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Background Heterogeneity of leukemia-initiating cells (LICs) is a major obstacle in acute myeloid leukemia (AML) therapy. Accumulated evidence indicates that the coexistence of multiple types of LICs with different pathogenicity in the same individual is a common feature in AML. However, the functional heterogeneity including the drug response of coexistent LICs remains unclear. Therefore, this study aimed to clarify the intra-heterogeneity in LICs that can help predict leukemia behavior and develop more effective treatments. Methods Spleen cells from the primary Setd2-/- -AML mouse were transplanted into C57BL/6 recipient mice to generate a transplantable model. Flow cytometry was used to analyze the immunophenotype of the leukemic mice. Whole-genome sequencing was conducted to detect secondary hits responsible for leukemia transformation. A serial transplantation assay was used to determine the self-renewal potential of Setd2-/- -AML cells. A limiting-dilution assay was performed to identify the LIC frequency in different subsets of leukemia cells. Bulk and single-cell RNA sequencing were performed to analyze the transcriptional heterogeneity of LICs. Small molecular inhibitor screening and in vivo drug treatment were employed to clarify the difference in drug response between the different subsets of LICs. Results In this study, we observed an aged Setd2-/- mouse developing AML with co-mutation of NrasG12S and BrafK520E . Further investigation identified two types of LICs residing in the c-Kit+ B220+ Mac-1- and c-Kit+ B220+ Mac-1+ subsets, respectively. In vivo transplantation assay disclosed the heterogeneity in differentiation between the coexistent LICs. Besides, an intrinsic doxorubicin-resistant transcriptional signature was uncovered in c-Kit+ B220+ Mac-1+ cells. Indeed, doxorubicin plus cytarabine (DA), the standard chemotherapeutic regimen used in AML treatment, could specifically kill c-Kit+ B220+ Mac-1- cells, but it hardly affected c-Kit+ B220+ Mac-1+ cells. Transcriptome analysis unveiled a higher activation of RAS downstream signaling pathways in c-Kit+ B220+ Mac-1+ cells than in c-Kit+ B220+ Mac-1- cells. Combined treatment with DA and RAS pathway inhibitors killed both c-Kit+ B220+ Mac-1- and c-Kit+ B220+ Mac-1+ cells and attenuated disease progression. Conclusions This study identified two cell subsets enriched for LICs in murine Setd2-/- -AML and disclosed the transcriptional and functional heterogeneity of LICs, revealing that the coexistence of different types of LICs in this model brings about diverse drug response.

Purpose Assembly accuracy is the guarantee of mechanical product performance, and the characterization of the part with geometrical deviations is the basis of assembly accuracy analysis. Design/methodology/approach The existed small displacement torsors (SDT) model cannot fully describe the part with multiple mating surfaces, which increases the difficulty of accuracy analysis. This paper proposed an integrated characterization method for accuracy analysis. By analyzing the internal coupling relationship of the different geometrical deviations in a single part, the Monomer Model was established. Findings The effectiveness of the Monomer Model is verified through an analysis of a simulated rotor assembly analysis, and the corresponding accuracy analysis method based on the model reasonably predicts the assembly deviation of the rotor. Originality/value The Monomer Model realizes the reverse calculation of assembly deformation for the first time, which can be used to identify the weak links that affect the assembly accuracy, thus support the accuracy improvement in the re-assembly stage.

The runtime environment and workload of software are constantly changing, requiring users to make appropriate adjustments to accommodate these changes. The runtime configuration, however, as the interface for users to manipulate software behavior often requires domain-specific knowledge to understand. This usually results in users spending a considerable amount of time wading through document and user manuals trying to understand the runtime configuration. In this paper, we study the possibility of understanding the intention of runtime configuration options through their documents, even sometimes it is difficult for users to understand. Based on these studies, we classify the runtime configuration option’s intention into six categories. Accordingly, we design runtime Configuration Intention Classifier (CIC), a supervised approach based on CNN to classify the runtime configuration option’s intention according to its document. CIC integrates the features of runtime configuration names and descriptions according to different levels of granularity and predicts the intention of runtime configuration options accordingly. Extensive experiments show that our approach can achieve an accuracy of 85.6% and outperform nine comparative approaches by up to 16.6% over the dataset we customized.

Background: Pulmonary tuberculosis is a chronic infectious disease of the respiratory system. It is still one of the causes of death from a single infectious disease, but it has been stuck in the study of a single pathogen. Recent studies have shown that many diseases are related to the microbiota. We clarified the occurrence of tuberculosis and the correlation between drug resistance and respiratory flora. High-throughput 16S rRNA gene sequencing was used to characterize the respiratory microbiota composition of 30 tuberculosis (TB) patients and compared with 30 health (H) controls. According to their Gene Xpert results, 30 pulmonary tuberculosis patients were divided into 12 persons in the sensitive group (DS0) and 18 persons in the drug-resistant group (DR0). The flora of the two were compared with the H group. Results: The data generated by sequencing showed that Firmicutes, Proteus, Bacteroides, Actinomyces and Fusobacterium were the five main bacterial phyla detected, and they constituted more than 96% of the microbial community. The relative abundance of Fusobacterium, Haemophilus, Porphyromonas, Neisseria, TM7, Spirochetes, SR1, and tunica in the TB group was lower than that of the H group, and Granulicatella was higher than the H group. The PcoA diagrams of the two groups had obvious clustering differences. The Alpha diversity of the TB group is lower than that of the H group, and the Beta diversity is higher than that of the H group (PStreptococcus in the DS0 group was much higher than that in the DR0 group (PStreptococcus was significantly different between rifampicin-sensitive and drug-resistant patients.

Background Pulmonary tuberculosis is a chronic infectious disease of the respiratory system. It is still one of the leading causes of death from a single infectious disease, but it has been stuck in the study of a single pathogen. Recent studies have shown that many diseases are associated with disruption of the native microbiota. In this study we investigated the occurrence of tuberculosis and the correlation between drug resistance and respiratory flora. High-throughput 16 S rRNA gene sequencing was used to characterize the respiratory microbiota composition of 30 tuberculosis (TB) affected patients and compared with 30 healthy (H) controls. According to their Gene Xpert results, 30 pulmonary tuberculosis patients were divided into 12 persons in the drug-sensitive group (DS0) and 18 persons in the drug-resistant group (DR0). The microbial flora of the two were compared with the H group. Results The data generated by sequencing showed that Firmicutes, Proteus, Bacteroides, Actinomyces and Fusobacterium were the five main bacterial phyla detected, and they constituted more than 96% of the microbial community. The relative abundances of Fusobacterium, Haemophilus, Porphyromonas, Neisseria, TM7, Spirochetes, SR1, and Tenericutes in the TB group was lower than that of the H group, and Granulicatella was higher than the H group. The PcoA diagrams of the two groups had obvious clustering differences. The Alpha diversity of the TB group was lower than that of the H group, and the Beta diversity was higher than that of the H group (P Streptococcus in the DS0 group was significantly higher than that in the DR0 group (P Conclusion Pulmonary tuberculosis can cause disorders of the respiratory tract microbial flora, in which the relative abundance of Streptococcus was significantly different between rifampicin-sensitive and rifampicin-resistant patients.

Since the Chromosome-Centric Human Proteome Project (C-HPP) was launched in 2010, many techniques have been adopted for the discovery of missing proteins (MPs). Because of these efforts, only 1481 MPs remained as of July 2020; however, by relying only on technique optimization, researchers have reached a bottleneck in MP discovery. Protein expression is tissue- or cell-type-dependent. The tissues of the human testis and brain have been reported to harbor a large number of tissue-specific genes and proteins; however, few studies have been performed on human brain tissue or cells to identify MPs. Herein a metastatic cell line derived from brain cancer, D283 Med, was used to search for MPs. With a traditional and simple shotgun workflow to separate the peptides into 20 fractions, 12 MPs containing at least two unique non-nested peptides (amino acid length ≥9) were identified in this cell line with a protein false discovery rate of

In this research, we developed an efficient approach to prepare hyperbranched polymers at room temperature via phosphazene-base t-BuP2 catalyzed oxa-Michael addition polymerization from commercially available trifunctional hydroxyl and diacrylate monomers. The branching structure of the obtained polymers and the polymerization process were investigated by nuclear magnetic resonance (NMR) spectroscopy and triple-detection size-exclusion chromatography (TD-SEC) analysis. It was revealed that acrylic double bond terminated branched polymers with high molecular weights and high degrees of branching (Mw.MALLS > 2.8 × 105 g mol−1, DB ≥ 0.8) were produced by t-BuP2 catalyzed oxa-Michael addition polymerization of a trimethylolpropane (TMP) with a double molar 1,6-hexanediol diacrylate (HDDA) in DMF at room temperature, even at 0 °C. The study of the branching process showed that t-BuP2 catalyzed oxa-Michael addition branching polymerization is rapid, and that significant branched structures formed when the polymerization was performed at 3 min. Most importantly, the prepared branched polymers can be further post-functionalized via aza- or thio-Michael addition reactions, due to the polymers retaining the acrylic double bond functionality. This research provides a versatile and efficient method for the preparation of hyperbranched polymers from commercially available monomers, and it is feasible to prepare functional branched polymers for application in various fields.

Rotating equipment often fails due to faults in the rolling element bearings. The remaining useful life (RUL) prediction of the bearings plays a critical role in prognostics and decision-makers. In this study, attention mechanism is integrated into the internal of just another network (JANET) unit, and a new improved version of JANET unit, namely, just another attention network (JAAN), is firstly presented. Firstly, root mean squares (RMS) of the test-to-failure datasets are calculated to characterize the degradation behavior of the bearings. Then, the prediction model is constructed by stacking multiple JAAN units to estimate the RUL values of rolling element bearings by existing RMS values. Extensive experiments on PRONOSTIA dataset are carried out to validate the superiority of the presented approach. The experiment results show that the proposed JAAN achieves good prediction results than other advanced technologies.

The color of light affects the reproductive performance of poultry, but it is not clear what efficient illumination strategy could be adopted to improve the reproductive performance of Zi-goose. Red light can increase the average weekly egg production rate, egg production, and qualified production. It can increase the serum GnRH level and decrease the serum PRL, MT, and T4 levels. In our study, red light for 12 h increased the average weekly laying rate, average qualified egg production, and hatching rate of Zi-goose eggs, and increased the serum levels of FSH, LH, P4, E2, MT, T3, and T4. Blue light at 14 h improved the average weekly egg production rate, average egg production, and average qualified egg production, and reduce serum PRL and MT levels to ensure the improvement of reproductive performance of goose. A total of 705,714 overlapping group sequences, 471,145 transcript sequences, and 268,609 single gene sequences were obtained from 18 sequencing samples, with a total length of 323.04, 668.53, and 247.88 M, respectively. About 176,416 unigenes were annotated successfully in six databases, accounting for 65.68% of the total unigenes obtained. 2,106, 2,142, and 8,892 unigenes were identified in the hypothalamus, pituitary gland, and ovary of the birds respectively, with different expressions of light regulation. The hypothalamus, ovary, and pituitary were involved in 279, 327, and 275 KEGG (Kyoto Encyclopedia of Genes and Genomes) metabolic pathways in response to light, respectively. Through further significance analysis and differential discovery rate control, a total of five metabolic pathways were obtained which were closely related to the reproductive hormones of goose. Ten candidate genes related to the reproductive performance of goslings were selected according to the identification results of differentially expressed genes of goslings under red light and white light conditions and the genes involved in metabolic pathways significantly related to the reproductive hormones of goslings. The expression levels of GnRh-1 in the hypothalamus, GnRH-R, FSHβ and LHβ in the pituitary gland, and FSH-R and LH-R candidate genes in the ovary were higher under the 12 h red light treatment than white light. However, the expression levels of VIP, PRL, and PRL-R candidate genes in the hypothalamus, pituitary and ovary were lower under 12 h red light than under 12 h white light.

Alternative open reading frames (AltORFs) are unannotated sequences in genome that encode novel peptides or proteins named alternative proteins (AltProts). Although ribosome profiling and bioinformatics predict a large number of AltProts, mass spectrometry (MS) as the only direct way of identification, is hampered by the short lengths and relative low abundance of AltProts. There is an urgent need for improvement of MS methodologies for AltProt identification. Here we report an approach based on size-exclusion chromatography (SEC) for simultaneous enrichment and fractionation of AltProts from complex proteome. This method greatly simplifies the variance of AltProts discovery by enriching small proteins smaller than 30 kDa. In a systematic comparison between ten methods, the approach we reported enabled discovery of more AltProts with overall higher intensities, with less cost of time and effort compared to other workflows. We applied this approach to identify 89 novel AltProts from mouse liver, 39 of which were differentially expressed between embryonic and adult mice. During embryonic development, the up-regulated AltProts were mainly involved in biological pathways on RNA splicing and processing, whereas the AltProts involved in metabolisms were more active in adult livers. Our study not only provides an effective approach for identifying AltProts, but also novel AltProts that are potentially important in developmental biology.

Small open reading frames (sORFs) are an important class of genes with less than 100 codons. They were historically annotated as noncoding or even junk sequences. In recent years, accumulating evidence suggests that sORFs could encode a considerable number of polypeptides, many of which play important roles in both physiology and disease pathology. However, it has been technically challenging to directly detect sORF-encoded peptides (SEPs). Here, we discuss the latest advances in methodologies for identifying SEPs with mass spectrometry, as well as the progress on functional studies of SEPs.

The amino acid response (AAR) and unfolded protein response (UPR) pathways converge on eIF2α phosphorylation, which is catalyzed by Gcn2 and Perk, respectively, under different stresses. This close interconnection makes it difficult to specify different functions of AAR and UPR. Here, we generated a zebrafish model in which loss of threonyl-tRNA synthetase (Tars) induces angiogenesis dependent on Tars aminoacylation activity. Comparative transcriptome analysis of the tars-mutant and wild-type embryos with/without Gcn2- or Perk-inhibition reveals that only Gcn2-mediated AAR is activated in the tars-mutants, whereas Perk functions predominantly in normal development. Mechanistic analysis shows that, while a considerable amount of eIF2α is normally phosphorylated by Perk, the loss of Tars causes an accumulation of uncharged tRNAThr, which in turn activates Gcn2, leading to phosphorylation of an extra amount of eIF2α. The partial switchover of kinases for eIF2α largely overwhelms the functions of Perk in normal development. Interestingly, although inhibition of Gcn2 and Perk in this stress condition both can reduce the eIF2α phosphorylation levels, their functional consequences in the regulation of target genes and in the rescue of the angiogenic phenotypes are dramatically different. Indeed, genetic and pharmacological manipulations of these pathways validate that the Gcn2-mediated AAR, but not the Perk-mediated UPR, is required for tars-deficiency induced angiogenesis. Thus, the interconnected AAR and UPR pathways differentially regulate angiogenesis through selective functions and mutual competitions, reflecting the specificity and efficiency of multiple stress response pathways that evolve integrally to enable an organism to sense/respond precisely to various types of stresses.

Immune and targeted therapy are becoming the first-line treatment for renal cell carcinoma (RCC). However, therapeutic outcomes are limited due to the low efficiency and side effect. Here, it is found that helicenes are able to exhibit an anticancer capability through changing the molecular structure from planar to nonplanar. Furthermore, the cytotoxicity in vitro and cancer inhibition ability of nonplanar helicenes increase with its aromatic rings' number. It is further demonstrated that benzo[4]helicenium shows the specific killing efficiency against the RCC cancer as compared to normal kidney cells. This is majorly originated from a more selective damage of benzo[4]helicenium for mitochondria and DNA in RCC cancer cells, not the normal kidney. The selective killing ability of benzo[4]helicenium makes it have potential to be used as a targeted drug for the precise treatment of RCC.

Remanufacturing repair has been applied as a promising technology to extend the fatigue life of damaged components. For the compressor blade with shallow surface crack, crack can be directly repaired by crack arrest and healing technology. However, for the blade with macrosurface crack, a surface notch will be generated by crack grinding process and then repaired by laser cladding technology. Therefore, there are essential differences in the remanufacturability evaluation methods for blade with shallow cracks or macrocracks. In this study, the remanufacturability evaluation methods that can be suitable for the blade with any depth surface crack are studied. Firstly, remanufacturability evaluation for shallow crack is introduced based on fracture mechanics. Secondly, remanufacturability evaluation based on surface notch is established for the blade with macrocrack. It consists of preliminary remanufacturability evaluation, remanufacturability evaluation based on residual fatigue life and remanufacturability evaluation based on fatigue damage. Finally, combined with the remanufacturability evaluation for shallow crack and macrocrack, all-crack remanufacturability evaluation is proposed that suitable for the blade with any depth surface cracks. With the assistance of all-crack remanufacturability evaluation, the potential fatigue performance of cracked blades can be reused furthest and reduce the waste of resources as much as possible.

MHC-I peptides are a group of important immunopeptides presented by major histocompatibility complex (MHC) on the cell surface for immune recognition. The majority of reported MHC-I peptides are derived from protein coding sequences, and noncanonical peptides translated from small open reading frames (sORF) are largely unknown due to the lack of accurate and sensitive detection methods. Herein we report an efficient approach that implements complementary bioinformatic strategies to improve the identification of noncanonical MHC-I peptides. In a database search strategy, noncanonical immunopeptides mapping was optimized by combining three complementary pipelines to construct predicted sORF databases from Ribo-seq data. In a de novo peptide sequencing strategy, MS data search results were filtered against sORF databases to pin down additional noncanonical immunopeptides. In total, 308 noncanonical immunopeptides were identified from two tumor cell lines with selected ones vigorously validated. Our approach is a handy solution to identify noncanonical MHC peptides with Ribo-seq and MS data. Meanwhile, the novel noncanonical immunopeptides identified with this method could shed insights on fundamental immunology as well as cancer immunotherapies.

Configuration error injection testing (CEIT) could systematically evaluate software reliability and diagnosability to runtime configuration errors. This paper explores the challenges and opportunities of applying CEIT technique. We build an extensible, highly-modularized CEIT framework named CeitInspector to experiment with various CEIT techniques. Using CeitInspector, we quantitatively measure the effectiveness and efficiency of CEIT using six mature and widely-used server applications. During this process, we find a fair number of test cases are left unstudied by the prior research work. The injected configuration errors in these cases often indicate latent misconfigurations, which might be ticking time bombs in the system and lead to severe damage. We conduct an in-depth study regarding these cases to reveal the root causes, and explore possible remedies. Finally, we come up with actionable suggestions guided by our study to improve the effectiveness and efficiency of the existing CEIT techniques.

Identifying more missing proteins (MPs) is an important mission of C-HPP. With the number of identified MPs being attenuated year by year (2,949 to 2,129 MPs from 2016 to 2019), we have realized that the difficulty of exploring the remaining MPs is a challenge in technique. Herein, we propose a comprehensive strategy to effectively enrich, separate, and identify proteins with low molecular weights, aiming at the discovery of MPs. Basically, a protein extract from human placenta was passed through a C18 SPE column, and the bound proteins that were eluted were further separated with an SDS-PAGE gel or a 50 kDa cutoff filter. The separated proteins were subjected to trypsin digestion, and the MS/MS signals were searched against data sets with two different digestion modes (full-trypsin and semitrypsin). The strategy was adopted, resulting in the identification of 4 MPs with 8 unique peptides (≥2 non-nested unique peptides with ≥9 amino acids). Importantly, the identification of 6 out of 8 of the unique peptides derived from the MPs was further supported by parallel reaction monitoring, which confirmed the identification of 3 MPs from human placenta tissues (Q6NT89: TMF-regulated nuclear protein 1; A0A183: late cornified envelope protein 6A; and Q6UWQ7: insulin growth factor-like family member 2, mapped to chromosomes 1, 1, and 19, respectively). The three proteins ranged in length from 80 aa to 227 aa. The study not only establishes a feasible strategy for analyzing proteins with low molecular weights but also fills a small part of a large gap in the list of MPs. The data obtained in this study are available via ProteomeXchange (PXD014083) and PeptideAtlas (PASS01389).

The assembly precision of mechanical products is closely related to the morphology of the mating surface. In order to predict the assembly accuracy of high precision mechanical products efficiently, a calculation method of assembly deviation based on the real mating status is proposed. Firstly, the wavelet transform is used to decompose and reconstruct the mating surface morphology. Secondly, the two basic principles of the contact points of the mating surface are analyzed, and the virtual assembly model based on difference surface is established. Finally, the centroid-driven algorithm is proposed to calculate the real mating status, and the assembly deviation based on the mating status is characterized by small displacement torsors (SDT). By comparing the results of theoretical calculation and numerical analysis, the contact point position obtained by the two methods is almost consistent and the calculation error of assembly deviation is 6.83%. In addition, the centroid-driven algorithm has greatly improved the efficiency of assembly deviation estimation. In the assembly process of high-precision mechanical system, the content of this article can realize the accurate prediction of assembly deviation.

Bisecting N-acetylglucosamine (GlcNAc), a GlcNAc linked to the core β-mannose residue via a β1,4 linkage, is a special type of N-glycosylated modification that has been reported to be involved in various biological processes, such as cell adhesion and fetal development. This N-glycan structure was found to be abundant in human trophoblasts; it was postulated to be resistant to natural killer cell-mediated cytotoxicity, enabling a mother to nourish a fetus without rejection. In this study, we hypothesized that the human amniotic membrane, which serves as the last barrier for the fetus, may also express bisected-type glycans. To test this hypothesis, glycomic analysis of the human amniotic membrane was performed, and bisected N-glycans were detected. Further, our proteomic data, which has been previously employed to explore human missing proteins, were analyzed and the presence of bisecting GlcNAc peptides was confirmed. A total of 41 glycoproteins with 43 glycopeptides were found to possess a bisecting GlcNAc, and 25 of these glycoproteins were reported to exhibit this type of modification for the first time. These results provide insights for implementing bisecting GlcNAc modification in the human amniotic membrane, and can be beneficial to functional studies on glycoproteins with bisecting GlcNAc modifications and functional studies on immune suppression in human placenta.

Background Heterogeneity of leukemia‐initiating cells (LICs) is a major obstacle in acute myeloid leukemia (AML) therapy. Accumulated evidence indicates that the coexistence of multiple types of LICs with different pathogenicity in the same individual is a common feature in AML. However, the functional heterogeneity including the drug response of coexistent LICs remains unclear. Therefore, this study aimed to clarify the intra‐heterogeneity in LICs that can help predict leukemia behavior and develop more effective treatments. Methods Spleen cells from the primary Setd2−/− ‐AML mouse were transplanted into C57BL/6 recipient mice to generate a transplantable model. Flow cytometry was used to analyze the immunophenotype of the leukemic mice. Whole‐genome sequencing was conducted to detect secondary hits responsible for leukemia transformation. A serial transplantation assay was used to determine the self‐renewal potential of Setd2−/− ‐AML cells. A limiting‐dilution assay was performed to identify the LIC frequency in different subsets of leukemia cells. Bulk and single‐cell RNA sequencing were performed to analyze the transcriptional heterogeneity of LICs. Small molecular inhibitor screening and in vivo drug treatment were employed to clarify the difference in drug response between the different subsets of LICs. Results In this study, we observed an aged Setd2 −/− mouse developing AML with co‐mutation of Nras G12S and Braf K520E. Further investigation identified two types of LICs residing in the c‐Kit+B220+Mac‐1− and c‐Kit+B220+Mac‐1+ subsets, respectively. In vivo transplantation assay disclosed the heterogeneity in differentiation between the coexistent LICs. Besides, an intrinsic doxorubicin‐resistant transcriptional signature was uncovered in c‐Kit+B220+Mac‐1+ cells. Indeed, doxorubicin plus cytarabine (DA), the standard chemotherapeutic regimen used in AML treatment, could specifically kill c‐Kit+B220+Mac‐1− cells, but it hardly affected c‐Kit+B220+Mac‐1+ cells. Transcriptome analysis unveiled a higher activation of RAS downstream signaling pathways in c‐Kit+B220+Mac‐1+ cells than in c‐Kit+B220+Mac‐1− cells. Combined treatment with DA and RAS pathway inhibitors killed both c‐Kit+B220+Mac‐1− and c‐Kit+B220+Mac‐1+ cells and attenuated disease progression. Conclusions This study identified two cell subsets enriched for LICs in murine Setd2−/− ‐AML and disclosed the transcriptional and functional heterogeneity of LICs, revealing that the coexistence of different types of LICs in this model brings about diverse drug response., Transcriptional and functional heterogeneity of LICs in murine Setd2−/−‐AML was explored. Coexistence of two different types of LICs in this model brings about diverse chemo‐response. Combined treatment with DA and RAS pathway inhibitors could kill both kinds of LICs and attenuate the disease progression. These findings may advance our understanding of the intra‐heterogeneity of LICs and help us to develop more efficient treatments.

With the explosive growth of the electric vehicle market, the recycling work of retired lithium-ion-battery packs, modules and cells is facing great challenges. Dismantling process is the primary step of the electronic waste recycling. In order to achieve rapid, efficient and safe disassembly of battery packs, and improve resource utilization efficiency, reduce environmental pollution, it is necessary to set battery pack disassembly production line. Based on the above targets, four optimization objectives are set, which are idle time, safety factor, disassembly cost and number of workstations. The solving part applies five heuristic algorithms, which can not only expand the solution range, but also discuss the performance of these algorithms. By comparing the value of objective functions, fitness and other indicators, NSGA-II is considered to have better convergence, and the optimal disassembly scheme is given.

Industrial machinery is developing in the direction of large-scale, automation, and high precision, which brings novel troubles to mechanical equipment management and maintenance. Intelligent diagnosis of mechanical running state based on vibration signals is becoming increasingly important, and it is still a great challenge at pattern recognition. As one of the indispensable components in mechanical equipment, planetary gearboxes are widely used in wind power, aerospace, and heavy industry. However, the problem of automatically maximizing the accuracy of planetary gearbox under different working conditions has not been solved. Therefore, an intelligent diagnosis method for planetary wheel bearing based on constrained independent component analysis (CICA) and stacked sparse autoencoder (SSAE) is presented in this research. Firstly, the fault signal with obvious time-domain characteristics is extracted by constrained independent component analysis (CICA), and the fault signals and noise is separated. Then, calculating the correlation kurtosis value of the time domain signals at different iteration periods as the eigenvalue to obtain the training samples and the test samples. The parameters of the network layer, the number of hidden nodes and learning rate are determined to build the model of SSAE. In the end, the training samples are input into the model for training and the whole network is fine-tuned. The advantages and disadvantages of the model are verified by the test samples. The intelligent classification and diagnosis of the mechanical running state are completed. Experiments analysis with real datasets of planetary wheel bearing show that the proposed method can achieve higher accuracy and robustness for fault classification compared with other data-driven methods. The application of this method in other major machinery industry also has bright prospects.

SummarySystem-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.

It is acknowledged that the bisecting N-acetylglucosamine (GlcNAc) structure, a GlcNAc linked to the core β-mannose residue via a β1,4 linkage, represents a special type of N-glycosylated modification and has been reported to be involved in various biological processes, such as cell adhesion and fetal development. Clark et al. has found that the majority of N-glycans in human trophoblasts bearing a bisecting GlcNAc. This type of glycan has been reported to help trophoblasts get resistant to natural killer (NK) cell-mediated cytotoxicity, and this would provide a possible explanation for the question how could the mother nourish a fetus within herself without rejection. Herein, we hypothesized that human amniotic membrane which is the last barrier for the fetus may also express bisecting type glycans to protect the fetus. To test this hypothesis, glycomic analysis of human amniotic membrane was performed, and the bisecting N-glycans with high abundance were detected. In addition, we re-analyzed our proteomic data with high fractionation and amino acid sequence coverage from human amniotic membrane, which had been released for the exploration of human missing proteins. The presence of bisecting GlcNAc peptides was revealed and confirmed. A total of 41 glycoproteins with 43 glycopeptides were found to possess a bisecting GlcNAc, 25 of which are for the first time to be reported to have this type of modification. These results provide the profiling of bisecting GlcNAc modification in human amniotic membrane and benefit to the function studies of glycoproteins with bisecting GlcNAc modification and the function studies in immune suppression of human placenta. The mass spectrometry placenta data are available via ProteomeXchange (PXD010630).

Analysis and prediction of power consumption law is the basis of power grid planning and construction, and is also an effective guide for energy demand side management. With the rapid development of economy and the complex change of industrial structure in recent years, the internal structure of power demand is changing to some extent. Therefore, a short-term forecasting method of regional electricity consumption considering the related factors is proposed. Based on the analysis results, a short-term prediction model of regional electricity consumption considering the related factors is established, and the short-term prediction is realized by the calculation of the model. Through the example analysis, it is verified that the forecasting deviation of the short-term forecasting method is low and meets the basic requirements of electric quantity forecasting.

A surface notch will be produced in crack grinding process of cracked blade, and fatigue life of surface notch is a critical measure to assess its remanufacturability. In this paper, a total fatigue life separation model based on surface notch is studied, which is defined as the sum of crack initiation life and crack propagation life. Tensile fatigue experiments were performed on surface notched plate specimens. At a given notch depth, there is a negative correlation between the secondary crack density and the notch width. Combined with Neuber's rule and elastic–plastic finite element results, a residual thickness correction coefficient S e is proposed to reflect the effect of finite thickness on local strain. Depending on simulation results, it is found that Neuber's rule underestimates the notch-root strains of surface notch, which is contrary to the current conclusions. Crack initiation life is estimated by modifying Morrow method with the proposed S e . The initial crack size a 0 of surface notch is qualified by equivalent initial flaw size (EIFS) modified by fatigue strength calculated by Neuber approach. Crack initiation life is estimated by Labg equation with the improved a 0 . The proposed model is verified by fatigue experiment results with a prediction accuracy falling into the scatter band of factor 1.5. This study enriches the current notch fatigue analysis, which can provide reference suggestions by the model for crack grinding design in remanufacturing pre-treatment process.

Following an enormous effort by the global scientific community coordinated by HUPO's Human Proteome Project, the number of proteins without high-quality MS or other evidence (colloquially termed missing proteins) has substantially decreased; however, some highly hydrophobic MPs remain on the list. We believe that efficient peptide separation is an approach that can be used to improve the identification of these hydrophobic MPs. We propose that peptides prepared from the membrane fractions of human cell lines and placental tissue can be well separated from hydrophilic peptides in organic solvents at high concentrations due to the precipitation of hydrophilic peptides with lower solubility. Using a combination strategy of peptide separation in 98% acetonitrile prior to traditional 2D reverse-phase liquid chromatography, more hydrophobic peptides were detected in the supernatants of the organic solvent extractions than were found in the pellets. When this strategy was adopted, 30 MPs (≥2 non-nested unique peptides with ≥9 amino acids) with 114 unique peptides were identified at protein false discovery rate (FDR) < 1%, including 7, 12, and 13 MPs obtained from membrane preparations derived from K562, HeLa cells, and human placenta, respectively. Of the 30 MPs identified in this study, 19 were categorized as membrane proteins or extracellular matrix proteins. Furthermore, 20 were verified to possess two non-nested unique peptides through parallel reaction monitoring with the corresponding chemically synthesized peptides. The use of organic solvents at high concentrations was shown to be an efficient way to improve the exploration of hydrophobic MPs. The data obtained in this study are available via ProteomeXchange (PXD010630) and PeptideAtlas (PASS01218).

Puberty is initiated by increased pulsatile gonadotropin-releasing hormone (GnRH) release from the hypothalamus. Epigenetic repression is thought to play a crucial role in the initiation of puberty, although the existence of analogous changes in methylation patterns across species is unclear. We analysed mRNA expression of DNA methyltransferases (DNMTs) and methyl-binding proteins (MBPs) in goats and rats by quantitative real-time PCR (qRT-PCR). DNA methylation profiles of hypothalamic were determined at the pre-pubertal and pubertal stages by bisulphite sequencing. In this study, expression of DNMTs and MBPs mRNA showed different patterns in goats and rats. Global methylation variation was low in goats and rats, and the profile remained stable during puberty. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway analysis revealed the involvement of 62 pathways in puberty in goats and rats including reproduction, type I diabetes mellitus and GnRH signalling pathways and found that Edn3, PTPRN2 and GRID1 showed different methylation patterns during puberty in goats and rats and similar variation patterns for Edn3 and PTPRN2 were showed. These indicated that Edn3 and PTPRN2 would play a role in the timing of puberty. This study provides evidence of the epigenetic control of puberty.

Oxygen reduction reaction is the key process that determines the performances of fuel cells and metal-air batteries. Replacing highly expensive noble metal electrocatalysts with highly active non-noble metal electrocatalysts is important for the practical application of these technologies. We have designed and synthesized a core–shell-structured catalyst consisted of silver nanowire (AgNW) core and a nitrogen-doped graphene (NG) shell that shows enhanced catalyst activity for oxygen reduction reaction in alkaline media. The newly designed structure is expected to take advantage of both one-dimensional AgNWs for fast electron transfer and two-dimensional NG for efficient oxygen adsorption/activation. The electrochemical assessments demonstrate that the prepared AgNWs@NG shows superior activity toward oxygen reduction reaction than either NG or AgNWs alone, demonstrating the synergistic effect between Ag and NG. Furthermore, the prepared catalysts show perfect (nearly 100%) four-electron (4e−) pathway selectivity in alkaline aqueous solution, indicating the potential substitute for Pt-based catalysts in fuel cells and metal–air batteries.

The high-cycle fatigue (HCF) behavior is significantly affected by surface roughness, especially for high strength metal FV520B-I. However, with surface roughness effect, neither the fatigue property, nor the high-cycle fatigue life model about FV520B-I with surface roughness has been reported. In this paper, designed fatigue experiment using the specimen with different surface roughness is presented to study the effectiveness of the roughness to the fatigue. The observations of the fatigue crack initiation sites and the crack propagation. Then the high cycle fatigue behavior of FV520B-I affected by surface roughness is analyzed. The existing very-high-cycle fatigue life model is not well-fit for high-cycle fatigue model of FV520B-I. A NEW high-cycle fatigue life prediction model of FV520B-I, taking surface roughness as a main effective variable is proposed. The model is built up by a comprehensive use of experimental data and the traditional fatigue modeling theory. The new finding between the fatigue strength coefficient and stress amplitude, with surface roughness, is adopted, leading to a NEW modified life prediction model. Study on fatigue model of FV520B-I with surface roughness is a very beneficial effort in fatigue theory and fatigue engineering development.

The mission of the Chromosome-Centric Human Proteome Project (C-HPP) to discover missing proteins (MPs) has become increasingly difficult due to the remaining low-abundance, high-hydrophobicity, or low-molecular-weight MPs. We have reported two approaches to resolve these identification problems for the low-abundance and high-hydrophobicity MPs, respectively. In this study, to improve the identification of low-abundance MPs with high hydrophobicity, we combined two approaches and obtained MPs from several different cancer cell lines. Their membrane fractions were isolated by ultracentrifugation, and the low-abundance proteins were enriched at the protein level with the ProteoMiner kit. After that, the peptides from the enriched proteins were separated by high concentrations of organic solvents according to their hydrophobicity as the first dimension of separation at the peptide level, and the second and third dimensions of separation involved a high pH reversed-phase and an acid reversed-phase column, respectively. In total, 16 MPs (at least two non-nested unique peptides with ≥9 amino acids) with 61 unique peptides were identified from four human cancer cell lines, including 2, 8, 2, and 7 MPs from HeLa, HCT116, SNU-1, and HepG2 cells, respectively. Furthermore, all MPs were verified with two non-nested unique peptides through parallel reaction monitoring (PRM) by matching the peptides with their chemically synthesized peptides. Interestingly, two additional MPs were verified from the same cell line by PRM assay, although the two non-nested unique peptides with ≥9 amino acids for each MP were identified from different MS injections or cell lines by data-dependent acquisition (DDA). Thus, a total of 18 MPs were dug out in this study. The data are available via ProteomeXchange (PXD014058) and PeptideAtlas (PASS01388).

Feature extraction plays a crucial role in the rolling bearing fault diagnosis, which determines the results of the fault diagnosis largely. However, conventional fault diagnosis methods only use single channel signal for analysis, which may lead to missed or misjudged diagnostic results. This work presents an incipient fault feature extraction based on full vector complete ensemble empirical mode decomposition (FVCEEMD) to extract the fault feature of rolling bearing. Complete ensemble empirical mode decomposition (CEEMD) is introduced as a pretreatment method to decompose signals into a set of intrinsic mode function (IMFs). Parameter index for selecting sensitive IMF components is correlation coefficient and kurtosis. And hilbert transform is used to obtain corresponding envelope signals. The full vector spectrum is utilized to analyze the envelope signals to get fault characteristics of rolling bearing. The results have been verified that the presented method can effectively extract the incipient fault feature of rolling bearing, and it has broad application prospects in industry.

Rolling bearing is a vital part of the machinery, whose remaining useful life (RUL) estimation plays a critical role in ensuring the safety and maintenance decision-making. However, in most industrial applications, it is difficult to obtain run-to-failure data under complex operating conditions, which is inefficient for deep learning approaches. To solve the above problem, a new approach using transfer depth-wise separable convolution recurrent network (TDSCRN) for RUL estimation of bearing is presented. A novel prediction model so-called depth-wise separable convolution recurrent network (DSCRN) is designed and trained by the source-domain dataset. The parameters and model of DSCRN are transferred to the target-domain, and then TDSCRN is obtained for RUL estimation task. Two public run-to-failure datasets are used to validate the performance of the presented method. The results indicate that this framework can improve estimation accuracy and robustness in complex operating conditions.

Crack grinding process is the essential step in the remanufacturing pre-treatment for the compressor blade with fatigue crack. After crack grinding process, a notch will be generated on the surface of the blade. Stress concentration factor (SCF) of the surface notch is a basic parameter on remanufacturability assessment depending on fatigue behaviors. However, few equations can be employed directly to estimate SCF of surface notch in the current lecture. In the present study, stress concentration of surface notch with semi-elliptical sections on a plate with finite thickness and width has been investigated using finite element analysis. It was found that the depth and width of surface notch and the thickness of plate were the main factors that controlling the stress concentration. What is interesting in theoretical modeling is that SCF of surface notch with semi-elliptical sections with large thickness can be estimated by the simple modification of Inglis’s equation. Following, based on the modified Inglis’s equation, an empirical SCF equation of surface notch was proposed with the consideration of depth and width of the surface notch and the thickness. A reference value of SCF for the blade after crack grinding process can be provided using the equation.

This paper proposed a new friction mechanical model of joint interface to better describe the tangential stiffness softening. A new probability density function is obtained by analyzing the actual two-dimensional pressure distribution of bolted joint. Then, an improved tangential stiffness model and the corresponding extraction method of the model parameters based on FEA method was introduced, and the effectiveness of the model was verified by the designed slip test. Finally, this paper discussed the influence of various parameters on tangential stiffness, and explained the stiffness nonlinear softening from the evolution of sliding area. Compared with the existing model, the calculation accuracy is improved by 18.2%. The research content has a better application prospect in dynamic analysis of connection structures.

In our previous work, a parameter a, r, e, a, , Δ, , , , , , , , was proposed to describe fatigue damage caused by micro scratch, whose validity was verified by fracture mechanics. In this article, we summarize an attempt to check the applicability of the a, r, e, a, , Δ, , , , , , , , in the field of the classic S-N curve method. For the sake of objective verification, the experiment data used in this article are from our published work. A high cycle fatigue life model of TC17 based on micro scratches is established with the synthesis of the three-parameter model and Murakami equation modified by a, r, e, a, , Δ, , , , , , , , . Prediction results gave accuracy to mainly fall into the scatter band of factor 2. It can be suggested that a, r, e, a, , Δ, , , , , , , , is suitable for being used in both fracture mechanics and classic S-N curve method. Furthermore, the validity of a, r, e, a, , Δ, , , , , , , , in fatigue behavior analysis combined with current fatigue theories and materials is summarized. The measurement method of scratch depth and width suitable for a, r, e, a, , Δ, , , , , , , , is also introduced.

SIN3 transcription regulator family member A (SIN3A) is the central scaffold protein of the SIN3/HDAC (histone deacetylase) transcriptional repressor complex. We previously found that SIN3A participates in the mouse pre-implantation development by finetuning HDAC1 expression. However, it remains unresolved whether this functional significance of SIN3A is conserved in other mammals. The objective of this work was thus to characterise the expression profiles and the functional role of SIN3A in pre-implantation development using non-rodent animal models. RNA sequencing results show that a large amount of SIN3A mRNA is present in oocytes and early embryos before embryonic genome activation and a low amount thereafter, suggesting a maternal origin of SIN3A in all species examined. Interestingly, immunofluorescence data show that SIN3A protein level peaks at the 4-cell stage in pigs compared with the morula stage in cattle, suggesting a differential role of SIN3A among species. To explore the function of SIN3A in early embryonic development, we used a short interfering (si)RNA-mediated knockdown approach in porcine parthenogenetic activated (PA) embryos. Immunocytochemical analysis showed that SIN3A levels were diminished ∼80% compared with nonspecific siRNA (NC) injected control (n=3). To monitor the developmental potential of embryo depleted of SIN3A, we injected SIN3A-siRNA into MII stage oocytes, followed by parthenogenetic activation, and percent cleavage and blastocyst formation were recorded. We found that SIN3A knockdown (KD) did not affect the cleavage rate (NC vs. KD, 83.63±3.63% vs. 80.08±4.66%, n=5), but significantly reduced blastocyst rate compared with the NC group (NC vs. KD, 36.64±4.28% vs. 6.33±3.12%, n=5). Specifically, SIN3A depletion in early embryos causes developmental arrest at 2-cell stage in pigs but does not affect early embryonic development in bovines. In contrast with mouse data, SIN3A depletion results in only a slight decrease and even no difference in HDAC1 expression in porcine and bovine early embryos, respectively. In addition, HDAC1 knockdown does not cause 2-cell block but leads to a reduced blastocyst rate, suggesting that the effect of SIN3A depletion on porcine early embryos is independent of HDAC1. RNA-Seq analysis was used to compare the global transcript content between NC and KD 2-cell embryos. A total of 23 genes (14 upregulated and 9 downregulated) had undergone significant changes. Interestingly, cyclin B1 (CCNB1) ranked second among downregulated genes. To test whether knockdown of CCNB1 would display a similar phenotype in porcine early embryos, we injected CCNB1-siRNA into pronuclear stage. CCNB1 KD resulted in a similar phenotype as SIN3A depletion. Injection of exogenous CCNB1 mRNA into SIN3A-depleted embryos could partly rescue embryonic development. In conclusion, our results indicate SIN3A plays an essential role in porcine early embryonic development, probably involving the regulation of CCNB1 expression. This work was funded by National Natural Science Foundation of China, the Anhui Provincial Natural Science Foundation and China Postdoctoral Science Foundation.

Path planning for the mobile robot is to find a shortest obstacle free path from the starting position to the target position. Ant colony optimization method is frequently used to obtain the optimal path in the static known environment. But local minimum and slow convergence are the main problems of ant colony algorithm. This paper proposes a modified ant colony algorithm for path planning of the mobile robot in a known static environment. The modified ant colony algorithm can enlarge the searching range so that the local minimum problem can be weakened, while the algorithm can also converge quickly. And in the optimal path searching process, the turning factor is considered, too. The obtained optimal path has not only short distance, but also few big turning positions. Simulations are done to verify the proposed modified ant colony algorithm.

Research of material giga-cycle fatigue shows that fatigue failure is caused by a comprehensive effect of the competition between surface defect and internal inclusion, and the competition is more significant with high strength steal FV520B-I. A clear understanding of fatigue failure mechanism can improve the accuracy of the fatigue life prediction for FV520B-I. There is currently no available fatigue-life model that describes the competition mechanism of giga cycle behavior for FV520B-I. In this paper, ultrasonic fatigue experiment is presented, which revealed the existence of the competition during the giga-cycle process. The giga-fatigue life prediction models for FV520B-I are established with the consideration of surface defect and internal inclusion. Based on fracture mechanics, the surface roughness is correlated to surface defect. The competition analysis is carried out on the basics of fatigue strength to obtain the critical defect value. The critical defect value is the direct criterion in practical engineering and the primary factor of final failure is determined by comparing the actual defect with the critical value. Then the competitive giga-fatigue model for FV520B-I is established and the actual fatigue life is calculated by substituting the actual defect value into the corresponding fatigue life model.