Search

With the development of information technology, digitalization has penetrated into our daily life, especially in the transcendence of time and space. People’s perception of time is accelerating under the wave of informationization. Human activities have become quantifiable, virtual, and ubiquitous “digital labor” in the vast cyberspace. Based on Harvey’s postmodern Marxist perspective, the deconstruction and criticism of modern rationality return to the reflection and confrontation of centrifugalized subjectivity in the framework of value rationality. The post-industrial era has entered a stage of elastic accumulation, where modernity and post-modernity, rationality and value, humanism and science are in constant conflict and collision in economic, social and cultural development. Also, the compression of space and time has expanded the production space of traditional labor that is contrary to modernity, has intensified the exploitation of private ownership under the logic of capital. Therefore, it is necessary to explore the production and practice of digital labor in the postmodernist perspective, reveal the material nature behind digital labor in the intelligent society, and look forward to the orderly governance and reflection of digital labor based on the logic of historical materialism.

Two-dimensional photocatalytic materials with unique properties have been well reported in recent decades. However, the strategy of controlling the photocatalytic process is still ongoing. Herein, Janus X2PAs (X = Si,...

Additional file 1: Supplemental material.

The oxidation of methane to a high-value-added chemical, methanol, is a major challenge in catalysis, requiring high energy input to overcome the CH

Photocatalytic water splitting for hydrogen energy is one of the most promising ways to solve the energy crises. The mechanism is unclear on the sequence of proton coupled electron transfer (PCET) in photocatalytic water dissociation catalyzed by organic material. Here, the water splitting catalyzed by zinc porphyrin with boron dipyrrin (ZnPP-BDP) is systematically investigated by density functional theory (DFT) calculations. The H2O/ZnPP in valence state based on the electron transfer pulls the trigger on the water splitting process. For the oxygen evolution reaction (OER) step on ZnPP, the processes for the two H ions dissociate from water are exothermic with the −1.06 and −0.95 eV energies respectively, and the O/ZnPP system is formed. The second H2O molecule on O/ZnPP system can provide the extra oxygen atom to produce the free O2 with 1.22 eV energy barrier. For the hydrogen evolution reaction (HER) step on BDP, the H ions dissociated from OER process can be captured by BDP to form free H2 with 2.24 eV/molecule energy released. In this attractive clean cyclic process, the ZnPP-BDP can continuously catalyze the H2O dissociated into free H2 and O2 by the shifting potential barrier. Besides, the proton coupled electron sequent transfer possess an essential role in photocatalytic water dissociation. It is very instructive to design sustainable photodecomposition catalysts for both OER and HER, and to design extraordinary biomimetic photosynthesizers for clean energy.

Panicle traits directly associated with yield are a target of selection in rice breeding. Although abundant QTL for panicle traits have been identified, there is little information about the genetic basis of panicle traits in japonica super rice (JSR) cultivars. In this study, we identified QTL for panicle traits in three environments using a population of recombinant inbred lines (RILs) derived from the JSR cultivar Liaoxing 1. A total of 197 RILs were genotyped with 285 polymorphic SNP markers. Phenotypic data and best linear unbiased prediction (BLUP) value of primary branch number (BNP), secondary branch number (BNS), grain number on primary branch (GNP), grain number on secondary branch (GNS), grain number per panicle (GN), panicle length (PL) and grain density (GD) were used for QTL mapping. A total of 105 QTL for seven panicle traits were detected in single environments using their BLUP values. Individual QTL explained 0.51%–52.22% of the phenotypic variation. Of the 105, 49 were also detected by joint multi-environment analyses. Five stable QTL: qGD9, qPL9, qGNP9, qGN6, and qBNS6.2 were identified in multiple environments. qGD9, qGNP9, and qPL9, co-localizing on chromosome 9, likely correspond to the known gene DEP1. Importantly, qGN6 and qBNS6.2 in a co-localization region were identified as novel QTL, and their Liaoxing 1 alleles had a positive effect. Several RILs with the QTL allele combinations qGD9/qPL9/qGNP9 and qGN6/qBNS6.2 showed greater GN. Further investigation of the putative gene underlying qGN6/qBNS6.2 would shed light on the molecular mechanism of JSR.

Additional file 1: Supplemental Figure 1. fMRI task paradigm. Supplemental Figure 2. Group difference in the Semantic Fluency-Fixation contrasts and its behavioral significance. One-way ANOVA, cluster-level P < 0.05, FWE corrected. Supplemental Table 1. The Post-hoc comparisons of the clinical characteristics in the China RSF multi-center cohort (Bonferroni corrected). Supplemental Table 2. Clinical characteristics of NC and AD patients in the Pitt center cohort. Supplemental Table 3. Correlation between PSD and cognition. Supplemental Table 4. The linear regression analysis of the variables correlated with PSD after adjusting for age. Supplemental Table 5. Demographic and neuropsychological/language characteristics of fMRI participants. Supplemental Table 6. Significant clusters in three linguistic tasks showing different activation by ANOVA analysis. Supplemental Table 7. Results of correlation analysis. # The spearman correlation coefficients were calculated between the average BOLD signal and the relevant fluency score of ACE-III. * The partial correlation coefficients were calculated between the average BOLD signal and PSD in the patient group. Supplemental Table 8. Post hoc analysis of cluster activation. Bold indicated significance (Bonferroni corrected).

Additional file 1.

Supplemental material, sj-docx-1-aop-10.1177_10600280211059040 for Are Proton Pump Inhibitors More Effective Than Histamine-2-Receptor Antagonists for Stress Ulcer Prophylaxis in Critically Ill Patients? A Systematic Review and Meta-Analysis of Cohort Studies by Na He, Yingying Yan, Shan Su, Qinggang Ge and Suodi Zhai in Annals of Pharmacotherapy

Photocatalytic water splitting is an effective way to obtain renewable clean energy. The challenge is to design tunable photocatalyst to meet the needs in different environments. At the same time, the oxygen and hydrogen evolution reactions (OER and HER) on the photocatalyst should be separated, which will be conducive to the separation of products. The electronic, optical and photocatalytic properties of Janus X2PAs (X = Si, Ge and Sn) monolayers are explored by first-principles calculation. All the strain-free X2PAs monolayers exhibit excellent photocatalytic properties with suitable band edge positions straddling the standard redox potential of water and large visible light absorption coefficients (up to 105 cm-1). Interestingly, the intrinsic internal electric field is favorable for separating photogenerated carriers to different surfaces of the monolayer. It contributes to realize the OER and HER separated on different sides of the monolayer. In particular, the energy band edge positions of X2PAs monolayers can be well adjusted by biaxial strain. Then it can effectively modulate photocatalytic reactions, suggesting X2PAs monolayers can be a piezo-photocatalytic switch between the OER, HER and full-reaction of redox for water splitting. This investigation not only highlights that the photocatalyst X2PAs monolayers with the separated OER and HER can be effectively tuned by the mechanical strain, but also provides a new strategy for designing highly adaptable and tunable piezo-photocatalysts., Comment: 22 pages, 5 figures

In alkaline, the electrocatalytic oxygen evolution reaction (OER) of dual transition metal atoms (2TM) nitrogen-decorated graphene as double-atom catalysts (DACs) has received special attention. Here, using density functional theory (DFT) calculations, the OER electrocatalysis of 2TM-pyridine/amino-nitrogen-decorated graphene (2TM-NPAG and 2TM-NPG. 2TM represents FeCo, FeNi, CoNi) is studied. The electrocatalytic OER mechanism is that 2TM-NPG act as the pre-catalyst, while the real catalysts are 2TM-NPAG and 2TM-NPG-O. Especially CoNi-NPAG and CoNi-NPG-O exhibit higher OER activity even than state-of-the-art RuO2 at pH= 14. It is also confirmed that the potential-determining step is also the rate-determining step. Amino-nitrogen is the main accepter of electrons from CoNi atoms, pyridine-nitrogen is the main accepter of electrons from nearby C atoms. The role of different N coordination continues to influence the whole process of electrocatalytic OER of CoNi-NG. Simultaneously, the over-potential of CoNi-NG is in a volcano-shaped relationship with the electronic properties (oxidation state or d-band center) of catalytic site Co. And CoNi-NPAG and CoNi-NPG-O are closest to the center of OER over-potential (a function of d-band center and oxidation state) contour plot, implying their best catalytic activity among all the CoNi-NG. The optimal electronic properties contribute the excellent OER performance of CoNi-NPAG and CoNi-NPG-O, and it provides the new breakthrough point to develop DACs with high performance.

The integration of piezoelectric and micro-electro-mechanical system (MEMS) technologies is promoting the rapid development of the MEMS industry. However, due to the lack of excellent in-plane and out-of-plane piezoelectric coefficients, good ambient temperature stability, and high mechanical durability, the reported two-dimensional piezoelectric thin films are facing severe challenges in the development of MEMS. Therefore, based on density functional theory calculations, we simulated the VIA group (the sixth main family in the periodic table of elements) functional MXenes, namely, Sc2CXY (Sc2COS, Sc2COSe, Sc2CSO, and Sc2CSeO). The results show that this kind of material has good dynamic, thermal, and mechanical stability. Importantly, the structure exhibits good in-plane and out-of-plane piezoelectric effects due to the inversion asymmetry, bandgap adjustability, flexibility, and different electronegativity. Among them, the piezoelectric strain value of d33 is one to three orders of magnitude higher than that of d22 or d31, which makes these materials can become a strong candidate for advanced equipment such as nano-wearable electronics, robot bionic skin, and piezoelectric products for MEMS.

BackgroundTo evaluate the association between postdiagnostic dairy intake and survival among patients with colorectal cancer (CRC).MethodsThis study analyzed data from the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). Postdiagnostic dairy intake and other dietary and lifestyle factors were obtained from validated questionnaires. Individual dairy items including milk, cheese, yogurt, and so on were reported, and total, high-fat, and low-fat dairy intakes were derived.ResultsA total of 1753 eligible CRC cases were identified until 2012, from which 703 deaths were documented after a median follow-up time of 8.2 y, and 242 were due to CRC. Overall, when comparing those who consumed 21+servings/wk with&nbsp

Refracturing technology has been widely applied to increase the production rate of multi-fractured horizontal wells (MFHWs) and enhance ultimate recovery. However, due to the complicated relationships between various parameters, it is often difficult to select candidate wells for refracturing. A novel method combining analytic hierarchy process (AHP), grey relation analysis (GRA) and fuzzy logic was proposed in this study to evaluate refracturing potential of wells from reservoir quality and initial completion efficiency. First, based on the parameters of the constructed wells, several elements were chosen as appraisal factors. AHP was used to establish a multi-parameter evaluation system for refracturing treatment. Then, GRA was used to calculate the weight coefficient and sort out the main factors that influence fracturing result. Finally, GRA was coupled with fuzzy logic to determine the classification threshold of reservoir quality. A novel comprehensive evaluation score (CES) was proposed to determine the priority of the refracturing wells. The method was successfully applied to a tight oilfield in Northeast China and the optimum refracturing potential area was selected based on the reservoirs quality and completion efficiency by using quadrant analysis. Average daily oil production increased from 2.3 to 17.6 tons per day after refracturing treatment. The method can be used to identify refracturing candidates quickly and economically.

Rice blast, caused by Magnaporthe oryzae, is a serious threat to global rice production. In recent years, many pathogenicity genes of M. oryzae have been identified, although most of their functions remain unknown. In this study, we report the synergistic deletion of RGS1 and COS1 that may reduce the pathogenicity of M. oryzae. The investigation involved comparing ΔMorgs1, ΔMocos1, and ΔMorgs1/ΔMocos1 mutants. The ΔMorgs1/ΔMocos1 mutant showed a weak reduction in vegetative growth, and the colonies displayed fewer and smoother aerial hyphae. The ΔMorgs1/ΔMocos1 mutant exhibited delayed appressorium-like structure formation and 'low pathogenicity' on detached rice seedling leaves when compared with ΔMocos1. Moreover, the melanin content of the single and double mutants was remarkably lower than that of the WT type. Thus, our results indicate that the synergy between RGS1 and COS1 may be crucial in the pathogenicity of M. oryzae.

The application of straw and biochar can effectively improve soil quality, but whether such application impacts paddy soil bacterial community development remains to be clarified. Herein, the impacts of three different field amendment strategies were assessed including control (CK) treatment, rice straw (RS) application (9000 kg ha−1), and biochar (BC) application (3150 kg ha−1). Soil samples were collected at five different stages of rice growth, and the bacterial communities therein were characterized via high-throughput 16S rDNA sequencing. The results of these analyses revealed that soil bacterial communities were dominated by three microbial groups (Chloroflexi, Proteobacteria and Acidobacteria). Compared with the CK samples, Chloroflexi, Actinobacteria, Nitrospirae and Gemmatimonadetes levels were dominated phyla in the RS treatment, and Acidobacteria, Actinobacteria, Nitrospirae and Patescibacteria were dominated phyla in the BC treatment. Compared with the RS samples, Chloroflexi, Acidobacteria, Actinobacteria, and Verrucomicrobia levels were increased, however, Proteobacteria, Gemmatimonadetes, Nitrospirae, and Firmicute levels were decreased in the BC samples. Rhizosphere soil bacterial diversity rose significantly following RS and BC amendment, and principal component analyses confirmed that there were significant differences in soil bacterial community composition among treatment groups when comparing all stages of rice growth other than the ripening stage. Relative to the CK treatment, Gemmatimonadaceae, Sphingomonadaceae, Thiovulaceae, Burkholderiaceae, and Clostridiaceae-1 families were dominant following the RS application, while Thiovulaceae and uncultured-bacterium-o-C0119 were dominant following the BC application. These findings suggest that RS and BC application can improve microbial diversity and richness in paddy rice soil in Northeast China.

The voltage error of three-phase combined transformer is detected according to the single-phase method, but this situation is not consistent with the actual operation state, thus the single-phase method can not accurately detect the actual voltage error characteristics of the three-phase combined transformer. In this paper, the three-phase combined transformer composed by three-column is treated as the object, using the real test platform to simulate the actual operation condition of the three-phase combined transformer, which carries out the test and in-depth analysis of its voltage error under different primary current conditions. The main conclusions are as follows: the three-phase combined transformer qualified in single-phase method may not be qualified in three-phase method, the current makes a linear influence on the voltage error of three-phase combined transformer, with the increase of current, the algebraic sum of error variation of three-phase voltage transformer is approximately equal to zero.

Voltage errors of three voltage transformers in three-phase four-line metering devices in ungrounded distribution power system are interrelate with each other, however, the error characteristics of each voltage transformer under unbalanced secondary burdens have scarcely been studied. In this paper, three-phase three-element combined transformer is taken as an example to analyze the influence of unbalanced secondary burdens on voltage errors of its three voltage transformers. Firstly, equivalent circuit of the three voltage transformers taken as a whole is established, and then voltage error is analyzed theoretically and tested to verify the validity of theoretical analysis. Results show that the change of the secondary burden of voltage transformer will results in the error of each voltage transformer changing linearly when the secondary burdens of two other voltage transformers remain unchanged, the primary current has some influence on the error of voltage transformer, however, the influence is much smaller compared with the influence of unbalanced secondary burdens on voltage error, the characteristics that unbalanced secondary burdens have a great influence on voltage errors can be utilized to optimize the power metering error of electric energy metering device.

Figure S10. Relationship between non-conversion level and mRNA translation state for candidate m5C sites with insufficient coverage in bsRNA-seq fraction 1. Related to Fig. 5. bsRNA-seq libraries were grouped as biological triplicates per fraction (e.g. LibB 1, LibC1 and LibE1 each report on sites detected in bsRNA-seq fraction 1), allowing the calculation of average non-conversion levels per individual site and per fraction. A: Non-conversion levels per individual site across the polysome profile were partitioned into nine soft clusters (C1–9 arranged here by similarity in trend with polysome profile) using Mfuzz. 315 candidate m5C sites were included based on having coverage in at least 9 out of 12 bsRNA-seq fraction samples and ≥ 10 average coverage in bsRNA-seq fractions 2–4 but failing this criterion for fraction 1. Degree of cluster ‘membership’ is indicated by the colour scale depicted to the right of panel A. Candidate sites with high membership (blue) have the best match to the respective cluster’s overall pattern. The legend to the right of panel A gives a colour/significance key applicable to all panels. Insets are: pie charts showing distribution of cluster members across different mRNA regions; boxplots showing site non-conversion distribution of cluster members across the polysome profile. Asterisks indicate significance p-value from unpaired, two-tailed Student’s t-test comparing the means of adjacent fractions. B: Mfuzz clusters from panel A were grouped into three translation state trend categories by visual inspection, showing a negative (clusters C3,4,6,9; N = 133), neutral (clusters C2,8,1; N = 75) or positive trend (clusters C5,7; N = 107) with polysome association. Top panels: line graphs displaying individual site average non-conversion levels across fractions. Middle panels: boxplots showing distribution of site non-conversion levels in each fraction. Asterisks indicate significance p-value from unpaired, two-tailed Student’s t-test comparing the means of adjacent fractions. Bottom panels: boxplots showing distribution of site coverage in each fraction. C: Stacked bar charts showing distribution of sites in the different translation state trend categories across mRNA regions (top) and distribution of sites in different mRNA regions across translation state trend categories (bottom). Asterisks indicate significance p-values following binomial test against the distribution of all sites. The legend to the right of panel A gives a colour/significance key applicable to all panels.

Additional file 3: Figure S1. The sensitivity analysis of the unprotected sex. Figure S2. The sensitivity analysis of the HIV testing. Figure S3. The sensitivity analysis of the equipment use. Figure S The sensitivity analysis of the HIV prevalence. Figure S5. The sensitivity analysis of the general condom use. Figure S6. The sensitivity analysis of the consistent condom use. Figure S7. The sensitivity analysis of the condom use with casual partners. Figure S8. The sensitivity analysis of the condom use with regular partners.

Figure S6. Additional validation and NSUN2-dependence of candidate m5C sites in mRNA and ncRNA. Related to Fig. 3. Amplicon-bsRNA-seq was performed with total RNA isolated from HeLa cells, or the prostate cell lines LNCaP or PrEC, after siRNA-mediated m5C:RNA methyltransferase knockdown targeting NSUN2 or TRDMT1 along with control siRNAs (targeting m5C:DNA methyltransferase DNMT1 or a non-targeting control [NTC]; see Fig. S5 for knockdown efficiency controls). Read coverage per amplicon was from 3500 to 67,500 (see Table S6). Grids are organised by knockdown sample in rows and cytosine position along the analysed transcript section in columns (genomic coordinates are given for the first and last interrogated cytosine position [in black], as well as the candidate m5C site [in red]). A white-to-red colour scale is used to tint each square by the degree of cytosine non-conversion. The longest mRNA isoform (based on Ensembl) is shown with the candidate m5C site position indicated by a red circle. The sequence context (non-converted cytosine indicated in red) is given. The enzyme identified to be responsible for cytosine methylation is indicated above the candidate sites: N – NSUN2; N? – unresolved but likely NSUN2. A: ‘Confirmatory’ HeLa data (N = 1) shown for mRNA sites in NAPRT (nicotinate phosphoribosyltransferase), CINP (cyclin dependent kinase 2 interacting protein), SCO1 (SCO cytochrome C oxidase assembly protein 1) and MCFD2 (multiple coagulation factor deficiency 2) (top and middle row). ‘In depth’ data (N = 2–3) is shown as the average of at least two biological replicates for mRNA sites in CCT5 (chaperonin containing TCP1 Subunit 5) and NSUN2 (bottom row). These two sites are likely controlled by NSUN2, although the non-conversion change is not significantly (ns) different (Student’s t-test) in comparison to the NSUN2 KD sample (non-conversion averages are indicated to the right; see also Table S6). B: ‘Confirmatory’ prostate data (N = 1) shown for mRNA sites in SZRD1 (SUZ RNA binding domain containing 1), RTN3 (reticulon 3), PWP2 (PWP2 small subunit processome component) and SRRT (serrate) (top and middle row) and ncRNA sites in SCARNA2 (small Cajal body-specific RNA 2) and SNORD62B (small nucleolar RNA, C/D box 62B) (bottom row).

Figure S2. bsRNA-seq mapping and data analysis. Related to Figs. 2 and 5. Workflow from bsRNA-seq read processing and mapping, m5C candidates site selection to clustering by non-conversion level across polysome gradients. For the definitive site selection, steps in the workflow were performed sequentially. Selection criteria for high confidence candidate sites and alternate groupings of bsRNA-seq libraries for different purposes are indicated. Note, four bsRNA-seq fraction libraries representing distinct translation states were sequenced per biological replicate, creating a total of twelve libraries termed LibB1–4, LibC1–4 and LibE1–4. For global m5C candidate site calling, Libs 1–4 were combined into one composite library for each biological replicate, creating cLibB, C and E. These composite libraries approximate a total transcriptome-wide survey for each biological replicate. For clustering analyses, libraries from corresponding bsRNA-seq fractions (i.e. LibB1, LibC1 and LibE1 and so forth) formed biological replicates of each other.

Additional file 4: Figure S9. The forest plot of the condom use among FSWs. Figure S10. The forest plot of the condom use among IDUs. Figure S11. The forest plot of the condom use among MSM. Figure S12. The forest plot of condom use with casual partners. Figure S13. The forest plot of condom use with regular partners. Figure S14. The forest plot of consistent condom use.

Additional file 2: Table S1. Study quality assessment. Table S2. The results of egger test.

Figure S5. siRNA knockdown efficiency controls. Related to Fig. 3. HeLa cells, or the prostate cell lines LNCaP or PrEC, were transiently transfected with siRNAs targeting the m5C:RNA methyltransferases NSUN2 or TRDMT1, the m5C:DNA methyltransferase DNMT1 or a non-targeting control (NTC) as indicated in the panels. Across panels, results are arranged with HeLa ‘confirmatory’ data on top (N = 1), HeLa ‘in depth’ data in the middle (N = 3), and prostate cell line ‘confirmatory’ data at the bottom (N = 1). A: Western blots for NSUN2, TRDMT1, DNMT1 and the internal controls alpha-tubulin or GAPDH are indicated on the left. siRNA knockdown condition is shown below. One replicate for the HeLa ‘in depth’ data is shown; similar results were obtained for the other replicates. B: mRNA levels are shown relative to those in the NTC control. HeLa RT-qPCR data were normalised to the internal control genes HPRT (top) or GAPDH (middle), RT-qPCR data from the prostate cell lines were normalised to the geometric mean of the internal control genes MRPL9, H2AFV and TCF25. ‘Confirmatory’ data (top and bottom) are shown as averages of three technical replicates. ‘In depth’ data (middle) are shown as averages of three biological replicates. Error bars indicate standard error of the mean. C-D: Amplicon-bsRNA-seq results for the R-Luc spike-in negative controls (C) and selected tRNAs as positive controls (D). Grids are organised by knockdown sample in rows and cytosine position along the analysed transcript section in columns (for tRNAs structural positions are given for the first interrogated cytosine as well as the candidate m5C sites [in red]). A white-to-red colour scale is used to tint each square by the degree of cytosine non-conversion. Note, C38 in tRNAGly (GCC) is a known target of TRDMT1, whereas C48–50 in tRNAGly (GCC) and C48 in tRNAThr (UGU) are mediated by NSUN2. Student’s t-test results of non-conversion change for tRNAGly (GCC) in the ‘confirmatory’ HeLa data is indicated next to the grid with asterisks and diamonds showing significance to the NSUN2 or TRDMT1 knockdown sample, respectively (key in top panel).

Table S2. Sequences of the Renilla Luciferase in vitro spike-in transcripts.

Figure S8. Correlation of mRNA translation and stability with m5C site content. Related to Fig. 4. A: Cumulative density distribution of translation efficiency for candidate site-containing and all remaining mRNAs. Translation efficiency values are based on HeLa cell ribosome profiling data from [X Wang, ZK Lu, A Gomez, GC Hon, YN Yue, DL Han, Y Fu, M Parisien, Q Dai, GF Jia, et al. [33]; first plot], [[79]; second plot] or [[80]; cell cycle plots]. (GSE49339: m5C mRNA, N = 666; remaining mRNA, N = 12,185. GSE102113: m5C mRNA, N = 667; remaining mRNA, N = 11,460. GSE79664: m5C mRNA, N = 669; remaining mRNA, N = 11,717). B: Cumulative density distribution of mRNA half-life for candidate site-containing and all remaining mRNAs. HeLa cell mRNA half-life data was taken from [[33]; first plot)] or [[79]; second plot]. (GSE49339: m5C mRNA, N = 649; remaining mRNA, N = 10,569. GSE102113: m5C mRNA, N = 612; remaining, N = 11,175).

Figure S7. Sequence context and NSUN2-dependence of candidate m5C sites. Related to Fig. 4. A: Gene Ontology (GO) term enrichment of candidate sites. Analysis was performed using the enrichGO function in ClusterProfiler using transcriptome-wide candidate sites (n = 846), with all genes detected at FKPM≥1 in the bsRNA-seq used as background. Bonferroni correction was applied and terms with p

Figure S11. Identification of individual sites with significant correlation of cytosine non-conversion with polysome co-sedimentation. Related to Fig. 6. A: Transcriptome-wide candidate m5C sites were used as input for logistic regression analysis (methylKit; [94]. For each pairwise comparison of adjacent polysome profile fractions a minimum of ≥10 average read coverage across each bsRNA-seq fraction was required. Plots show the -log10 q-value (FDR) of the non-conversion change, against the relative non-conversion difference for each pairwise comparison, with the number of sites that qualified indicated above (993 of 1034 sites were involved in at least one such comparison). Each dot represents a single site, sites that score as significant (q-value

Table S1. HeLa cell lysate parameters. Measurements of HeLa cell lysate biological triplicates. For each biological replicate three technical replicate 150 mm diameter plates were seeded with six million (M) cells and grown for 24 h before harvest. Two plates were used for cell lysate preparation and the protein concentration measured by protein assay and absorption at 260 nm. The third plate was used to count final cell number.

Figure S4. m5C candidate site call reproducibility across biological replicates and effects of non-conversion ‘noise suppression’. Related to Fig. 2. A: Pair-wise scatter plot comparisons of transcriptome-wide candidate sites called in composite libraries of each biological replicate. Sites shown passed the 80CT, 30RC and 5C filter in their respective composite library (a non-conversion cut-off was not applied). Further to that, only sites with coverage in all three replicates were used. The adjusted R-squared value following linear regression is shown. B: Effect of the 3C and S/N90 filters on candidate site calling in different RNA types. The number of candidate sites that passed the 80CT, 30RC, 5C filter in their respective composite library and fulfilled the 10MM criterion are listed. C: Position of candidate sites in the tRNA cloverleaf consensus structure. Each circle indicates a nucleotide position within the tRNA cloverleaf structure, with blue filled circles indicating position at which candidate sites were identified. Iso-acceptors found to carry the candidate site are identified by the single letter amino acid code. D: Genetic code table highlighting tRNA iso-decoders with candidate sites in blue. C-D: Of note, we detected the NSUN2-dependent sites at the edge of the variable loop at position C48–50 in a variety of tRNA iso-decoders, as well as at position C34 of intron-containing tRNALeu (CAA). We further identified the TRDMT1-dependent modification of C38 in tRNAAsp (GUC). Interestingly, we also detected several candidate sites at structural position C72. The established NSUN6-dependent sites in tRNAThr (UGU) and tRNACys (GCA) iso-decoders did not receive read coverage. Instead, we saw clear non-conversion at C72 in tRNAIle (UAU), tRNALys (CUU) and tRNASer (ACU); these might be novel NSUN6 substrates. C70 in tRNAGly (CCC) is indicated in the figure, however, detection of this site is heavily driven by the terminal base of reads in one direction, thus likely suspect.

Additional file 1. The information of the selected studies.

Figure S9. Clustering of candidate m5C site non-conversion level patterns across the polysome profile. Related to Fig. 5. bsRNA-seq libraries were grouped as biological triplicates per fraction (e.g. LibB 1, LibC1 and LibE1 each report on sites detected in bsRNA-seq fraction 1), allowing the calculation of average non-conversion levels per individual site and per fraction. Non-conversion levels per individual site across the polysome profile were partitioned into nine soft clusters (C1–9 arranged here by similarity in trend with polysome profile) using Mfuzz. 254 candidate m5C sites were included based on having coverage in at least 9 out of 12 bsRNA-seq fraction samples and ≥ 10 average coverage in each of the four bsRNA-seq fractions. Degree of cluster ‘membership’ is indicated by the colour scale depicted to the right of panel A. Candidate sites with high membership (blue) have the best match to the respective cluster’s overall pattern. The legend to the right gives a colour/significance key applicable to all panels. Insets are: pie charts showing distribution of cluster members across different mRNA regions; boxplots showing site non-conversion distribution of cluster members across the polysome profile. Asterisks indicate significance p-value from unpaired, two-tailed Student’s t-test comparing the means of adjacent fractions. For Fig. 5, clusters C9,2,7,1,4,6 were combined into the negative trend category, clusters C3,5 into the neutral category, and cluster C8 formed the positive category. (PDF 944 kb)

Figure S3. Effects of the 3C and S/N90 filters on specificity and sensitivity of m5C candidate site detection. Related to Fig. 2. In each panel, plots are arranged vertically by RNA under investigation, and horizontally by the extent of sequential filtering (initial read mapping—after removing reads with > 3 non-converted cytosines ‘3C filter’—after suppressing sites below the chosen signal-to-noise threshold ‘3C & S/N90 filter’ [less than 90% of reads passing the 3C filter]). Dual y-axis plots show either cytosine conversion (A,C) or non-conversion (B) (left y-axis, blue bars) and read coverage (right y-axis, red line) against cytosine position in the respective reference sequence (x-axis). Data is shown as mean across the three biological replicates with error bars indicating ± standard deviation. Candidate sites disqualified by the S/N90 filter are identified by orange bars. The effects of the filters were evaluated using selected spike-in control (A), rRNA (B) and tRNA (C) sequences. A: Panel of spike-in controls, R-Luc RNA and two arbitrarily selected ERCC transcripts. B: Mature ribosomal RNA species. Note that cytosine non-conversion is plotted for improved visualisation. The fourth to sixth panels show zoomed-in plots of fully filtered 18S and 28S rRNA data. Residues of zoomed regions are indicated on the top and correspond to numbering in full-scale plots. Green arrows and position labelling indicate the two known m5C sites in 28S rRNA [96]. C: Selected tRNA examples. tRNAAsp (GUC), tRNAGlu (UUC) and tRNAGly (GCC) were chosen to represent different m5C positions within tRNAs and to illustrate the adverse effect of the chosen filters on tRNAs with > 3 modified cytosines. Cytosine numbering is according to the tRNA consensus structural positions.

peer-reviewed Particle size distribution of gravelly soil plays a crucial role in debris flow initiation. For better understanding the mechanism of debris flow formation, two crucial mechanical property parameters of the gravelly soil are required to be studied meticulously: hydraulic conductivity and strength. With the aim of measuring the composition of the gravelly soil, 182 soil samples were taken from debris flow prone areas. With the aid of a sieve test, the particle size distribution of the samples can be obtained and analyzed. Then fractal theory was employed to compute the fractal dimension of the soil samples. By analyzing the results of sieve test (particle size distribution curves) and the results of the fractal theory calculations, the relationship between fractal dimension and particle size distribution can be explored. The results illustrate that the particle compositions of the gravelly soil tends to remain uniform as the fractal dimension increases. Moreover, as the coarse particle content increases, the fractal dimension decreases. To better understand the formation mechanism of debris flows, direct shear tests were conducted. Subsequently the experimental results were analyzed. By analysis, the following conclusions can be drawn: the soil strength decreases as the fractal dimension increases, and for soils with lower moisture content and identical dry density, a linear relationship between fractal dimension and cohesion force was identified. Moreover, cohesion force and internal friction force both decrease as the fractal dimension increases, but the internal friction angle decreases slightly while the cohesion force decreases greatly. Therefore we concluded that soil strength decreased mainly due to the reduction in cohesion force. PUBLISHED peer-reviewed

// Jian’an Bai 1 , He Na 2 , Xiumei Hua 2 , Yaling Wei 2 , Tian Ye 1 , Yiqiang Zhang 3 , Guo Jian 4 , Weiwen Zeng 2 , Lijun Yan 2 , Qiyun Tang 2 1 Department of Gastroenterology, Sir Run Run Hospital Affiliated with Nanjing Medical University, Nanjing, China 2 Department of Gastroenterology, The First Affiliated Hospital with Nanjing Medical University, Nanjing, China 3 Department of Radiology, Linyi People's Hospital, Dezhou, China 4 Department of Orthopaedics, Linyi People’s Hospital, Dezhou, China Correspondence to: Qiyun Tang, email: tqy831@163.com Keywords: NENs, epidemiology, LDL-C, PCSK9, miR-224 Received: February 29, 2016 Accepted: December 16, 2016 Published: December 28, 2016 ABSTRACT Neuroendocrine neoplasms (NENs) represent relatively rare tumors. The lack of diagnostic, therapeutic method and prognostic factors makes them a challenge to us. We retrospectively reviewed the data of 205 NENs patients among which 157 cases were followed-up. Proprotein convertase subtilisin/kexin 9 (PCSK9), a regulator of low density lipoprotein cholesterol (LDL-C), was confirmed as a target gene of microRNA-224. We found an increased incidence of NENs from 2012 to 2015. Women were usually diagnosed at earlier stages than men ( P < 0.05). Tumor grading was associated with primary tumor site, especially esophagus and cardia NENs all at G3 ( P

Purpose Glucocorticoid (GC) is probably related to biological aging, but the exact mechanism remains unknown. Cushing's disease (CD) could represent a unique human model for examining the effects of prolonged exposure to hypercortisolism and its relationship with aging. Thus, we studied the alterations of neurites in CD patients with Neurite orientation dispersion and density imaging (NODDI). Methods CD patients (n = 15) and healthy control subjects (n = 15) were included in this study. Orientation dispersion index (Odi), neurite density index (Ndi), partial fraction of free water (fiso), partial fraction of extracellular water (fec) were examined in a cross-sectional analysis. Results Significant altered NODDI parameters were found in CD patients. Some of these alterations were correlated with current age. Additionally, increased dendritic density was found in cerebellar of CD patients. Conclusion Hypercortisolism relative reductions of the dendritic density were correlated with current age in several regions of CD patients. Our study enhances the understanding of the link between the aging and GC.

The existing transformer calibrator has many problems such as, low accurate, poor stability, error interference of frequency conversion, small range of working circuit, etc., this paper focus on those problems, adopting adjustment technology of rectangular coordinate system and polar coordinate system, automatic measurement feedback technology with high accurate, designs an adoptable digital program-control standard signal source with two channels of phase and amplitude, realizing automatic feedback of phase and amplitude after the frequency and load changing, realizing the automatic verification and calibration of transformer calibrator and PT secondary drop test instrument. The device designed in this paper has already passed the test of third-party detection mechanism, all of the technical indexes and function meet the demand.

Conjugated polyaniline has shown anticorrosive, hydrophilic, antibacterial, pH-responsive, and pseudocapacitive properties making it of interest in many fields. However, in situ grafting of polyaniline without harsh chemical treatments is challenging. In this study, we report a simple, fast, and non-destructive surface modification method for grafting tetraaniline (TANI), the smallest conjugated repeat unit of polyaniline, onto several materials via perfluorophenylazide photochemistry. The new materials are characterized by nuclear magnetic resonance (NMR) and electrospray ionization (ESI) mass spectroscopy. TANI is shown to be covalently bonded to important carbon materials including graphite, carbon nanotubes (CNTs), and reduced graphene oxide (rGO), as confirmed by transmission electron microscopy (TEM). Furthermore, large area modifications on polyethylene terephthalate (PET) films through dip-coating or spray-coating demonstrate the potential applicability in biomedical applications where high transparency, patternability, and low bio-adhesion are needed. Another important application is preventing biofouling in membranes for water purification. Here we report the first oligoaniline grafted water filtration membranes by modifying commercially available polyethersulfone (PES) ultrafiltration (UF) membranes. The modified membranes are hydrophilic as demonstrated by captive bubble experiments and exhibit extraordinarily low bovine serum albumin (BSA) and Escherichia coli adhesions. Superior membrane performance in terms of flux, BSA rejection and flux recovery after biofouling are demonstrated using a cross-flow system and dead-end cells, showing excellent fouling resistance produced by the in situ modification.

It is challenging to realize the piezoelectricity of 2D films by exerting the stress along the direction perpendicular to the film plane. The ability to transfer the mechanical stress perpendicular to the films into electric energy can significantly enhance the transfer efficiency and have more broad application prospects, such as medical device (sphygmomanometer) and ultrathin nano-sensor devices (tactile sensor as the bionic skin of robot). Then the out-of-plane piezoelectric coefficients e33 and d33 of film have the special importance. We investigate the lattice and piezoelectricity properties of group V-IV-III-VI films (SnN–InO, GeN-GaO, and SiN–AlO) using first-principles calculations. It is found that they have the promising piezoelectric coefficients e33 and d33 due to their broken inversion symmetry along the direction perpendicular to the film plane. The e33 (38.69 × 10−10 C m−1) of SiN–AlO is the largest, which is larger than that (5.20 × 10−10 C m−1) of gallium nitride nanowires' surface layers by 7.4 times, while the out-of-plane piezoelectric strain coefficient d33 (5.29 × 103 pm V−1) of SnN–InO is the largest, which is one order of magnitude larger than that (0.42 × 103 pm V−1) of the Y-doped ZnO nano sheets. The special direction's piezoelectricity of the SiN–AlO and SnN–InO films indicates that they have the new applications in nanoscale energy harvesting devices, nano-sensor and other micro-electromechanical devices, which can transfer the mechanical stress perpendicular to the films into electric energy.