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Background: Exercise is one of the most effective interventions for preventing and treating skeletal muscle aging. Exercise-induced autophagy is widely acknowledged to regulate skeletal muscle mass and delay skeletal muscle aging. However, the mechanisms underlying of the effect of different exercises on autophagy in aging skeletal muscle remain unclear.Methods: A systematic review was performed following an electronic search of SCOPUS, PubMed, Web of Science, ScienceDirect, and Google Scholar and two Chinese electronic databases, CNKI and Wan Fang. All articles published in English and Chinese between January 2010 and January 2022 that quantified autophagy-related proteins in aging skeletal muscle models.Results: The primary outcome was autophagy assessment, indicated by changes in the levels of any autophagy-associated proteins. A total of fifteen studies were included in the final review. Chronic exercise modes mainly comprise aerobic exercise and resistance exercise, and the intervention types include treadmill training, voluntary wheel running, and ladder training. LC3, Atg5-Atg7/9/12, mTOR, Beclin1, Bcl-2, p62, PGC-1α, and other protein levels were quantified, and the results showed that long-term aerobic exercise and resistance exercise could increase the expression of autophagy-related proteins in aging skeletal muscle (p < 0.05). However, there was no significant difference in short term or high-intensity chronic exercise, and different types and intensities of exercise yielded different levels of significance for autophagy-related protein expression.Conclusion: Existing evidence reveals that high-intensity exercise may induce excessive autophagy, while low-intensity exercise for a short period (Intervention duration

HBV infection is recognized as a serious global health problem, and hepatitis B virus infection is a complicated chronic disease leading to liver cirrhosis (LC) and hepatocellular carcinoma (HCC). New biochemical serum markers could be used to advance the diagnosis and prognosis of HBV-associated liver diseases during the progression of chronic hepatitis B into cirrhosis and HCC. We determined whether the 4210 Da and 1866 Da polypeptides are serum metabolite biomarkers of hepatopathy with hepatitis B virus. A total of 570 subjects were divided into five groups: healthy controls, those with natural clearance, and patients with CHB, LC, and HCC. The 1866 Da and 4210 Da polypeptides were measured by Clin-ToF II MALDI-TOF–MS. There were significant differences in 4210 Da and 1866 Da levels among the five groups (P P P

Additional file 9: Figure S8. Survival curve analysis for mutated TTN or OBSCN in different pathologic stages of HCC. Survival curve analyses for the mutation of a-d TTN, e-h OBSCN in the overall HCC, stage I, II, III-IV of HCC, were performed by a “survminer” R package, respectively.

Additional file 14: Figure S13. Expression level of SNRPD2 in five GEO datasets. From the GEO database, we obtained five independent datasets, including a GSE102079 (n = 91), b GSE76427 (n = 52), c GSE64041 (n = 60), d GSE121248 (n = 37), e GSE84005 (n = 38), to analyze the expression difference of SNRPD2 between HCC and adjacent non-tumor tissues. Each vertical line represents one patient with HCC.

Additional file 4: Figure S3. Expression and relative survival curve analyses for some targeting genes. a We analyzed the expression levels of PIANP, DUOX2, CUZD1, CRTAC1, IQCA1, IL11, NPHS1, PCSK1, CPA1, HOXB9, KCNH2 and NPTX1 genes in a normal and overall HCC, and b different pathologic stages by GEPIA2. c We also performed the Kaplan-Meier estimates of OS or DFS, according to the expression level.

Additional file 5: Figure S4. Comparison between CNV and expression level of genes within cell cycle pathway. We performed a Kolmogorov-Smirnov test for correlation analysis to identify the expression-correlated targeting genes with CNV, and then utilized the “enrichKEGG” function for the KEGG pathway enrichment analysis. The cell cycle pathway data was provided. a -1og (P value) for CNV; b gene expression for FC (fold change).

Additional file 4: Figure S3. Expression and relative survival curve analyses for some targeting genes. a We analyzed the expression levels of PIANP, DUOX2, CUZD1, CRTAC1, IQCA1, IL11, NPHS1, PCSK1, CPA1, HOXB9, KCNH2 and NPTX1 genes in a normal and overall HCC, and b different pathologic stages by GEPIA2. c We also performed the Kaplan-Meier estimates of OS or DFS, according to the expression level.

Additional file 1: Table S1. Clinical characteristics of HCC cases in HLivH060PG02 cohort.

Additional file 5: Figure S4. Comparison between CNV and expression level of genes within cell cycle pathway. We performed a Kolmogorov-Smirnov test for correlation analysis to identify the expression-correlated targeting genes with CNV, and then utilized the “enrichKEGG” function for the KEGG pathway enrichment analysis. The cell cycle pathway data was provided. a -1og (P value) for CNV; b gene expression for FC (fold change).

Additional file 8: Figure S7. Survival curve analysis for mutated CTNNB1 or TP53 in different pathologic stages of HCC. The “survminer” R package was used to perform the survival curve analysis for the mutation of a-d CTNNB1, e-h TP53 in the overall HCC, stage I, II, III-IV of HCC, respectively.

Additional file 3: Figure S2. Genetic difference analysis for different pathologic stages of HCC. a Volcano plots of Tumor vs. Normal, stage II vs. stage I, stage III + IV vs. stage II. b Intersection analysis of the above comparisons. c Protein-protein interaction network analysis of intersected genes. d A heat map of cluster analysis. e Full name information of the intersected genes.

Additional file 16: Figure S15. Expression level of SEMA3F in five GEO datasets. From the GEO database, we obtained five independent datasets, including a GSE102079 (n = 91), b GSE76427 (n = 52), c GSE64041 (n = 60), d GSE121248 (n = 37), e GSE84005 (n = 38), to analyze the expression difference of SEMA3F between HCC and adjacent non-tumor tissues. Each vertical line represents one patient with HCC.

Additional file 6: Figure S5. Waterfall plot and analysis regarding the relationship between gene expression and mutation status of top 15 mutated genes. a Top 15 genes of mutation frequency, such as TTN, TP53, CTNNB1, MUC16, and ALB, were selected for the waterfall plot with clinical grading information. b Correlation between gene expression and mutation in normal and different pathologic stages of HCC was analyzed.

Additional file 2: Figure S1. Correlation between clinical or distribution characteristics and different pathologic stages of HCC. We performed the Kruskal-Wallis tests to analyze the relationship between pathologic stage I, II, III-IV, and a total bilirubin, b albumin, c fetoprotein, d creatine, e protherombin time, f platelet count, g age, h height and i weight, respectively. We also performed the chi-square tests to analyze the association between the factors of the j race, k ethnicity, l gender, and pathologic stage I, II, III-IV. * P

Additional file 11: Figure S10. Survival curve analysis for CTNNB1 and TP53 SNPs in different pathologic stages of HCC. The “survminer” R package was used to perform the survival curve analysis for a CTNNB1 rs121913396, b rs121913400, c rs121913407, and d TP53 rs28934571 SNP in the different pathologic stages of TCGA HCC patients.

Additional file 6: Figure S5. Waterfall plot and analysis regarding the relationship between gene expression and mutation status of top 15 mutated genes. a Top 15 genes of mutation frequency, such as TTN, TP53, CTNNB1, MUC16, and ALB, were selected for the waterfall plot with clinical grading information. b Correlation between gene expression and mutation in normal and different pathologic stages of HCC was analyzed.

Additional file 15: Figure S14. GAS2L3 expression analysis of DEN-induced HCC mouse model. Based on the tumor and adjacent non-tumor tissues (n = 14) of 20 mg/kg DEN-induced HCC model in mice, qPCR assay was performed to detect the expression level of GAS2L3. A wilcox.test was performed, and the results were visualized by a “‘ggplot2’” R package.

Additional file 9: Figure S8. Survival curve analysis for mutated TTN or OBSCN in different pathologic stages of HCC. Survival curve analyses for the mutation of a-d TTN, e-h OBSCN in the overall HCC, stage I, II, III-IV of HCC, were performed by a “survminer” R package, respectively.

Additional file 7: Figure S6. Waterfall plot and analysis regarding the relationship between gene expression and mutation status of 18 target genes. a Fifteen target genes, including CENPF, ASPM, SND1, MELK, TOP2A, IQCA1, CUZD1, TTK, NCAPQ, FPR2, GADD45G, CDC20, PPBP, PCSK1, IL11, GNGT1, CCNE2, BDKRB1, were selected for the waterfall plot with clinical grading information. b Correlation between the mutation and expression level of the above genes was analyzed.

Additional file 8: Figure S7. Survival curve analysis for mutated CTNNB1 or TP53 in different pathologic stages of HCC. The “survminer” R package was used to perform the survival curve analysis for the mutation of a-d CTNNB1, e-h TP53 in the overall HCC, stage I, II, III-IV of HCC, respectively.

Additional file 7: Figure S6. Waterfall plot and analysis regarding the relationship between gene expression and mutation status of 18 target genes. a Fifteen target genes, including CENPF, ASPM, SND1, MELK, TOP2A, IQCA1, CUZD1, TTK, NCAPQ, FPR2, GADD45G, CDC20, PPBP, PCSK1, IL11, GNGT1, CCNE2, BDKRB1, were selected for the waterfall plot with clinical grading information. b Correlation between the mutation and expression level of the above genes was analyzed.

Additional file 12: Figure S11. Decision tree and random forest analyses for normal controls and HCC cases. We perform a random forest modeling analysis to distinguish the normal controls and HCC cases. a Multiple dimension scale plot, b ROC curve, and c-d largely contributed genes were provided. e-f We performed a decision tree modeling analysis and compared the expression of these genes in 50 HCC tissues with adjacent non-tumor tissues, targeting ECM1, FCN2, ANGPTL6, OIT3, ADAMTS13, and LRRC14 genes.

Additional file 13: Figure S12. Expression level of SNRPA in five GEO datasets. From the GEO database, we obtained five independent datasets, including a GSE102079 (n = 91), b GSE76427 (n = 52), c GSE64041 (n = 60), d GSE121248 (n = 37), e GSE84005 (n = 38), to analyze the expression difference of SNRPA between HCC and adjacent non-tumor tissues. Each vertical line represents one patient with HCC.

Additional file 10: Figure S9. Relationship between gene expression and SNP status of CTNNB1 in different pathologic stages of HCC. a We extracted the SNP data of HCC, and identified the SNPs with relatively high frequency. b SNP status of CTNNB1 in the HCC cases. c Correlation between gene expression and CTNNB1 rs121913396, rs121913400, rs121913407, and TP53 rs28934571 SNP in normal and different pathologic stages of HCC was analyzed.

Litter inputs can influence soil respiration directly through labile C availability and, indirectly, through the activity of soil microorganisms and modifications in soil microclimate; however, their relative contributions and the magnitude of any effect remain poorly understood. We synthesized 66 recently published papers on forest ecosystems using a meta‐analysis approach to investigate the effect of litter inputs on soil respiration and the underlying mechanisms involved. Our results showed that litter inputs had a strong positive impact on soil respiration, labile C availability, and the abundance of soil microorganisms, with less of an impact related to soil moisture and temperature. Overall, soil respiration was increased by 36% and 55%, respectively, in response to natural and doubled litter inputs. The increase in soil respiration induced by litter inputs showed a tendency for coniferous forests (50.7%)> broad‐leaved forests (41.3%)> mixed forests (31.9%). This stimulation effect also depended on stand age with 30‐ to 100‐year‐old forests (53.3%) and ≥100‐year‐old forests (50.2%) both 1.5 times larger than ≤30‐year‐old forests (34.5%). Soil microbial biomass carbon and soil dissolved organic carbon increased by 21.0%‐33.6% and 60.3%‐87.7%, respectively, in response to natural and doubled litter inputs, while soil respiration increased linearly with corresponding increases in soil microbial biomass carbon and soil dissolved organic carbon. Natural and doubled litter inputs increased the total phospholipid fatty acid (PLFA) content by 6.6% and 19.7%, respectively, but decreased the fungal/bacterial PLFA ratio by 26.9% and 18.7%, respectively. Soil respiration also increased linearly with increases in total PLFA and decreased linearly with decreases in the fungal/bacterial PLFA ratio. The contribution of litter inputs to an increase in soil respiration showed a trend of total PLFA > fungal/bacterial PLFA ratio > soil dissolved organic carbon > soil microbial biomass carbon. Therefore, in addition to forest type and stand age, labile C availability and soil microorganisms are also important factors that influence soil respiration in response to litter inputs, with soil microorganisms being more important than labile C availability., Soil respiration, labile C availability, and soil microorganisms (e.g., microbial quantity and community structure) were significantly influenced by litter inputs.The increase in soil respiration in response to litter inputs was closely related to labile C availability and soil microorganisms.Soil microorganisms had a greater effect than labile C availability influence soil respiration in response to litter inputs.

The wide deployment of face recognition systems has raised serious concern on its security level. One of the most prominent threats is the presentation attack, which attempts to fool the system in the absence of the real person. In this article, we propose a way of identifying the spoof face by using spoofing noise. Since the spoofing noise is brought into the spoof image when an adversary uses some tricks to fool the face recognition system, it consists of imagining device noise and is affected by the spoofing environments. We think it is a clue against fake face. We first address how to use color channel difference images to enhance the spoofing noise, and then introduce a self-adapting attention framework named Noise-Attention Network to learn the end-to-end spoofing-features. Experiments on benchmarks including CASIA-FASD, MSU-MFSD and Idiap Replay-Attack demonstrate the effectiveness of the proposed method. It can yield results comparable with other current methods but has better robustness.

We described a route to a core–shell polynaphthoxazine nanofiber that can be fabricated by a single-nozzle electrospinning process using a phase-separated mixed polymer composite solution. The naphthoxazine-based polymer, as the core material, was synthesized by using a hydroxyl-containing naphthoxazine through esterification with methacryloyl chloride and subsequent free radical polymerization. Our results demonstrated that these core–shell structure nanofibres are composed of bundles of regularly structured ultrafine polynaphthoxazine nanofibers as the core and polymethylmethacrylate (PMMA) as the shell, because of the incompatibility of the naphthoxazine-based polymer and PMMA in mixed solvents. To maintain the structural integrity of the fibrous network during the curing process, we carried out the curing reaction in a chemically inert fluid with p-toluenesulfonic acid as the catalyst. After carbonization, the obtained carbon fiber with high nitrogen content (2.2 wt%), resulting from the oxazine ring as the carbon source, showed individual nanofibres without aggregation, and with a mean diameter of less than 30 nm. As an energy storage electrode, these naphthoxazine-based carbon nano-materials have excellent high-rate discharge capacity and low equivalent series resistance.

One octopus-shaped amphiphilic polymer was used to functionalize MWNTs for the first time. Characterization results showed that the octopus-shaped amphiphilic polymer was much more efficient at modifying MWNTs than linear polymers in aqueous or acetone solution. The hydrophobic cubic-silsesquioxane core locally anchored to the surface of the nanotubes, while the arms of the RAFT polymer extended into the aqueous solution, thus imparting steric stabilization to the nanotube dispersion.

Nano-wrinkled double-layer moth-eye-like antireflection coating (ARC) surfaces were fabricated by coupling octakis(methacryloxypropyl) silsesquioxane-based polymeric surface onto silsesquioxanes rigid layer on the quartz substrate. Octakis(aminophenyl) silsesquioxane (OAPS) reacted with decakis(methacryloxypropyl) silsesquioxane (CMSQ-T10) through Aza-Michael addition and octakis(methacryloxypropyl) silsesquioxane (CMSQ-T8) polymerized with hexafluorobutyl acrylate (HFBA) through radical polymerization in the rigid layer and top layer, respectively. Compressive stress, caused by mismatch of the different volumetric shrinkages between top layer and rigid layer, led to the wrinkled nanopatterned structures. Besides, the silsesquioxanes layer could offer as an in situ template and scaffold for the top polymeric surface. The reflectance was decreased to 3.5% (transmittance 98.5%) and the resulting ARC surfaces showed obvious hydrophobicity. We expect these ARC surfaces can find wide-spread applications in solar cells, camera lenses, and other photovoltaic components.

We herein report a hierarchical hybrid prepared from zero-dimensional cubic silsesquioxane, octa-aminophenylsilsesquioxane, and one-dimensional single-walled carbon nanotubes (SWNTs) through Friedel–Crafts acylation and amidation chemistry. We characterized the electronic structure and morphology of the nanohybrid by FT-IR spectroscopy, Raman spectroscopy, electrochemical analysis and field-emission scanning electron microscopy. In addition, high resolution TEM results indicated that their average diameter and diameter distribution remained nearly unchanged with respect to that of the pristine, in accordance with the Raman spectroscopic results. The specific capacitance of the obtained hybrid was larger than that of the pristine SWNTs due to its hierarchical structure and the charge transfer from both SWNTs and octa-aminophenylsilsesquioxane. To further study the electronic properties of conjugated functionalized silsesquioxane, the model compounds with a structure similar to that of the nanohybrid were designed and characterized by photoluminescence UV-vis analysis and density functional theoretical calculations. The analysis indicated the presence of an electron delocalization effect between the octa-aminophenylsilsesquioxane cores and the conjugated group. Such important electronic properties also assisted in the improvement of the performance of the hierarchical hybrid.

In this report, in contrast to conventional processes which rely upon non-covalent wrapping, we manipulate the covalent binding of conjugated polymers to carbon nanofibers to synthesize hybrid nanostructures. First, the Friedel–Crafts acylation reaction was utilized to introduce carboxyl groups onto the nanofiber sidewalls. Octa-aminophenylsilsesquioxane was then uniformly covalently attached to the carboxylated nanocarbon (CNF–COOH) through amide linkage. Subsequently, the phenylamino groups on the CNF surface were copolymerized with aniline via chemical oxidative polymerization to create a unique CNF-conjugated polymer hybrid (CNFS–PANI), and a binder-free CNF-based composite paper electrode was generated by vacuum-filtration. Morphology investigations revealed the formation of 3D porous interconnected network structures with loosely stacked hyperbranched PANI nanobundles due to the incorporation of OASQ onto the skeleton of CNFs. Such a flexible CNFS–PANI nanohybrid paper further exhibited excellent electric conductivity (0.31 S cm−1) and specific capacitance (167 F g−1), which is much higher than that of original CNFs (2.5 F g−1), suggesting its potential use as an electrochemical electrode material.

We prepared core–shell polymer–silsesquioxane hybrid microcapsules from cage-like methacryloxypropyl silsesquioxanes (CMSQs) and styrene (St). The presence of CMSQ can moderately reduce the interfacial tension between St and water and help to emulsify the monomer prior to polymerization. Dynamic light scattering (DLS) and TEM analysis demonstrated that uniform core–shell latex particles were achieved. The polymer latex particles were subsequently transformed into well-defined hollow nanospheres by removing the polystyrene (PS) core with 1:1 ethanol/cyclohexane. High-resolution TEM and nitrogen adsorption–desorption analysis showed that the final nanospheres possessed hollow cavities and had porous shells; the pore size was approximately 2–3 nm. The nanospheres exhibited large surface areas (up to 486 m2 g−1) and preferential adsorption, and they demonstrated the highest reported methylene blue adsorption capacity (95.1 mg g−1). Moreover, the uniform distribution of the methacryloyl moiety on the hollow nanospheres endowed them with more potential properties. These results could provide a new benchmark for preparing hollow microspheres by a facile one-step template-free method for various applications.

Due to the simplicity, immediacy and convenience, micro-blog is gaining more and more attention from all kinds of people, especially the researchers. Recently, topic detection on micro-blog has attracted more interests due largely to the rapid development of micro-blog. However, retrieving information from micro-blog is challenging, as the texts of the micro-blog are short, ungrammatical, and unstructured, and they are full of noise. Therefore, the traditional hot topic detection method performed less. In order to solve this problem, this paper proposed a method of hot topics found based on speed growth. In this method, the pretreated micro-blogs were divided into different windows, and the time information was extracted in each window; then, for each word, it was expressed as feature trajectory of binary group sequence; then, calculated the growth speed of the word and the users relevant to the word in every adjacent two windows, selected the words whose growth speed is greater than a certain threshold as hot keywords; then, hot topics were found through the hot keywords clustering. The experiment was done based on SINA micro-blog dataset, the miss rate and false detection rate were done to prove the feasibility of the algorithm, results showed that the method improved the efficiency of the detection to a certain extent.

To avoid the local optimum problems and to improve convergent speed when particle swarm optimization algorithm in solving complex problems, an adaptive cultural algorithm based on dynamic particle swarm optimization algorithm was proposed. Particle swarm algorithm introduced evaluation premature convergence degree of index to judge the population space condition to determine the role of the influence function time. The inertia weight of the particle was adjusted adaptively based on the premature convergence degree of the swarm. The diversity of inertia weight makes a compromise between the global convergence and the speed of convergence. The proposed algorithm was tested with four well-known benchmark functions. The experimental results show that the new algorithm has great global search ability convergence accuracy and convergence velocity is also increased and avoid the premature convergence problem effectively.