Dynamic Simulation of the Leaf Mass per Area (LMA) in Multilayer Crowns of Young Larix principis-rupprechtii.

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycles of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. During different growing periods, the LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (adjusted determination coefficient (Ra2) = 0.45, root mean square error (RMSE) = 13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the relative depth in the crown (RDINC) and date of the year (DOY) as independent variables was reliable in both the assessments (Ra2 = 0.68, RMSE = 10.25 g/m2) and the validation (absolute mean error (MAE) = 8.05 g/m2, fit index (FI) = 0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model.

The occurrence and contamination of optrA-positive methicillin-resistant Staphylococcus aureus from duck farms in Guangdong, China.

OBJECTIVES: Staphylococcus aureus, especially methicillin-resistant S. aureus (MRSA), is an important zoonotic microorganism that increasingly causes public health concern worldwide. The objective of this study was to determine the prevalence and transmission of S. aureus in duck farms and evaluate its antimicrobial resistance and genetic characteristics. METHODS: The samples associated with ducks, feeders, and the environment were collected on 14 duck farms from four areas in Guangdong, China, from 2020 to 2021. All isolates were subjected to antimicrobial susceptibility testing. A comprehensive epidemiological survey of S. aureus was conducted by S. aureus protein A typing and whole-genome sequencing. RESULTS: A total of 560 samples were collected. The prevalence rate of MRSA among ducks (8.1%, 11 of 135) was higher compared with that in environmental samples. OptrA-positive ST398-t034 MRSA were first detected from duck farms in China. A total of 79.3% (34 of 46) S. aureus isolates showed multidrug-resistant phenotypes. Notably, some isolates carried multidrug-resistant genes encoding macrolide-lincosamide-streptogramin B, pleuromutilin-pleuromutilin-streptogramin A, and oxazolidinone. Analysis of the virulence genes revealed that the MRSA isolates carried genes encoding gamma-hemolysin, enterotoxin, and leukocidin. ST9-t899 is a primary clonal lineage among duck- and environment-associated MRSA. Single-nucleotide polymorphism analysis showed the potential contamination relationship of optrA-positive ST2308 MRSA isolates carrying the gamma-hemolysin genes and the leukocidin virulence genes between airborne dust and sick ducks. CONCLUSION: The contamination of MRSA, especially optrA-positive MRSA, between food animals and the environment is a growing public health concern worldwide. Based on One Health principles, continuous surveillance of MRSA is urgently needed.

The construction of a biomass component interaction model based on research into the hydrothermal liquefaction of sewage sludge.

Sewage sludge (SS), a hazardous solid waste with a high water and pollutant content, should be disposed of correctly. Hydrothermal liquefaction (HTL) shows tremendous potential to treat organic matter with substantial water content like SS. In this paper, we examined the impact of key factors on the characteristics and yield of bio-oil during HTL of SS. We clarified the impacts of each component on the yield through model compounds based on that and constructed a component additivity model for forecasting the bio-oil yield from biomass with complex component composition. In the reactions of the model compounds, cellulose showed synergistic interaction with protein and alkali lignin in the bio-oil yield but lipids showed antagonistic effects with protein and alkaline lignin. The co-HTL results of these binary mixtures improved our model and further clarified the reaction mechanism of HTL of SS.

Application of CRISPR/Cas12a in the rapid detection of pathogens.

The combination of clustered regularly interspaced short palindromic repeats (CRISPR) and its associated Cas protein is an effective gene-editing instrument. Among them, the CRISPR-Cas12a system forms a DNA-cleavage-capable complex with crRNA and exerts its trans-cleavage activity by recognising the PAM site on the target pathogen's gene. After amplifying the pathogenic gene, display materials such as fluorescent probes are added to the detection system, along with the advantages of rapid detection and high sensitivity of the CRISPR system, so that pathogenic bacteria can be diagnosed with greater speed and precision. This article reviews the mechanism of CRISPR-Cas12a in rapid detection, as well as its progress in the rapid detection of pathogenic bacteria in conjunction with various molecular biology techniques, in order to provide a foundation for the future development of a more effective detection platform.

[Construction and precision analysis of individual tree biomass model of Larix olgensis considering random effects]. / 考虑随机效应的长白落叶松立木生物量模型构建及精度分析.

Accurate estimation of forest biomass in China is crucial for the study of carbon cycle and mechanisms underlying carbon storage in global terrestrial ecosystems. Based on the biomass data of 376 individuals of Larix olgensis in Heilongjiang Province, we used seemingly unrelated regression (SUR) method to build a univariate biomass SUR model with diameter at breast height as the independent variable and considering the random effect at the sampling site level. Then, a seemingly unrelated mixed effect (SURM) model was constructed. As the calculation of random effects of SURM model did not require the empirically measured values of all dependent variables, we analyzed the deviations from the following four types in detail: 1) SURM1, the random effect was calculated according to the measured biomass of stem, branch and foliage; 2) SURM2, the random effect was calculated according to the measured value of tree height (H); 3) SURM3, the random effect was calculated according to the measured crown length (CL); 4) SURM4, the random effect was calculated according to the measured values of H and CL. The results showed that the fitting effect of branch and foliage biomass models was improved significantly after considering the horizontal random effect of the sampling plot, with R2 being increased by more than 20%. The fitting effect of stem and root biomass models were improved slightly, with R2 being increased by 4.8% and 1.7%, respectively. When using five randomly selected trees to calculate the horizontal random effect of the sampling plot, the prediction performance of SURM model was better than that of SUR model and SURM model considering only fixed effects, especially SURM1 model (MAPE% of stem, branch, foliage and root was 10.4%, 29.7%, 32.1% and 19.5%, respectively). Except for SURM1 model, the deviation of SURM4 in predicting stem, branch, foliage and root biomass was smaller than that of SURM2 and SURM3 models. In actual prediction, although the prediction accuracy of SURM1 model was the highest, it needed to measure aboveground biomass of several trees, and the use cost was relatively high. Therefore, the SURM4 modelled on measured H and CL was recommended to predict the standing tree biomass of L. olgensis.

Naked-eye on-site detection platform for Pasteurella multocida based on the CRISPR-Cas12a system coupled with recombinase polymerase amplification.

Pasteurella multocida (P. multocida) is an important pathogenic bacterium that poses a serious threat to the development of the livestock economy and human health. Currently, the existing methods for P. multocida detection are time-consuming and require complex professional operations, limiting the application of field detection. In the study, we presented a single-pot naked-eye CRISPR-Cas12a platform (Cas12a-NEye) for the detection of P. multocida. The round tube cover allowed more Cas12a detection solution to be temporarily stored than the flat cap, enabling single-pot assays and avoiding aerosol contamination. The positive samples generated obvious red using naked eye using no excitation light and the negative samples generated blue. The limit of detection (LOD) was a single copy, without cross-reactivity with other closely related bacteria. Furthermore, we validated this platform using 16 P. multocida clinical lung samples and obtained consistent results with the real-time quantitative polymerase chain reaction (qPCR) method. The entire experimental process included rapid DNA extraction (<1 h) and Cas12a-NEye assay (25 min), which was accomplished within 1.5 h. Thus, this "sample-to-answer" platform has significant potential for P. multocida detection.

Coupling influences of organic components and temperature on nitrogen transformation and hydrochar characterization during hydrothermal carbonization of sewage sludge.

Nitrogen (N) in sewage sludge (SS) should be reduced if it is to be used to produce clean solid fuels. However, the N transformation during hydrothermal carbonization (HTC) of SS is not yet fully understood. Since the composition of SS is complex, it is wise to study a model compound, which should have typical functional groups of organic components. Hence, in this study, six model components (protein, lipid, cellulose, hemicellulose, humic acid, and lignin) representing the main organic components in SS were mixed with SS and treated at 150-270 °C for 1 h. The influence of the organic component and reaction temperature on hydrochar yield, hydrochar characterization, and N distribution in the products was investigated. Except for proteins and lipids, all the other components were found to contribute to the N content and aromatization of the hydrochar. Humus shows the best comprehensive performance in terms of both reducing the N content and increasing the aromaticity. The strongest effects of hemicellulose and cellulose on N retention in hydrochar are found to occur at 210 °C and 240 °C, respectively. The N retention caused by lignin is correlated with the Mannich reaction at 240 °C, while humus significantly promotes N transformation at 240 °C. For carbohydrates, lignin, and humus, the temperatures required for increasing the N content and aromaticity maintain a high degree of consistency. Although protein pulls down the energy recovery (ER) and yield of the hydrochar, observations indicate that it favors the carbonization process. This finding can be used for estimating the N content and quality of hydrochar and provides references for future research targeting the upgrading of hydrochar.

[Constructing biomass models for natural Quercus mongolica based on Bayesian seemingly unrelated regression]. / åŸºäºŽè´å¶æ–¯ä¼¼ä¹Žä¸ç›¸å ³å›žå½’æ–¹æ³•çš„å¤©ç„¶è’™å¤æ Žç”Ÿç‰©é‡æ¨¡åž‹æž„å»º.

In this study, the biomass models for natural Quercus mongolica in Heilongjiang Province were constructed based on the predictors of diameter at breast height (D) and tree height (H) by several methods including multivariate likelihood analysis and seemingly unrelated regression. The results showed that the H could significantly improve the stem biomass model, with the coefficient of determination (R2) being increased from 0.953 to 0.988 and the root mean square error (RMSE) being reduced by 14 kg, but it had no significant improvement for the biomass model of branch, foliage, and root. The error structures of both biomass model systems (only D and D-H) were multiplicative, indicating that the linear models after logarithmic transformation were more appropriate. The R2 for the biomass models of stem, branch, foliage and root were 0.953-0.988, 0.982-0.983, 0.916-0.917, and 0.951-0.952, while the RMSE were 13.42-27.03, 6.84-7.00, 1.95-1.97 and 9.71-9.84 kg. Compared with the feasible generalized least squares (FGLS) approach, Bayesian estimation had similar fitting performance and provided parameter estimates with different variations. The standard errors of parameters for FGLS were 0.054-0.211. There were similar variations (standard deviations of 0.055-0.221) for the two Bayesian estimation with no prior information (DMC and Gibbs1). The Gibbs sampler with a multivariate normal distribution with a mean vector of 0, variances of 1000 and covariances of 0 (Gibbs2) or the prior information from the historical researches summary for Quercus trees biomass models (Gibbs3) produced greater variation than those of FGLS, DMC, and Gibbs1 (stan-dard deviations were 0.080-0.278), while Gibbs sampler with the prior information obtained from own data (Gibbs4) provided the lower variations than others (standard deviations were 0.004-0.013). The Gibbs4 approach provided the narrowest 95% prediction interval and produced the smaller prediction biases, with the average absolute error percentage (MAPE) for stem, branch, foliage, root and total of the only-D biomass model being 19.8%, 24.7%, 24.6%, 29.0% and 13.1%, while MAPE for the corresponding components of D-H biomass model kept same except for stem and total decreased to 10.5% and 9.8%, which indicated that Gibbs4 could provide more accurate biomass predictions. Compared with classical statistics, accurate prior information made Bayesian seemingly unrelated regression an advantage in estimation stability and uncertainty reduction.

Prevalence of Livestock-Associated MRSA ST398 in a Swine Slaughterhouse in Guangzhou, China.

Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is an important zoonotic microorganism that is increasingly causing public health concern worldwide. The objective of this study was to determine the transmission and occurrence of MRSA in a slaughterhouse environment and evaluate its antimicrobial resistance and genetic characterization. In this study, we conducted a comprehensive epidemiological survey of S. aureus by spa typing and whole-genome sequencing (WGS) of samples obtained from the pork production chain, the environment, and community residents. To clarify the evolutionary relationships of MRSA sequence type (ST) 398 in this study and global isolates, 197 published whole-genome sequences data of MRSA ST398 strains were downloaded from the GenBank database and included in the phylogenetic analysis. A total of 585 porcine samples (snout and carcass swabs), 78 human nasal samples, and 136 environmental samples were collected. The MRSA isolates were detected at higher frequencies in samples from swine (15.0%) than carcasses (10.0%), slaughterhouse workers (8.0%), community residents (0%), and environment samples (5.9%). The spa typing results showed that t571 accounted for a higher proportion than other spa types. Closely related isolates from the samples of swine, slaughterhouse workers, carcasses, carrier vehicle, and surrounding fishpond water indicate that MRSA ST398 strains may spread among swine, humans, and the environment. MRSA ST398-t571 isolates were genetically different from global strains, except for two Korean isolates, which showed genetic closeness with it. In addition, a MRSA ST398 isolate recovered from an infected patient in Europe differed by only 31 SNPs from the airborne dust-associated strain isolated in this study, thereby suggesting potential transmission among different countries. Antimicrobial susceptibility testing results demonstrated that 99.0% (96/97) of MRSA and 95.1% (231/243) of methicillin-sensitive S. aureus (MSSA) showed multidrug-resistant (MDR) phenotypes. According to WGS analysis, the poxtA-carrying segment (IS431mec-optrA-IS1216-fexB-IS431mec) was reported in MRSA ST398 isolates for the first time. The coexistence of cfr and optrA in a plasmid was first detected in MRSA ST398. The potential transmission of MRSA among humans, animals, and the environment is a cause for concern. The emergence and transmission of LA-MRSA ST398 with high levels of resistance profiles highlight the urgent need for LA-MRSA surveillance.

[Analysis of carbon concentration and allometric growth model of carbon content for Larix olgensis]. / 长白落叶松含碳率分析及含碳量异速生长模型.

Forest carbon storage accounts for about 45% of terrestrial carbon storage. Accurate assessment of forest carbon storage is of great significance to the scientific management and planning of forests. Based on the data of 77 sampling Larix olgensis trees from Mengjiagang, Shangzhi Maoershan, Xiaojiu Forest Farm and Dongjing, Lin-kou Forestry Bureaus of Jiamusi, Heilongjiang Province from 2015 to 2018, we analyzed the partition of carbon content and variation of carbon concentration for five tree components (i.e., wood, bark, branch, leaf, and root). The mono-element and dual-element additive models of carbon content for each component of L. olgensis were deve-loped. The nonlinear seemly unrelated regression was used to estimate the parameters in the additive models, while the jackknife resampling technique was used to verify and evaluate the developed models. The results showed that the weighted mean carbon concentration of each component differed significantly, branches (49.3%) > bark (48.7%) > foliage (48.5%) > wood (48.2%) > root (47.1%). The aboveground and belowground carbon content accounted for about 80% and 20% of the total carbon content, respectively. The adjusted coefficient of determination (Ra2) of additive models of carbon content was greater than 0.89, the mean absolute error was less than 4.1 kg, and the mean absolute error percentage for most models was less than 30%. Adding tree height in the additive models of carbon content could significantly improve model fitting performance and predicting precision. The additive models of carbon content of total, aboveground, wood and bark were better than that of carbon content of branch, foliage, root and crown.

[Effects of mixing proportions on carbon storage and allocation in mixed plantation of Larix olgensis and Fraxinus mandshurica]. / æ··äº¤æ¯”ä¾‹å¯¹é•¿ç™½è½å¶æ¾å’Œæ°´æ›²æŸ³æ··äº¤æž—ç¢³å‚¨é‡åŠå ¶åˆ†é æ ¼å±€çš„å½±å“.

In this study, four types of mixed Larix olgensis and Fraxinus mandshurica plantations were selected according to the rows-mixing proportions (type Ⅰ: 5:3, type Ⅱ: 6:4, type Ⅲ: 5:5, type Ⅳ: 1:1). The see-mingly unrelated biomass models of L. olgensis and F. mandshurica were developed for obtaining biomass values, and the difference and composition of carbon storage in each forest layer and ecosystem were analyzed. The results showed that carbon storage of arbor layer in different stand types was 39.86-50.12 t·hm-2, the carbon storage of arbor layer inⅠ, Ⅱ and Ⅳ was significantly higher than that in type Ⅲ. The carbon storage of understory was 0.10-0.30 t·hm-2, with that in type Ⅱ being significantly higher than other types. Carbon storage of litter layer was 4.43-6.96 t·hm-2, with type Ⅱ and Ⅲ being significantly higher than those of the other types. In the soil layer, carbon storage was 34.97-54.66 t·hm-2. The carbon storage of soil layer in type Ⅱ was significantly greater than those in the other types. At the whole ecosystem level, carbon storage of type Ⅰ-Ⅳ was 90.43, 108.27, 85.83 and 89.92 t·hm-2, respectively. Type Ⅱ had significantly greater carbon storage than the other types. The arbor layer and soil layer were the major carbon pools in the ecosystem, which accounted for 43.3%-55.7% and 38.7%-50.5% of the total, respectively. Our results suggested that mixing by six rows of L. olgensis and four rows of F. mandshurica was better for future planting.

Metagenomic Insights into Chicken Gut Antibiotic Resistomes and Microbiomes.

The chicken gut microbiota, as a reservoir of antibiotic resistance genes (ARGs), poses a high risk to humans and animals worldwide. Yet a comprehensive exploration of the chicken gut antibiotic resistomes remains incomplete. In this study, we established the largest chicken gut resistance gene catalogue to date through metagenomic analysis of 629 chicken gut samples. We found significantly higher abundance of ARGs in the Chinese chicken gut than that in the Europe. tetX, mcr, and blaNDM, the genes resistant to antibiotics of last resort for human and animal health, were detected in the Chinese chicken gut. The abundance of ARGs was linearly correlated with that of mobile genetic elements (MGEs). The host-tracking analysis identified Escherichia, Enterococcus, Staphylococcus, Klebsiella, and Lactobacillus as the major ARG hosts. Especially, Lactobacillus, an intestinal probiotic, carried multiple drug resistance genes, and was proportional to ISLhe63, highlighting its potential risk in agricultural production processes. We first established a reference gene catalogue of chicken gut antibiotic resistomes. Our study helps to improve the knowledge and understanding of chicken antibiotic resistomes for knowledge-based sustainable chicken meat production. IMPORTANCE The prevalence of antibiotic resistance genes in the chicken gut environment poses a serious threat to human health; however, we lack a comprehensive exploration of antibiotic resistomes and microbiomes in the chicken gut environment. The results of this study demonstrate the diversity and abundance of antibiotic resistance genes and flora in the chicken gut environment and identify a variety of potential hosts carrying antibiotic resistance genes. Further analysis showed that mobile genetic elements were linearly correlated with antibiotic resistance genes abundance, implying that we should pay attention to the role played by mobile genetic elements in antibiotic resistance genes transmission. We established a reference genome of gut antibiotic resistance genes in chickens, which will help to rationalize the use of drugs in poultry farming.

Swine manure facilitates the spread of antibiotic resistome including tigecycline-resistant tet(X) variants to farm workers and receiving environment.

The prevalence of antibiotic resistance genes (ARGs) in livestock and poultry manure is a severe threat to human health. However, the comprehensive characterization of antibiotic resistance in swine, workers, and the receiving environment is still lacking in the actual breeding environment. Hence, the ARG profile and the potential bacterial hosts producing among swine manure (including sows, piglets, finishing pigs, and nursery pigs), worker feces, and the receiving environment (including sediment and vegetable soil) were comprehensively analyzed based on the metagenomic method. The results showed that swine manure exhibited the high levels of richness and diversity of ARGs. Inactivating tetracycline resistance genes such as tet(X), tet(X1), and tet(X10) were prevalent on swine farms. Workers and the environment were the primary recipients of ARGs, and shared ARGs accounted for at least 90% of their ARG abundances. Network analysis revealed that Escherichia, Acinetobacter, and Erysipelothrix were the most dominant genera co-occurring with specific shared ARGs. The abundance of coexisting ARGs in swine at different developmental stages accounted for 76.4% to 90.8% of the shared ARGs in swine, workers, and environmental samples. The Mantel test revealed that Firmicutes and Proteobacteria had a significant correlation with the ARG profiles. In addition, variation partitioning analysis (VPA) showed that the joint effects of mobile genetic elements (MGEs) and bacterial communities accounted for 24.7% of the resistome variation and played a significant role in the ARG profiles. These results improve our understanding of the transmission and persistence of ARGs in the actual breeding environment.

Co-hydrothermal carbonization of sewage sludge and polyvinyl chloride for the production of high-quality solid fuel with low nitrogen content.

Sewage sludge (SS) and polyvinyl chloride (PVC) are typical solid wastes. Their co-hydrothermal carbonization behavior was investigated in this study. The low-nitrogen solid fuel (0.94 wt%) with high heating value (9.84 MJ·Kg-1) was prepared through parameter optimization at 240 °C for 1.5 h under water loading amount of 0.84 g·cm-3. In an acidic environment, the stubborn protein in SS could be converted into free amino acids, which were generated by the decomposition of PVC under hydrothermal conditions. The stubborn N could be translated into easy-to-remove N, such as nitrile-N and inorganic N, and the dehydration reaction was evidently promoted. The acidic environment at high temperatures caused the dissolution of ash in SS and improved the combustion performance of hydrochar. FT-IR results showed that, with increased PVC loading proportion, -C=N- was converted into -C=O-. Co-hydrothermal carbonization could effectively improve the combustion performance of hydrochar. The addition of PVC could lead to the generation of increased volatile matter, fixed carbon, and unsaturated CC, and the combustion temperature range shifted to a high range. However, the generation of graphite-like carbon was caused by further increasing the PVC loading proportion, which hindered the improvement of its combustion performance. In the parameter optimization study, the increased water loading amount (from 0.54 g·cm-3 to 0.84 g·cm-3) had the most evident effect on the N content in the hydrochar (from 1.50 wt% to 0.94 wt%), which promoted the denitrification efficiency (from 60.11% to 75.00%) and the conversion of -C=N- components, and prevented further polymerization of solid products.

N6-Methyladenosine Modification of PTTG3P Contributes to Colorectal Cancer Proliferation via YAP1.

BACKGROUND: Long noncoding RNAs (lncRNAs) have emerged to have irreplaceable roles in the epigenetic regulation of cancer progression, but their biological functions in colorectal cancer (CRC) remain unclear. METHODS: LncRNA expression profiles in CRC tissue and their normal counterpart were explored. Through gain and loss of function approaches, the role of lncRNA PTTG3P was validated in relevant CRC cells and subcutaneous tumor model. The correlations of PTTG3P expression with clinical outcomes were assessed. RESULTS: PTTG3P was upregulated in CRC tissues and was closely correlated with unsatisfactory prognosis. PTTG3P facilitated glycolysis and proliferation, and the transcriptional regulator YAP1 was necessary for PTTG3P-induced proliferation. Mechanistically, the N6-methyladenosine (m6A) subunit METTL3 increased PTTG3P expression by influencing its stability, while insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) could identify PTTG3P m6A methylation status and bind to it. IGF2BP2 knockdown partly recovered PTTG3P expression induced by METTL3, indicating that METTL3-regulated PTTG3P expression depended on the presence of IGF2BP2. Finally, rescue assays validated the critical role of the METTL3/PTTG3P/YAP1 axis on CRC proliferation. CONCLUSIONS: PTTG3P is an independent prognostic biomarker for CRC. The METTL3/PTTG3P/YAP1 axis promotes the progression of CRC and is a promising treatment target.

SP1-Regulated Non-Coding RNA SNHG22 Promotes Ovarian Cancer Growth and Glycolysis.

OBJECTIVES: Long non-coding RNAs (lncRNAs) play a crucial part in cancer progression. However, in epithelial ovarian carcinoma (EOC), the role of SNHG22 needs to be further explained. METHODS: Quantitative real-time PCR was used to detect the expression of SNHG22. EOC cells were stably transfected with lentivirus approach and cell proliferation, glycolysis and cell apoptosis, as well as tumorigenesis in animal were performed to assess the effects of SNHG22 in EOC. Chromatin immunoprecipitation (ChIP) and luciferase reporter assay were conducted to confirm the relationship between SP1 and SNHG22. RESULTS: Higher expressed SNHG22 was associated with a poor prognosis in EOC tissues. SNHG22 facilitated glycolysis and proliferation. Mechanistically, LDHA deficiency and glycolysis inhibitor (2-DG, 3-BG) partly rescued proliferation. SP1 mediated SNHG22 expression at the transcriptional level and the SNHG22 promoter region (-900~ -600) was necessary for SP1 binding. Hypoxia and HIF-1α also upregulated SNHG22 expression. CONCLUSION: SNHG22 is an independent prognostic biomarker for EOC. SNHG22 promotes EOC progression and is a prospective therapeutic target.

Hypoxia-induced PTTG3P contributes to colorectal cancer glycolysis and M2 phenotype of macrophage.

Long noncoding RNAs (lncRNAs) play critical factors in tumor progression and are ectopically expressed in malignant tumors. Until now, lncRNA pituitary tumor-transforming 3, pseudogene (PTTG3P) biological function in colorectal cancer (CRC) further needs to be clarified. qRT-PCR was used to measure the PTTG3P level and CCK-8, glucose uptake, lactate assay, adenosine triphosphate (ATP) assay, extracellular acidification rate (ECAR) assay, and xenograft mice model were adopted to evaluate the glycolysis and proliferation, and macrophage polarization were determined in CRC cells. Xenograft experiments were utilized to analyze tumor growth. Ectopic expression of PTTG3P was involved in CRC and related to dismal prognosis. Through gain- and loss-of-function approaches, PTTG3P enhanced cell proliferation and glycolysis through YAP1. Further, LDHA knockdown or glycolysis inhibitor (2-deoxyglucose (2-DG), 3-BG) recovered from PTTG3P-induced proliferation. And PTTG3P overexpression could facilitate M2 polarization of macrophages. Silenced PTTG3P decreased the level of inflammatory cytokines TNF-α, IL-1ß and IL-6, and low PTTG3P expression related with CD8+ T, NK, and TFH cell infiltration. Besides, hypoxia-inducible factor-1α (HIF1A) could increase PTTG3P expression by binding to the PTTG3P promoter region. Hypoxia-induced PTTG3P contributes to glycolysis and M2 phenotype of macrophage, which proposes a novel approach for clinical treatment.

Pathways and Kinetics for Autocatalytic Reduction of CO2 into Formic Acid with Fe under Hydrothermal Conditions.

The utilization of CO2, as a cheap and abundant carbon source to produce useful chemicals or fuels, has been regarded as one of the promising ways to reduce CO2 emissions and minimize the green-house effect. Previous studies have demonstrated that CO2 (or HCO3 -) can be efficiently reduced to formic acid with metal Fe under hydrothermal conditions without additional hydrogen and any catalyst. However, the pathways and kinetics of the autocatalytic CO2 reduction remain unknown. In the present work, the reaction kinetics were carefully investigated according to the proposed reaction pathways, and a phenomenological kinetic model was developed for the first time. The results showed that the hydrothermal conversion of HCO3 - into formic acid with Fe can be expressed as the first-order reaction, and the activation energy of HCO3 - is 28 kJ/mol under hydrothermal conditions.

Photoaffinity Labeling and Quantitative Chemical Proteomics Identify LXRß as the Functional Target of Enhancers of Astrocytic apoE.

Utilizing a phenotypic screen, we identified chemical matter that increased astrocytic apoE secretion in vitro. We designed a clickable photoaffinity probe based on a pyrrolidine lead compound and carried out probe-based quantitative chemical proteomics in human astrocytoma CCF-STTG1 cells to identify liver x receptor ß (LXRß) as the target. Binding of the small molecule ligand stabilized LXRß, as shown by cellular thermal shift assay (CETSA). In addition, we identified a probe-modified peptide by mass spectrometry and proposed a model where the photoaffinity probe is bound in the ligand-binding pocket of LXRß. Taken together, our findings demonstrated that the lead chemical matter bound directly to LXRß, and our results highlight the power of chemical proteomic approaches to identify the target of a phenotypic screening hit. Additionally, the LXR photoaffinity probe and lead compound described herein may serve as valuable tools to further evaluate the LXR pathway.

[Effect of microbial community structure of activated sludge in an Anaerobic-anoxic-oxic process with Actinic reaction enzyme system start-up].

In order to explore the microbial communities and functions of activated sludge in an Anaerobic-anoxic-oxic (A²/O) process under the start-up of Actinic reaction enzyme system (ARES) system and to understand the impact of the ARES system in domestic sewage treatment process, the activated sludge microbial community structure in the A²/O process system before and after ARES system start-up was analyzed by Illumina-HiSeq 2000 high-throughput sequencing platform. By combining with the main parameters related to the effect of sewage treatment, we analyzed the environmental functions of the microbial communities. The microbial community structure of activated sludge was significantly different before and after the ARES system start-up. There were 9 main bacterial phyla in the system (average relative abundance ≥1%), accounting for 96%-98% of the total bacteria sequenced. After the ARES system was started, the relative abundance of Betaproteobacteria and Chlorobi increased by 3.45%-3.85% and 0.45%-2.61%, respectively. In the anaerobic unit, the relative abundance of Bacteroidetes increased by 12.97%, while the Actinobacteria and Firmicutes decreased by 9.60% and 1.45%, respectively. At the genus level of bacteria, the relative abundance of Denitratisoma increased by 0.80%-3.27%, while the Haliangium and Arcobacter decreased by 3.36%-4.52% and 1.48%-3.45%, respectively. The relative abundance of bacteria was significantly different before and after the ARES system start-up. There were 7 abundant fungi phyla (average relative abundance ≥1%) in the system. After the ARES system was started, the relative abundance of Rozellomycota decreased by 42.71%-46.77%. In the anaerobic unit, the relative abundance of Ascomycota decreased by 13.39%, while the relative abundance of Glomeromycota increased by 13.86%. At the genus level of fungi. The relative abundance of Entomophthoraceae sp. and Glomcromycota sp. increased by 31.35%-36.50% and 6.27%-13.84%, respectively, while the Rozellomycota sp. and Xylochrysis lucida decreased by 42.71%-46.77% and 3.67%-5.54%, respectively. Our results showed that the application of ARES system caused the response of the microbial community to environmental changes, especially for the fungi communities, in the meanwhile, improved the effluent quality, especially the removal rate of total nitrogen.