapped by thione-containing nucleophiles. A subgram-scale experiment and multiple downstream transformations of the sulfide products are further pursued to demonstrate the synthetic utility. Notably, a few heteroaromatic sulfone derivatives could serve as "covalent warhead" in the enzymatic inhibition of severe acute respiratory syndrome coronavirus 2 main protease.

Network pharmacology mechanism of Scutellarin to inhibit RGC pyroptosis in diabetic retinopathy.

To investigate the effect of scutellarin (SCU) in diabetic retinopathy (DR) and explore the associated molecular network mechanism. The animal model of DR was established from diabetic mellitus (DM) rats by intraperitoneally injected streptozotocin (STZ) at dosage 55 mg/kg. Meanwhile, SCU was intraperitoneally administrated to protect retina from cell pyroptosis induced by DM, and cell pyroptosis was detected by using HE, Nissl staining, and immunofluorescence recognition. Moreover, the hub gene involving in pyroptosis in DR was screened by bioinformatics and network pharmacology, designated as Venny intersection screen, GO and KEGG analysis, PPI protein interaction, and molecular docking. Lastly, the expressional change of hub genes were validated with experimental detection. Cell pyroptosis of the DR, specifically in retina ganglion cells (RGC), was induced in DM rats; SCU administration results in significant inhibition in the cell pyroptosis in DR. Mechanically, 4084 genes related to DR were screened from GeneCards and OMIM databases, and 120 SCU therapeutic targets were obtained, by using GeneCards, TCMSP with Swiss Target Prediction databases. Moreover, 357 targets related to pyroptosis were found using GenenCards database, and Drug, disease and phenotypic targets were analyzed online using the Draw Venn Diagram website, and 12 cross targets were obtained. Through GO function and KEGG pathway enrichment analysis, 659 BP related items, 7 CC related items, 30 MF related items, and 70 signal pathways were screened out; Of these, eleven proteins screened from cross-target PPI network were subsequently docked with the SCU, and their expressions including caspase-1, IL-1ß, IL-18, GSDMD and NLRP3 in RGC indicated by immunofluorescence, and the mRNA expression for caspase-1 in DR indicated by quantitative PCR, were successfully validated. SCU can effectively protect RGC pyroptosis in DR, and underlying mechanisms are involved in the inhibition of caspase-1, GSDMD, NLRP3, IL-1ß and IL-18. Our findings therefore provide crucial evidence to support the clinic practice of SCU for the treatment of DR, and explained the underlying molecular network mechanism.

High-Efficiency 3D DNA Walker Immobilized by a DNA Tetrahedral Nanostructure for Fast and Ultrasensitive Electrochemical Detection of MiRNA.

Herein, by directly limiting the reaction space, an ingenious three-dimensional (3D) DNA walker (IDW) with high walking efficiency is developed for rapid and sensitive detection of miRNA. Compared with the traditional DNA walker, the IDW immobilized by the DNA tetrahedral nanostructure (DTN) brings stronger kinetic and thermodynamic favorability resulting from its improved local concentration and space confinement effect, accompanied by a quite faster reaction speed and much better walking efficiency. Once traces of target miRNA-21 react with the prelocked IDW, the IDW could be largely activated and walk on the interface of the electrode to trigger the cleavage of H2 with the assistance of Mg2+, resulting in the release of amounts of methylene blue (MB) labeled on H2 from the electrode surface and the obvious decrease of the electrode signal. Impressively, the IDW reveals a conversion efficiency as high as 9.33 × 108 in 30 min with a much fast reaction speed, which is at least five times beyond that of typical DNA walkers. Therefore, the IDW could address the inherent challenges of the traditional DNA walker easily: slow walking speed and low efficiency. Notably, the IDW as a DNA nanomachine was utilized to construct a sensitive sensing platform for rapid miRNA-21 detection with a limit of detection (LOD) of 19.8 aM and realize the highly sensitive assay of biomarker miRNA-21 in the total RNA lysates of cancer cell. The strategy thus helps in the design of a versatile nucleic acid conversion and signal amplification approach for practical applications in the areas of biosensing assay, DNA nanotechnology, and clinical diagnosis.

Automatic recognition of protein subcellular location patterns in single cells from immunofluorescence images based on deep learning.

With the improvement of single-cell measurement techniques, there is a growing awareness that individual differences exist among cells, and protein expression distribution can vary across cells in the same tissue or cell line. Pinpointing the protein subcellular locations in single cells is crucial for mapping functional specificity of proteins and studying related diseases. Currently, research about single-cell protein location is still in its infancy, and most studies and databases do not annotate proteins at the cell level. For example, in the human protein atlas database, an immunofluorescence image stained for a particular protein shows multiple cells, but the subcellular location annotation is for the whole image, ignoring intercellular difference. In this study, we used large-scale immunofluorescence images and image-level subcellular locations to develop a deep-learning-based pipeline that could accurately recognize protein localizations in single cells. The pipeline consisted of two deep learning models, i.e. an image-based model and a cell-based model. The former used a multi-instance learning framework to comprehensively model protein distribution in multiple cells in each image, and could give both image-level and cell-level predictions. The latter firstly used clustering and heuristics algorithms to assign pseudo-labels of subcellular locations to the segmented cell images, and then used the pseudo-labels to train a classification model. Finally, the image-based model was fused with the cell-based model at the decision level to obtain the final ensemble model for single-cell prediction. Our experimental results showed that the ensemble model could achieve higher accuracy and robustness on independent test sets than state-of-the-art methods.