Expression profiling and function analysis identified new genes regulating cumulus expansion and cumulus cell apoptosis in mouse oocytes.

In brief: Genes expressed in cumulus cells might be used as markers for competent oocytes/embryos. This study identified and validated a new group of cumulus expansion and/or apoptosis-regulating genes, which may be used for selection of quality oocytes/embryos. Abstract: Studies on the mechanisms behind cumulus expansion and cumulus cell (CC) apoptosis are essential for understanding the mechanisms for oocyte maturation. Genes expressed in CCs might be used as markers for competent oocytes and/or embryos. In this study, both in vitro (IVT) and in vivo (IVO) mouse oocyte models with significant difference in cumulus expansion and CC apoptosis were used to identify and validate new genes regulating cumulus expansion and CC apoptosis of mouse oocytes. We first performed mRNA sequencing and bioinformatic analysis using the IVT oocyte model to identify candidate genes. We then analyzed functions of the candidate genes by RNAi or gene overexpression to select the candidate cumulus expansion and CC apoptosis-regulating genes. Finally, we validated the cumulus expansion and CC apoptosis-regulating genes using the IVO oocyte model. The results showed that while Spp1, Sdc1, Ldlr, Ezr and Mmp2 promoted, Bmp2, Angpt2, Edn1, Itgb8, Cxcl10 and Agt inhibited cumulus expansion. Furthermore, Spp1, Sdc1 and Ldlr inhibited CC apoptosis. In conclusion, by using both IVT and IVO oocyte models, we have identified and validated a new group of cumulus expansion and/or apoptosis-regulating genes, which may be used for selection of quality oocytes/embryos and for elucidating the molecular mechanisms behind oocyte maturation.

The degree of population aging and carbon emissions: Analysis of mediation effect and multi-scenario simulation.

The continuous deepening of aging has posed new challenges for global sustainable development. Measuring the impact of population aging on carbon emissions is crucial for the next stage of climate governance. However, the structural changes in social production and consumption make it difficult to evaluate the impact effects. Therefore, this study constructed a bidirectional fixed Space Durbin Model to explore the mediating pathway of aging's impact on carbon emissions. Furthermore, we have established high-precision prediction models to simulate the evolution trajectory of carbon emissions under multi-factor driving scenarios. The main findings are as follows: (1) The process of carbon emission reduction due to population aging has significant energy hindrance effect and industrial structure effect, while the process of carbon growth is constrained by the consumption enhancement effect, technology progress effect and labor participation effect. (2) The moderating effects of energy consumption and technological innovation on carbon emissions under the aging process are 10.74% and 10.24%, respectively, while the moderating effects of industrial structure and labor force participation are relatively weak. (3) The goodness of fit of the MNGM-ARIMA and MNGM-BPNN models is over 97%. Carbon emissions in the high aging regions show a decreasing trend in all scenarios except the energy consumption-driven scenario, while in the medium and low aging regions decrease slowly only in the R&D- and labor supply-driven scenarios. This study advocates developing heterogeneous emission reduction measures based on the degree of aging, accelerating supply side upgrading, and increasing the proportion of green consumption.

Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm. METHODS: The 130 datasets enrolled were randomly divided into a training set and a testing set in a 7:3 ratio. Clinical factors were included and radiomics features were extracted from pretreatment CT scans using pyradiomics-based software, and a pairwise naive Bayes (NB) model was developed. The performance of the model was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). To facilitate practical application, we attempted to construct an automated esophageal cancer diagnosis system based on trained models. RESULTS: To the follow-up date, 64 patients (49.23%) had experienced LR. Ten radiomics features and two clinical factors were selected for modeling. The model demonstrated good prediction performance, with area under the ROC curve of 0.903 (0.829-0.958) for the training cohort and 0.944 (0.849-1.000) for the testing cohort. The corresponding accuracies were 0.852 and 0.914, respectively. Calibration curves showed good agreement, and DCA curve confirmed the clinical validity of the model. The model accurately predicted LR in elderly patients, with a positive predictive value of 85.71% for the testing cohort. CONCLUSIONS: The pairwise NB model, based on pre-treatment enhanced chest CT-based radiomics and clinical factors, can accurately predict LR in elderly patients with ESCC. The esophageal cancer automated diagnostic system embedded with the pairwise NB model holds significant potential for application in clinical practice.

Mixotrophic denitrification of waste activated sludge fermentation liquid as an alternative carbon source for nitrogen removal: Reducing N2O emissions and costs.

Heterotrophic-sulfur autotrophic denitrification (HAD) has been proposed to be a prospective nitrogen removal process. In this work, the potential of fermentation liquid (FL) from waste-activated sludge (WAS) as the electron donor for denitrification in the HAD system was explored and compared with other conventional carbon sources. Results showed that when FL was used as a carbon source, over 99% of NO3--N was removed and its removal rate exceeded 14.00 mg N/g MLSS/h, which was significantly higher than that of methanol and propionic acid. The produced sulfate was below the limit value and the emission of N2O was low (1.38% of the NO3--N). Microbial community analysis showed that autotrophic denitrifiers were predominated in the HAD system, in which Thiobacillus (16.4%) was the dominant genus. The economic analysis showed the cost of the FL was 0.062 €/m3, which was 30% lower than that in the group dosed with methanol. Our results demonstrated the FL was a promising carbon source for the HAD system, which could reduce carbon emission and cost, and offer a creative approach for waste-activated sludge resource reuse.

The neural implausibility of the diffusion decision model doesn't matter for cognitive psychometrics, but the Ornstein-Uhlenbeck model is better.

In cognitive psychometrics, the parameters of cognitive models are used as measurements of the processes underlying observed behavior. In decision making, the diffusion decision model (DDM) is by far the most commonly used cognitive psychometric tool. One concern when using this model is that more recent theoretical accounts of decision-making place more emphasis on neural plausibility, and thus incorporate many assumptions not found in the DDM. One such model is the Ising Decision Maker (IDM), which builds from the assumption that two pools of neurons with self-excitation and mutual inhibition receive perceptual input from external excitatory fields. In this study, we investigate whether the lack of such mechanisms in the DDM compromises its ability to measure the processes it does purport to measure. We cross-fit the DDM and IDM, and find that the conclusions of DDM would be mostly consistent with those from an analysis using a more neurally plausible model. We also show that the Ornstein-Uhlenbeck Model (OUM) model, a variant of the DDM that includes the potential for leakage (or self-excitation), reaches similar conclusions to the DDM regarding the assumptions they share, while also sharing an interpretation with the IDM in terms of self-excitation (but not leakage). Since the OUM is relatively easy to fit to data, while being able to capture more neurally plausible mechanisms, we propose that it be considered an alternative cognitive psychometric tool to the DDM.

CwJAZ4/9 negatively regulates jasmonate-mediated biosynthesis of terpenoids through interacting with CwMYC2 and confers salt tolerance in Curcuma wenyujin.

Plant JASMONATE ZIM-DOMAIN (JAZ) genes play crucial roles in regulating the biosynthesis of specialized metabolites and stressful responses. However, understanding of JAZs controlling these biological processes lags due to numerous JAZ copies. Here, we found that two leaf-specific CwJAZ4/9 genes from Curcuma wenyujin are strongly induced by methyl-jasmonate (MeJA) and negatively correlated with terpenoid biosynthesis. Yeast two-hybrid, luciferase complementation imaging and in vitro pull-down assays confirmed that CwJAZ4/9 proteins interact with CwMYC2 to form the CwJAZ4/9-CwMYC2 regulatory cascade. Furthermore, transgenic hairy roots showed that CwJAZ4/9 acts as repressors of MeJA-induced terpenoid biosynthesis by inhibiting the terpenoid pathway and jasmonate response, thus reducing terpenoid accumulation. In addition, we revealed that CwJAZ4/9 decreases salt sensitivity and sustains the growth of hairy roots under salt stress by suppressing the salt-mediated jasmonate responses. Transcriptome analysis for MeJA-mediated transgenic hairy root lines further confirmed that CwJAZ4/9 negatively regulates the terpenoid pathway genes and massively alters the expression of genes related to salt stress signaling and responses, and crosstalks of multiple phytohormones. Altogether, our results establish a genetic framework to understand how CwJAZ4/9 inhibits terpenoid biosynthesis and confers salt tolerance, which provides a potential strategy for producing high-value pharmaceutical terpenoids and improving resistant C. wenyujin varieties by a genetic approach.

Production line balance problem identification and improvement based on decision tree: A case study of commercial air conditioner production line.

In the production of air conditioners, there are various issues such as complex requirements, redundant stations, excessive man-hours, and low production line balance rate. This paper aims to address these problems by analyzing the historical data of H Company's commercial air conditioner production line. The data is categorized into five aspects: station, working hours, standard working hours, labor capacity, and presence of bottleneck processes. To optimize and improve the second production line, this paper applies the production line balance management method based on data mining. It utilizes the decision tree model in data mining and incorporates lean production knowledge from industrial engineering. The goal is to identify crucial factors that affect the balance of the production line and address the issues caused by these factors. The aim is to reduce and eliminate redundant working hours and enhance the balance rate of the production line. By implementing the approach outlined in this paper, the bottleneck time of the second production line was reduced from 96.67 s to 74.6 s, and the production line balance rate increased from 68% to 85%.

Prediction of protein-ATP binding residues using multi-view feature learning via contextual-based co-attention network.

Accurately predicting protein-ATP binding residues is critical for protein function annotation and drug discovery. Computational methods dedicated to the prediction of binding residues based on protein sequence information have exhibited notable advancements in predictive accuracy. Nevertheless, these methods continue to grapple with several formidable challenges, including limited means of extracting more discriminative features and inadequate algorithms for integrating protein and residue information. To address the problems, we propose ATP-Deep, a novel protein-ATP binding residues predictor. ATP-Deep harnesses the capabilities of unsupervised pre-trained language models and incorporates domain-specific evolutionary context information from homologous sequences. It further refines the embedding at the residue level through integration with corresponding protein-level information and employs a contextual-based co-attention mechanism to adeptly fuse multiple sources of features. The performance evaluation results on the benchmark datasets reveal that ATP-Deep achieves an AUC of 0.954 and 0.951, respectively, surpassing the performance of the state-of-the-art model. These findings underscore the effectiveness of assimilating protein-level information and deploying a contextual-based co-attention mechanism grounded in context to bolster the prediction performance of protein-ATP binding residues.

Energy-efficient path planning for a multi-load automated guided vehicle executing multiple transport tasks in a manufacturing workshop environment.

Automated guided vehicles (AGVs) are typical intelligent logistics equipment, and path planning plays a significant role in the efficient use of AGVs. To better utilize multi-load AGVs and enhance the sustainability of the logistics process, an energy-efficient path planning model is formulated for a multi-load AGV executing multiple transport tasks in a manufacturing workshop environment, with transport distance and energy consumption (EC) serving as optimization objectives. Furthermore, a two-stage approach is proposed to solve it. In the first stage, the optimal energy-efficient paths connecting any two different nodes are acquired based on the workshop transport network expressed as a topological map. Afterward, the non-dominated sorting genetic algorithm-II is adopted in the second stage to determine the optimal execution sequence of pickup and delivery operations related to the assigned transport tasks, as well as to select the optimal path from the first stage's output information to execute each operation simultaneously. Moreover, the experimental study validates the energy-saving effect of the established model and the effectiveness of the solution method, and the factors affecting the multi-load AGV EC are analyzed.

Role and action mechanisms of miR-149 and miR-31 in regulating function of pig cumulus cells and oocytes.

Understanding the mechanisms for oocyte maturation and optimizing the protocols for in vitro maturation (IVM) are greatly important for improving developmental potential of IVM oocytes. The miRNAs expressed in cumulus cells (CCs) play important roles in oocyte maturation and may be used as markers for selection of competent oocytes/embryos. Although a recent study from our group identified several new CCs-expressed miRNAs that regulate cumulus expansion (CE) and CC apoptosis (CCA) in mouse oocytes, validation of these findings and further investigation of mechanisms of action in other model species was essential before wider applications. By using both in vitro and in vivo pig oocyte models with significant differences in CE, CCA and developmental potential, the present study validated that miR-149 and miR-31 improved CE and developmental potential while suppressing CCA of pig oocytes. We demonstrated that miR-149 and miR-31 targeted SMAD family member 6 (SMAD6) and transforming growth factor ß2 (TGFB2), respectively, in the transforming growth factor-ß (TGF-ß) signaling. Furthermore, both miR-149 and miR-31 increased CE and decreased CCA via activating SMAD family member 2 (SMAD2) and increasing the expression of SMAD2 and SMAD family member 4. In conclusion, the present results show that miR-149 and miR-31 improved CE and developmental potential while suppressing CCA of pig oocytes by activating the TGF-ß signaling, suggesting that they might be used as markers for pig oocyte quality.

Nupr1-mediated vascular smooth muscle cell phenotype transformation involved in methamphetamine induces pulmonary hypertension.

AIMS: Nuclear protein 1 (Nupr1) is a multifunctional stress-induced protein involved in the regulation of tumorigenesis, apoptosis, and autophagy. However, its role in pulmonary hypertension (PH) after METH exposure remains unexplored. In this study, we aimed to investigate whether METH can induce PH and describe the role and mechanism of Nupr1 in the development of PH. METHODS AND RESULTS: Mice were made to induce pulmonary hypertension (PH) upon chronic intermittent treatment with METH. Their right ventricular systolic pressure (RVSP) was measured to assess pulmonary artery pressure. Pulmonary artery morphometry was determined by H&E staining and Masson staining. Nupr1 expression and function were detected in human lungs, mice lungs exposed to METH, and cultured pulmonary arterial smooth muscle cells (PASMCs) with METH treatment. Our results showed that chronic intermittent METH treatment successfully induced PH in mice. Nupr1 expression was increased in the cultured PASMCs, pulmonary arterial media from METH-exposed mice, and METH-ingested human specimens compared with control. Elevated Nupr1 expression promoted PASMC phenotype change from contractile to synthetic, which triggered pulmonary artery remodeling and resulted in PH formation. Mechanistically, Nupr1 mediated the opening of store-operated calcium entry (SOCE) by activating the expression of STIM1, thereby promoting Ca2+ influx and inducing phenotypic conversion of PASMCs. CONCLUSIONS: Nupr1 activation could promote Ca2+ influx through STIM1-mediated SOCE opening, which promoted METH-induced pulmonary artery remodeling and led to PH formation. These results suggested that Nupr1 played an important role in METH-induced PH and might be a potential target for METH-related PH therapy.

Role of miRNAs in glucose metabolism of mouse cumulus cells†.

It is known that the oocyte has a limited capacity to acquire and metabolize glucose, and it must rely on cumulus cells (CCs) to take up glucose and produce pyruvate for use to produce ATP through oxidative phosphorylation. We therefore propose that miRNAs might regulate glucose metabolism (GM) in CCs and might be used as markers for oocyte quality assessment. Here, mouse CC models with impaired glycolysis or pentose phosphate pathway (PPP) were established, and miRNAs targeting the key enzymes in glycolysis/PPP were predicted using the miRNA target prediction databases. Expression of the predicted miRNAs was compared between CCs with normal and impaired glycolysis/PPP to identify candidate miRNAs. Function of the candidate miRNAs was validated by transfecting CCs or cumulus-oocyte-complexes (COCs) with miRNA inhibitors and observing effects on glucose metabolites of CCs and on competence of oocytes. The results validated that miR-23b-3p, let-7b-5p, 34b-5p and 145a-5p inhibited glycolysis, and miR-24-3p, 3078-3p,183-5p and 7001-5p inhibited PPP of CCs. Our observation using a more physiologically relevant model (intact cultured COCs) further validated the four glycolysis-targeting miRNAs we identified. Furthermore, miR-let-7b-5p, 34b-5p and 145a-5p may also inhibit PPP, as they decreased the production of glucose-6-phosphate. In conclusion, miRNAs play critical roles in GM of CCs and may be used as markers for oocyte quality assessment. Summary sentence:  We identified and validated eight new miRNAs that inhibit glycolysis and/or pentose phosphate pathways in cumulus cells (CCs) suggesting that miRNAs play critical roles in glucose metabolism of CCs and may be used for oocyte quality markers.

Energy optimisation for the combination of turning and drilling features using differential evolution.

Cutting parameter optimisation is an effective way to realise energy-efficient machining. In previous studies, the cutting parameters of machining features of turning, milling, grinding, drilling, hobbing, and threading were optimised to decrease energy consumed by machine tools, and considerable energy savings were achieved. However, the energy consumption (EC) for each feature was separately optimised without systematic consideration of the negative effects on the EC for other features. The total EC for all features together probably increases. Hence, the trade-off amongst the reductions of EC for each feature needs to be jointly optimised. In our study, the external turning and drilling features are selected as examples to be combined. As a key novel contribution, we propose the integrated dimensional and cutting parameter optimisation problem about minimising the EC of Machine Tools for the combination of Turning and Drilling features (EMT-TD). In terms of optimisation, differential evolution (DE) is adopted to minimise the EMT-TD. According to case studies, DE obtained the optimal solutions within a computation time of 1 second. The optimal solutions achieved savings of 5.41%, 10.85%, and 7.19% of EMT-TD and savings of 2.23%, 5.90%, and 2.73% of machining time for three typical cases, respectively.

Revealing the mechanism of quartz sand seeding in accelerating phosphorus recovery from anaerobic fermentation supernatant through vivianite crystallization.

The recovery of phosphorus (P) through vivianite crystallization offers a promising approach for resource utilization in wastewater treatment plants. However, this process encounters challenges in terms of small product size and low purity. The study aimed to assess the feasibility of using quartz sand as a seed material to enhance P recovery and vivianite crystal characteristics from anaerobic fermentation supernatant. Various factors, including seed dosage, seed size, Fe/P ratio, and pH, were systematically tested in batch experiments to assess their influence. Results demonstrated that the effect of seed enhancement on vivianite crystallization was more pronounced under higher seed dosages, smaller seed sizes, and lower pH or Fe/P ratio. The addition of seeds increased P recovery by 4.43% in the actual anaerobic fermentation supernatant and also augmented the average particle size of the recovered product from 19.57 to 39.28 µm. Moreover, introducing quartz sand as a seed material effectively reduced co-precipitation, leading to a notable 12.5% increase in the purity of the recovered vivianite compared to the non-seeded process. The formation of an ion adsorption layer on the surface of quartz sand facilitated crystal attachment and growth, significantly accelerating the vivianite crystallization rate and enhancing P recovery. The economic analysis focused on chemical costs further affirmed the economic viability of using quartz sand as a seed material for P recovery through vivianite crystallization, which provides valuable insights for future research and engineering applications.

Phosphorus recovery from synthetic anaerobic fermentation supernatant via vivianite crystallization: Coupling effects of various physicochemical process parameters.

Recovery of phosphorus (P) via vivianite crystallization is an effective strategy to recycle resources from the anaerobic fermentation supernatant. However, the presence of different components in the anaerobic fermentation supernatant (e.g., polysaccharides and proteins) might alter conditions for optimal growth of vivianite crystals, resulting in distinct vivianite characteristics. In the present study, the effect of different components on vivianite crystallization was explored. Then, the reaction parameters (pH, Fe/P, and stirring speed) for P recovery from synthetic anaerobic fermentation supernatant as vivianite were optimized using response surface methodology, and the relationship between crystal properties and supersaturation was elucidated using a thermodynamic equilibrium model. The optimized values for pH, Fe/P, and stirring speed were found to be 7.8, 1.74, and 500 rpm respectively, resulting in 90.54 % P recovery efficiency. Moreover, the variation of reaction parameters did not change the crystalline structure of the recovered vivianite but influenced its morphology, size, and purity. Thermodynamic analysis suggested the saturation index (SI) of vivianite increased with increasing pH and Fe/P ratio, leading to a facilitative effect on vivianite crystallization. However, when the SI was >11, homogenous nucleation occurred so that the nucleation rate was much higher than the crystal growth rate, causing a smaller crystal size. The findings presented herein will be highly valued for the future large-scale application of the vivianite crystallization process for wastewater treatment.

Metagenomic insight into the prevalence and driving forces of antibiotic resistance genes in the whole process of three full-scale wastewater treatment plants.

The spread of antibiotic resistance genes (ARGs) is an emerging global health concern, and wastewater treatment plants (WWTPs), as an essential carrier for the occurrence and transmission of ARGs, deserves more attention. Based on the Illumina NovaSeq high-throughput sequencing platform, this study conducted a metagenomic analysis of 18 samples from three full-scale WWTPs to explore the fate of ARGs in the whole process (influent, biochemical treatment, advanced treatment, and effluent) of wastewater treatment. Total 70 ARG subtypes were detected, among which multidrug, aminoglycoside, tetracycline, and macrolide ARGs were most abundant. The different treatment processes used for three WWTPs were capable of reducing ARG diversity, but did not significantly reduce ARG abundance. Compared to that by denitrification filters, the membrane bioreactor (MBR) process was advantageous in controlling the prevalence of multidrug ARGs in WWTPs. Linear discriminant analysis Effect Size (LEfSe) suggested g_Nitrospira, g_Curvibacter, and g_Mycobacterium as the key bacteria responsible for differential ARG prevalence among different WWTPs. Meanwhile, adeF, sul1, and mtrA were the persistent antibiotic resistance genes (PARGs) and played dominant roles in the prevalence of ARGs. Proteobacteria and Actinobacteria were the host bacteria of majority ARGs in WWTPs, while Pseudomonas and Nitrospira were the most crucial host bacteria influencing the dissemination of critical ARGs (e.g., adeF). In addition, microbial richness was determined to be the decisive factor affecting the diversity and abundance of ARGs in wastewater treatment processes. Overall, regulating the abundance of microorganisms and key host bacteria by selecting processes with microbial interception, such as MBR process, may be beneficial to control the prevalence of ARGs in WWTPs.

Combinational study with network pharmacology, molecular docking and preliminary experiments on exploring common mechanisms underlying the effects of weijing decoction on various pulmonary diseases.

Objective: 'Homotherapy for heteropathy' is a theory by which different diseases with similar pathogenesis can be treated with one Chinese formula. We aimed to explore the key components and core targets of Weijing decoction (WJD) in treating various lung diseases, namely, pneumonia, chronic obstructive pulmonary disease (COPD), acute lung injury (ALI), pulmonary fibrosis, pulmonary tuberculosis and non-small cell lung cancer (NSCLC), via network pharmacology, molecular docking and some experiments. Significance: This is the first study on the mechanism of WJD in treating various lung diseases by 'homotherapy for heteropathy'. This study is helpful for the transformation of TCM formula and development of new drugs. Methods: Active components and therapeutic targets of WJD were obtained via TCMSP and UniProt databases. Targets of the six pulmonary diseases were harvested from the GeneCards TTD, DisGeNet, UniProt and OMIM databases. Drug-disease intersection targets, corresponding Venn diagrams, herb-component-target networks and protein-protein interaction networks were established. Furthermore, GO biological function and KEGG enrichment analysis were completed. Moreover, the binding activity between main compounds and core targets was measured through molecular docking. Finally, the xenograft NSCLC mouse model was established. Immune responses were evaluated by flow cytometry and mRNA expression levels of critical targets were measured by real-time PCR. Results: JUN, CASP3 and PTGS2 were the most critical targets in six pulmonary diseases. The active compounds beta-sitosterol, tricin and stigmasterol stably bound to many active sites on target proteins. WJD had extensive pharmacological regulation, involving pathways related to cancer, inflammation, infection, hypoxia, immunity and so on. Conclusions: Effects of WJD against various lung diseases involve lots of compounds, targets and pathways. These findings will facilitate further research as well as clinical application of WJD.

KLF9 inhibits the proliferation, invasion, and migration of renal cell carcinoma through the SDF-1/CXCR4 axis.

Altered Krüppel-like factor 9 (KLF9) expression can regulate the progression of several cancers, including renal cell carcinoma (RCC). This study was conducted to investigate the role of KLF9 in the proliferation, invasion, and migration of RCC cells via regulation of stromal cell-derived factor-1 (SDF-1)/CXC chemokine receptor 4 (CXCR4). The expression patterns of KLF9, SDF-1, and CXCR4 in the experimental cell lines were determined by real-time quantitative polymerase chain reaction and Western blotting. After transfection of the KLF9 siRNA and KLF9 pcDNA, cell proliferation, invasion, and migration were evaluated by experiments including cell counting kit-8, colony formation, and Transwell assays. The binding of KLF9 to the SDF-1 promoter was analyzed by chromatin immunoprecipitation and dual-luciferase assay. The rescue experiment was performed using the recombinant SDF-1 protein and KLF9 pcDNA. KLF9 was downregulated in the RCC cells. KLF9 knockdown induced the proliferation, invasion, and migration of RCC cells, whereas KLF9 overexpression elicited the opposite roles. Mechanically, KLF9 bound to the SDF-1 promoter, repressed SDF-1 transcription, and reduced the SDF-1/CXCR4 expression levels. Activation of the SDF-1/CXCR4 axis attenuated the inhibitory role of KLF9 overexpression in RCC cell growth. Ordinarily, KLF9 suppressed the proliferation, invasion, and migration of RCC cells by repressing the SDF-1/CXCR4 signaling.

Facile preparation of a novel iminodisuccinate modified chitin and its excellent properties as a silver bioadsorbent and antibacterial agent.

A novel iminodisuccinate modified chitin (ICH) was prepared using crab shells via a one-step facile procedure. The ICH with grafting degree of 1.46 and deacetylation degree of 47.68 % possessed maximum adsorption capacity of 2572.41 mg/g for silver ions (Ag(I)).The ICH also exhibited good selectivity and reusability. The adsorption followed better with the Freundlich isotherm model, while fitted well with both the Pseudo-first-order and Pseudo-second-order kinetics models. The characteristical results showed that the excellent Ag(I) adsorption capability of ICH should be attributed to both looser porous microstructure as well as additional functional groups-grafting molecular. Moreover, the Ag-loaded ICH (ICH-Ag) showed remarkable antibacterial properties against six typical pathogenic bacteria strains (Escherichia coli, Pseudomonas aeruginosa, Enterobacter aerogenes, Salmonella typhimurium, Staphylococcus aureus, and Listeria monocytogenes), with the corresponding 90 % minimal inhibitory concentrations ranged 0.426-0.685 mg/mL. Further study on the silver release, microcell morphology, and metagenomic analysis suggested that many Ag nanoparticles were formed after the Ag(I) adsorption, and the antibacterial mechanisms of the ICH-Ag involved both cell membranes destruction and intracellular metabolism disturbing. This research presented a coupling solution of crab shell wastes treatment with chitin-based bioadsorbents preparation, metal removal and recovery, as well as antibacterial agent production.

Evolution of m6A-related genes in insects and the function of METTL3 in silkworm embryonic development.

N6-methyladenosine (m6A) plays a key role in many biological processes. However, the function and evolutionary relationship of m6A-related genes in insects remain largely unknown. Here we analysed the phylogeny of m6A-related genes among 207 insect species and found that m6A-related genes are evolutionarily conserved in insects. Subcellular localization experiments of m6A-related proteins in BmN cells confirmed that BmYTHDF3 was localized in the cytoplasm, BmMETTL3, BmMETTL14, and BmYTHDC were localized in the nucleus, and FL2D was localized to both the nucleus and cytoplasm. We examined the expression patterns of m6A-related genes during the embryonic development of Bombyx mori. To elucidate the function of BmMETTL3 during the embryonic stage, RNA sequencing was performed to measure changes in gene expression in silkworm eggs after BmMETTL3 knockdown, as well as in BmN cells overexpressing BmMETTL3. The global transcriptional pattern showed that knockdown of BmMETTL3 affected multiple cellular processes, including oxidoreductase activity, transcription regulator activity, and the cation binding. In addition, transcriptomic data revealed that many observed DEGs were associated with fundamental metabolic processes, including carbon metabolism, purine metabolism, amino acid biosynthesis, and the citrate cycle. Interestingly, we found that knockdown of BmMETTL3 significantly affected Wnt and Toll/Imd pathways in embryos. Taken together, these results suggest that BmMETTL3 plays an essential role in the embryonic development of B. mori, and deepen our understanding of the function of m6A-related genes in insects.