FFAR4 activation inhibits lung adenocarcinoma via blocking respiratory chain complex assembly associated mitochondrial metabolism.

Despite notable advancements in the investigation and management of lung adenocarcinoma (LUAD), the mortality rate for individuals afflicted with LUAD remains elevated, and attaining an accurate prognosis is challenging. LUAD exhibits intricate genetic and environmental components, and it is plausible that free fatty acid receptors (FFARs) may bridge the genetic and dietary aspects. The objective of this study is to ascertain whether a correlation exists between FFAR4, which functions as the primary receptor for dietary fatty acids, and various characteristics of LUAD, while also delving into the potential underlying mechanism. The findings of this study indicate a decrease in FFAR4 expression in LUAD, with a positive correlation (P < 0.01) between FFAR4 levels and overall patient survival (OS). Receiver operating characteristic (ROC) curve analysis demonstrated a significant diagnostic value [area under the curve (AUC) of 0.933] associated with FFAR4 expression. Functional investigations revealed that the FFAR4-specific agonist (TUG891) effectively suppressed cell proliferation and induced cell cycle arrest. Furthermore, FFAR4 activation resulted in significant metabolic shifts, including a decrease in oxygen consumption rate (OCR) and an increase in extracellular acidification rate (ECAR) in A549 cells. In detail, the activation of FFAR4 has been observed to impact the assembly process of the mitochondrial respiratory chain complex and the malate-aspartate shuttle process, resulting in a decrease in the transition of NAD+ to NADH and the inhibition of LUAD. These discoveries reveal a previously unrecognized function of FFAR4 in the negative regulation of mitochondrial metabolism and the inhibition of LUAD, indicating its potential as a promising therapeutic target for the treatment and diagnosis of LUAD.

Robotic Intracellular Pressure Measurement Using Micropipette Electrode.

Intracellular pressure, a key physical parameter of the intracellular environment, has been found to regulate multiple cell physiological activities and impact cell micromanipulation results. The intracellular pressure may reveal the mechanism of these cells' physiological activities or improve the micro-manipulation accuracy for cells. The involvement of specialized and expensive devices and the significant damage to cell viability that the current intracellular pressure measurement methods cause significantly limit their wide applications. This paper proposes a robotic intracellular pressure measurement method using a traditional micropipette electrode system setup. First, the measured resistance of the micropipette inside the culture medium is modeled to analyze its variation trend when the pressure inside the micropipette increases. Then, the concentration of KCl solution filled inside the micropipette electrode that is suitable for intracellular pressure measurement is determined according to the tested electrode resistance-pressure relationship; 1 mol/L KCl solution is our final choice. Further, the measurement resistance of the micropipette electrode inside the cell is modeled to measure the intracellular pressure through the difference in key pressure before and after the release of the intracellular pressure. Based on the above work, a robotic measurement procedure of the intracellular pressure is established based on a traditional micropipette electrode system. The experimental results on porcine oocytes demonstrate that the proposed method can operate on cells at an average speed of 20~40 cells/day with measurement efficiency comparable to the related work. The average repeated error of the relationship between the measured electrode resistance and the pressure inside the micropipette electrode is less than 5%, and no observable intracellular pressure leakage was found during the measurement process, both guaranteeing the measurement accuracy of intracellular pressure. The measured results of the porcine oocytes are in accordance with those reported in related work. Moreover, a 90% survival rate of operated oocytes was obtained after measurement, proving limited damage to cell viability. Our method does not rely on expensive instruments and is conducive to promotion in daily laboratories.

A Machine Learning Method for Automated In Vivo Transparent Vessel Segmentation and Identification Based on Blood Flow Characteristics.

In vivo transparent vessel segmentation is important to life science research. However, this task remains very challenging because of the fuzzy edges and the barely noticeable tubular characteristics of vessels under a light microscope. In this paper, we present a new machine learning method based on blood flow characteristics to segment the global vascular structure in vivo. Specifically, the videos of blood flow in transparent vessels are used as input. We use the machine learning classifier to classify the vessel pixels through the motion features extracted from moving red blood cells and achieve vessel segmentation based on a region-growing algorithm. Moreover, we utilize the moving characteristics of blood flow to distinguish between the types of vessels, including arteries, veins, and capillaries. In the experiments, we evaluate the performance of our method on videos of zebrafish embryos. The experimental results indicate the high accuracy of vessel segmentation, with an average accuracy of 97.98%, which is much more superior than other segmentation or motion-detection algorithms. Our method has good robustness when applied to input videos with various time resolutions, with a minimum of 3.125 fps.

Current progress of emerging technologies in human and animals' milk processing: Retention of immune-active components and microbial safety.

Human milk and commercial dairy products play a vital role in humans, as they can provide almost all essential nutrients and immune-active components for the development of children. However, how to retain more native immune-active components of milk during processing remains a big question for the dairy industry. Nonthermal technologies for milk processing are gaining increasing interest in both academic and industrial fields, as it is known that thermal processing may negatively affect the quality of milk products. Thermosensitive components, such as lactoferrin, immunoglobulins (Igs), growth factors, and hormones, are highly important for the healthy development of newborns. In addition to product quality, thermal processing also causes environmental problems, such as high energy consumption and greenhouse gas (GHG) emissions. This review summarizes the recent advances of UV-C, ultrasonication (US), high-pressure processing (HPP), and other emerging technologies for milk processing from the perspective of immune-active components retention and microbial safety, focusing on human, bovine, goat, camel, sheep, and donkey milk. Also, the detailed application, including the instrumental design, technical parameters, and obtained results, are discussed. Finally, future prospects and current limitations of nonthermal techniques as applied in milk processing are discussed. This review thereby describes the current state-of-the-art in nonthermal milk processing techniques and will inspire the development of such techniques for in-practice applications in milk processing.

A Cell's Viscoelasticity Measurement Method Based on the Spheroidization Process of Non-Spherical Shaped Cell.

The mechanical properties of biological cells, especially the elastic modulus and viscosity of cells, have been identified to reflect cell viability and cell states. The existing measuring techniques need additional equipment or operation condition. This paper presents a cell's viscoelasticity measurement method based on the spheroidization process of non-spherical shaped cell. The viscoelasticity of porcine fetal fibroblast was measured. Firstly, we introduced the process of recording the spheroidization process of porcine fetal fibroblast. Secondly, we built the viscoelastic model for simulating a cell's spheroidization process. Then, we simulated the spheroidization process of porcine fetal fibroblast and got the simulated spheroidization process. By identifying the parameters in the viscoelastic model, we got the elasticity (500 Pa) and viscosity (10 Pa·s) of porcine fetal fibroblast. The results showed that the magnitude of the elasticity and viscosity were in agreement with those measured by traditional method. To verify the accuracy of the proposed method, we imitated the spheroidization process with silicone oil, a kind of viscous and uniform liquid with determined viscosity. We did the silicone oil's spheroidization experiment and simulated this process. The simulation results also fitted the experimental results well.

Mechanical and barrier properties of maize starch-gelatin composite films: effects of amylose content.

BACKGROUND: In order to obtain new reinforcing bio-fillers to improve the physicochemical properties of gelatin-based films, three types of maize starch, waxy maize starch (Ap), normal starch (Ns) and high-amylose starch (Al), were incorporated into gelatin film and the resulting film properties were investigated, focusing on the impact of amylose content. RESULTS: The thickness, opacity and roughness of gelatin film increased depending on the amylose content along with the starch concentration. The effects of the three starches on the mechanical properties of gelatin film were governed by amylose content, starch concentration as well as environmental relative humidity (RH). At 75% RH, the presence of Al and Ns in the gelatin matrix increased the film strength but decreased its elongation, while Ap exhibited an inverse effect. Starch addition decreased the oxygen permeability of the film, with the lowest value at 20% Al and Ns. All starches, notably at 30% content, led to a decrease in the water vapor permeability of the film at 90% RH, especially Ns starch. Furthermore, the starches improved the thermal stability of the film to some extent. Fourier transform infrared spectra indicated that some weak intermolecular interactions such as hydrogen bonding occurred between gelatin and starch. Moreover, a high degree of B-type crystallinity of starch was characterized in Gel-Al film by X-ray diffraction. CONCLUSION: Tailoring the properties of gelatin film by the incorporation of different types of maize starch provides the potential to extend its applications in edible food packaging. © 2017 Society of Chemical Industry.

Evaluation of Two Observational Pain Assessment Tools in Chinese Critically Ill Patients.

OBJECTIVES: To examine and compare the reliability and validity of two observational pain assessment tools used in a sample of Chinese critically ill patients. DESIGN: A prospective observational study. SETTING AND SUBJECTS: A convenience sample of 117 adult critically ill patients was recruited from a general Intensive Care Unit in a university-affiliated hospital in China. METHODS: Pain was assessed before and during painful and nonpainful routine care procedures (suctioning and noninvasive blood pressure measurement, respectively) using the Critical-Care Pain Observation Tool (CPOT) and the Behavioral Pain Scale (BPS), including the original BPS and the BPS for Non-Intubated patients (BPS-NI). Internal consistency, test-retest reliability, interrater reliability, and discriminant validity of the CPOT and the BPS were evaluated, and the two scales compared. RESULTS: A total of 608 assessments were obtained using the CPOT and the BPS. Overall Cronbach's alpha coefficient for the CPOT and the BPS was 0.795 and 0.791, respectively. Test-retest reliability of the CPOT and the BPS was 0.950 and 0.941, respectively. Overall weighted κ between the two raters of the CPOT and the BPS was 0.973 and 0.955, respectively. Scores of the CPOT and the BPS during the painful procedures were both significantly higher than those during the nonpainful procedures, and those at rest before the painful procedures. There was a strong correlation between the two scales with adequate limits of agreement. CONCLUSION: Both the CPOT and the BPS are reliable and valid tools to assess pain in intubated and nonintubated critically ill Chinese patients.

Evaluation of two observational pain assessment scales during the anaesthesia recovery period in Chinese surgical older adults.

AIMS AND OBJECTIVES: To evaluate the reliability and validity of the Pain Assessment in Advanced Dementia scale and the Checklist of Nonverbal Pain Indicators in Chinese older adults post surgery during the anaesthesia recovery period. BACKGROUND: Pain assessment in older surgical patients is complicated by factors such as anaesthesia and opioid administration. Although observational pain behavioural assessment tools have been validated for those unable to self-report, research on their application during the anaesthesia recovery period is limited. DESIGN: A prospective correlational design. METHODS: Ninety-three older patients admitted for scheduled abdominal surgery were recruited in a university-affiliated hospital. The two observational scales were used to conduct pain assessments during the anaesthesia recovery period. On the first and the third postoperative day, participants recalled their pain intensity during the recovery period using the Numeric Rating Scale or the Faces Pain Scale-Revised. RESULTS: The internal consistency reliability of the Pain Assessment in Advanced Dementia scale and the Checklist of Nonverbal Pain Indicators was 0·81 and 0·69 respectively. The correlation between scores of the two observational scales was 0·95. The recalled self-reports of pain intensity were significantly correlated. The correlation of the Pain Assessment in Advanced Dementia scale and patients' recalled self-reports was 0·55, 0·54, and the correlation between the Checklist of Nonverbal Pain Indicators and the two recalled pain scores was both 0·60. CONCLUSIONS: Both the two observational scales had good reliability and validity when used to assess pain in Chinese surgical older adults during the anaesthesia recovery period. RELEVANCE TO CLINICAL PRACTICE: Observational pain scales can be useful as a tool for patients unable to self-report. Accurate use of one of the observational pain tools can help identify pain during the anaesthesia recovery period, when patients are unable to self-report, to support effective pain management during this period.

A Simulation of the Mechanical Testing of the Cell Membrane and Cytoskeleton.

Cell models play a crucial role in analyzing the mechanical response of cells and quantifying cellular damage incurred during micromanipulation. While traditional models can capture the overall mechanical behavior of cells, they often lack the ability to discern among distinct cellular components. Consequently, by employing dissipative particle dynamics, this study constructed a triangular network-like representation of the cell membrane along with cross-linked cytoskeletal chains. The mechanical properties of both the membrane and cytoskeleton were then analyzed through a series of simulated mechanical tests, validated against real-world experiments. The investigation utilized particle-tracking rheology to monitor changes in the mean square displacements of membrane particles over time, facilitating the analysis of the membrane's storage and loss moduli. Additionally, the cytoskeletal network's storage and loss moduli were examined via a double-plate oscillatory shear experiment. The simulation results revealed that both the membrane and cytoskeleton exhibit viscoelastic behavior, as evidenced by the power-law dependency of their storage and loss moduli on frequency. Furthermore, indentation and microinjection simulations were conducted to examine the overall mechanical properties of cells. In the indentation experiments, an increase in the shear modulus of the membrane's WLCs correlated with a higher Young's modulus for the entire cell. Regarding the microinjection experiment, augmenting the microinjection speed resulted in reduced deformation of the cell at the point of membrane rupture and a lower percentage of high strain.

Microbial resistance and resilience to drought and rewetting modulate soil N2O emissions with different fertilizers.

Future climate models indicate an enhanced severity of regional drought and frequent rewetting events, which may cause cascading impacts on soil nitrogen cycle and nitrous oxide (N2O) emissions, but the underlying microbial mechanism remains largely unknown. Here we report an incubation study that examined the impacts of soil moisture status and nitrification inhibitor (DCD) on the N2O-producers and N2O-reducers following the application of urea and composted swine manure in an acid soil. The soil moisture treatments included 100 % water-holding capacity (WHC) (wetting, 35.3 % gravimetric soil water content), 40 % WHC (drought, 7 % gravimetric soil water content), and 40 % to 100 % WHC (rewetting). The results showed that N2O emissions were significantly decreased under drought conditions and were significantly increased after rewetting. The resistance of ammonia-oxidizing bacteria and nosZII, which was inhibited by urea or manure application, modulated N2O emissions under drought conditions. The resilience of the functional guilds modulated their dominant role in N2O emissions with rewetting. Ammonia-oxidizing bacteria, nirS-type denitrifying bacteria and nosZI showed significant resilience in response to rewetting. Significant negative relationships were observed between N2O emissions and nosZII clade under wetting condition and between N2O emissions and nosZI clade after rewetting. Our results highlighted the importance of microbial resistance and resilience in modulating N2O emissions, which help to better understand the dominant way of N2O emissions, and consequently make efficient mitigation strategies under the global climate change.

A new method for axis adjustment of the hydro-generator unit using machine learning.

The power quality and efficiency of the hydro-power station depend on the stable operation of the hydro-generator unit, which needs to continue to operate and it is prone to axis failure. Therefore, to adopt effective axis adjustment technology to eliminate faults. This paper proposes a new method for axis adjustment of hydro-generator unit based on an improved grey prediction model and swarms intelligence optimization neural network. First of all, it proposes a sequence acceleration translation and mean value transformation method, which is used to pre-process the axis net total swing sequence that exhibits oscillating fluctuations. It uses e1 and e2 factor transformation to establish an improved axis net total swing gray prediction model. Then, the advanced flamingo search algorithm is used to search the maximum value of the sine function of the net total pendulum of the axis, and the axis adjustment orientation is obtained. This method solves the problem that GM(1, 1) can only be predicted by monotone sequence in the past and the problem that the search algorithm is easy to fall into local optimum, effectively improves the calculation efficiency of axis and shorts the search time. Simulation examples show that the proposed method can significantly improve accuracy of axis adjustment. This method greatly improves the efficiency of azimuth search for axis adjustment.

The full model of micropipette aspiration of cells: A mesoscopic simulation.

Studies on the interaction between cells and micromanipulation tools are necessary to optimize the procedures and improve the developmental potential of cells. The molecular dynamics simulation is not possible for such a large-scale simulation, and the spring-damped viscoelastic models and the constitutive equations of the continuum are usually adopted to model the cells as a whole without consideration of the different properties presented by the heterogeneous subcellular components. In this study, we utilized coarse-grained modeling to develop a subcellular model of suspension cell dynamics and a model of a holding micropipette for the fixation of a suspension cell, and designed a large-scale, accurate mesoscopic simulation environment for specific cell micromanipulation. We established a triangular mesh cell membrane and a uniformly distributed, non-intersecting cytoskeleton network and added polymerization/depolymerization processes to connect the cytoskeleton chains with the membrane and cross-linking proteins. In the cell aspiration model, we adopted the profile of the reversed Poiseuille flow to calibrate the viscosity of the fluid and set the bounce-back condition and the appropriate solid-fluid force coefficient to realize non-slip flow at the boundary. The rheological properties of the cells during micropipette aspiration were further analyzed in the simulation by varying parameters such as the inner diameter of the micropipette, negative pressure, and maximum bond length. The model well reproduced the experimentally observed cell deformation phenomenon at low and high pressures. The dynamic response of the cell elongation observed from the simulation was consistent with that obtained from the analysis of the experimental data collected from a custom-designed micromanipulation system. STATEMENT OF SIGNIFICANCE: In this study, we extended the coarse-grained modeling of cells by developing a relatively large-scale micromanipulation environment consisting of a subcellular cell dynamics model and a fluid flow model for cell aspiration. We simulated cytoskeleton filaments that were uniformly distributed in space via applying Harmonic energy to model cytoskeleton with a high level of fidelity. The shortcoming of the soft repulsion in the solid-fluid interaction in the current simulation technique was solved by implementing the bounce-back boundary and the condition that the total force imposed by the wall particles on the fluid particles was equal to the pressure of the fluid. This work paved the way for understanding the mechanical properties of cells and improving the biological efficacy of micromanipulation.

Identification of significant imaging features for sensing oocyte viability.

The evaluation of oocyte viability in the laboratory is limited to the morphological assessment by naked eyes, but the realization that most normal-appearing oocytes may conceal abnormalities prompts the search for automated approaches that can detect the abnormalities imperceptible to naked eyes. In this study, we developed an image processing pipeline applicable to bright-field microscope images to quantify the causal relationship between the quantitative imaging features and the developmental potential of oocytes. We acquired 19 imaging features of approximately 700 oocytes and determined two imaging subtypes, namely viable and nonviable subtypes that correlated closely with a viability fluorescence indicator and cleavage rates. The causal relationship between these imaging features and oocyte viability was derived from a viability-oriented Bayesian network that was developed based on the Bayesian information criterion and Tabu search. Our experimental results revealed that entropy with mean Gray Level Co-Occurrence Matrix energy describing the uniformity and texture roughness of cytoplasm were salient features for the automated selection of promising oocytes that exhibited excellent developmental potential.

Diversity and assembly of active bacteria and their potential function along soil aggregates in a paddy field.

Numerous studies have found that soil microbiomes differ at the aggregate level indicating they provide spatially heterogeneous habitats for microbial communities to develop. However, an understanding of the assembly processes and the functional profile of microbes at the aggregate level remain largely rudimentary, particularly for those active members in soil aggregates. In this study, we investigated the diversity, co-occurrence network, assembly process and predictive functional profile of active bacteria in aggregates of different sizes using H218O-based DNA stable isotope probing (SIP) and 16S rRNA gene sequencing. Most of the bacterial reads were active with 91 % of total reads incorporating labelled water during the incubation. The active microbial community belonged mostly of Proteobacteria and Actinobacteria, with a relative abundance of 55.32 % and 28.12 %, respectively. Assembly processes of the active bacteria were more stochastic than total bacteria, while the assembly processes of total bacteria were more influenced by deterministic processes. Furthermore, many functional profiles such as environmental information processing increased in active bacteria (19.39 %) compared to total bacteria (11.22 %). After incubation, the diversity and relative abundance of active bacteria of certain phyla increased, such as Proteobacteria (50.70 % to 59.95 %), Gemmatimonadetes (2.63 % to 4.11 %), and Bacteroidetes (1.50 % to 2.84 %). In small macroaggregates (SMA: 0.25-2 mm), the active bacterial community and its assembly processes differed from that of other soil aggregates (MA: microaggregates, <0.25 mm; LMA: large macroaggregates, 2-4 mm). For functional profiles, the relative abundance of important functions, such as amino acid metabolism, signal transduction and cell motility, increased with incubation days and/or in SMA compared to other aggregates. This study provides robust evidence that the community of active bacteria and its assembly processes in soil aggregates differed from total bacteria, and suggests the importance of dominant active bacteria (such as Proteobacteria) for the predicted functional profiles in the soil ecosystem.

Oocyte Penetration Speed Optimization Based on Intracellular Strain.

Oocyte penetration is an essential step for many biological technologies, such as animal cloning, embryo microinjection, and intracytoplasmic sperm injection (ICSI). Although the success rate of robotic cell penetration is very high now, the development potential of oocytes after penetration has not been significantly improved compared with manual operation. In this paper, we optimized the oocyte penetration speed based on the intracellular strain. We firstly analyzed the intracellular strain at different penetration speeds and performed the penetration experiments on porcine oocytes. Secondly, we studied the cell development potential after penetration at different penetration speeds. The statistical results showed that the percentage of large intracellular strain decreased by 80% and the maximum and average intracellular strain decreased by 25-38% at the penetration speed of 50 µm/s compared to at 10 µm/s. Experiment results showed that the cleavage rates of the oocytes after penetration increased from 65.56% to 86.36%, as the penetration speed increased from 10 to 50 µm/s. Finally, we verified the gene expression of oocytes after penetration at different speeds. The experimental results showed that the totipotency and antiapoptotic genes of oocytes were significantly higher after penetration at the speed of 50 µm/s, which verified the effectiveness of the optimization method at the gene level.

Mechanical Characterization and Modelling of Subcellular Components of Oocytes.

The early steps of embryogenesis are controlled exclusively by the quality of oocyte that linked closely to its mechanical properties. The mechanical properties of an oocyte were commonly characterized by assuming it was homogeneous such that the result deviated significantly from the true fact that it was composed of subcellular components. In this work, we accessed and characterized the subcellular components of the oocytes and developed a layered high-fidelity finite element model for describing the viscoelastic responses of an oocyte under loading. The zona pellucida (ZP) and cytoplasm were isolated from an oocyte using an in-house robotic micromanipulation platform and placed on AFM to separately characterizing their mechanical profiling by analyzing the creep behavior with the force clamping technique. The spring and damping parameters of a Kelvin-Voigt model were derived by fitting the creeping curve to the model, which were used to define the shear relaxation modulus and relaxation time of ZP or cytoplasm in the ZP and cytoplasm model. In the micropipette aspiration experiment, the model was accurate sufficiently to deliver the time-varying aspiration depth of the oocytes under the step negative pressure of a micropipette. In the micropipette microinjection experiment, the model accurately described the intracellular strain introduced by the penetration. The developed oocyte FEM model has implications for further investigating the viscoelastic responses of the oocytes under different loading settings.

Effects of microfiltration combined with ultrasonication on shelf life and bioactive protein of skim milk.

To extend the shelf life and retain bioactive proteins in milk, this study utilized microfiltration (MF) combined with ultrasonication to treat skim milk and investigated its efficiency in removing bacteria and retaining bioactive proteins compared with HTST pasteurization and microfiltration alone. Results showed that microfiltration combined with ultrasonication at 1296 J/mL could completely remove the bacteria in skim milk. Ultrasonication further extended the shelf life (4 °C) of microfiltered skim milk, which could reach at least 40 days when MF was combined with ˃1296 J/mL ultrasonication. In addition, ELISA showed that HTST pasteurization significantly decreased the levels of IgG by ~30%, IgA by ~ 50%, IgM by ~60%, and lactoferrin by ~40%, whereas the activity of the enzymes lactoperoxidase and xanthine oxidase were also decreased by ~ 20%. Compared with HTST, MF alone or combined with ultrasonication retained these bioactive proteins to a larger degree. On the other hand, proteomics indicated both damage to casein micelle and fat globule structures in milk when ultrasonication at >1296 J/mL was applied, as shown by increases in caseins and milk fat globular proteins. Simultaneously, this ultrasound intensity also decreased levels of bioactive proteins, such as complement factors. Taken together, this study provided new insights that may help to implement this novel combination of non-thermal technologies for the dairy industry aimed at improving milk quality and functionality.

Robotic Label-Free Precise Oocyte Enucleation for Improving Developmental Competence of Cloned Embryos.

OBJECTIVE: The invisibility of domestic oocyte nucleus in bright field currently forces operators to blindly aspirate nucleus out in oocyte enucleation, usually causing large cytoplasm losses and poor developmental competences of cloned embryos. Although fluorescent labeling of nucleus allows for nucleus localization, the involved photobleaching problems and barriers to the execution of enucleation process limit its online-application in oocyte enucleation. This paper reports a novel label-free oocyte enucleation method for precise removal of the nucleus with less cytoplasm loss. METHODS: The relative positions between the injection pipette and nucleus for complete removal of nucleus with less cytoplasm loss were determined through a finite element modeling of nucleus aspiration. To position injection pipette to the above positions relative to nucleus, the appropriate oocyte orientation and trajectory of injection pipette inside oocyte were derived according to the offline-calibrated 3-D distribution of nucleus and the simulated dynamic drift of nucleus that occurs as injection pipette is maneuvered inside oocyte. Finally, a robotic label-free precise enucleation procedure was established. RESULTS: The experimental results on more than 1000 porcine oocytes proved that this system is capable of reducing cytoplasm loss by 60% at the same level of enucleation success rate and almost doubling the cleavage rate of clone embryos in comparison to blind aspiration method. CONCLUSIONS: The results prove that our method significantly improves the developmental competence of cloned embryos in comparison to manual enucleation method. SIGNIFICANCE: Our method is expected to improve the extremely low success rate of animal cloning in the future.

Grazing weakens competitive interactions between active methanotrophs and nitrifiers modulating greenhouse-gas emissions in grassland soils.

Grassland soils serve as a biological sink and source of the potent greenhouse gases (GHG) methane (CH4) and nitrous oxide (N2O). The underlying mechanisms responsible for those GHG emissions, specifically, the relationships between methane- and ammonia-oxidizing microorganisms in grazed grassland soils are still poorly understood. Here, we characterized the effects of grazing on in situ GHG emissions and elucidated the putative relations between the active microbes involving in methane oxidation and nitrification activity in grassland soils. Grazing significantly decreases CH4 uptake while it increases N2O emissions basing on 14-month in situ measurement. DNA-based stable isotope probing (SIP) incubation experiment shows that grazing decreases both methane oxidation and nitrification processes and decreases the diversity of active methanotrophs and nitrifiers, and subsequently weakens the putative competition between active methanotrophs and nitrifiers in grassland soils. These results constitute a major advance in our understanding of putative relationships between methane- and ammonia-oxidizing microorganisms and subsequent effects on nitrification and methane oxidation, which contribute to a better prediction and modeling of future balance of GHG emissions and active microbial communities in grazed grassland ecosystems.

Interactions between methanotrophs and ammonia oxidizers modulate the response of in situ methane emissions to simulated climate change and its legacy in an acidic soil.

Methane (CH4) is one of the most important greenhouse gases which can be formed by methanogens and oxidized by methanotrophs, as well as ammonia oxidizers. Agricultural soils can be both a source and sink for atmospheric CH4. However, it is unclear how climate change, will affect CH4 emissions and the underlying functional guilds. In this field study, we determined the impact of simulated climate change (a warmer and drier condition) and its legacy effect on CH4 emissions and the methanogenic and methanotrophic communities, as well as their relationships with ammonia oxidizers in an acidic soil with urea application. The climate change conditions were simulated in a greenhouse, and the legacy effect was simulated by removing the greenhouse after twelve months. Simulated climate change significantly decreased the in situ CH4 emissions in the urea-treated soils while the legacy effect significantly decreased the in situ CH4 emissions in the control plots, but had very little effect in the urea-treated soils. This indicates that the impact of simulated climate change and its legacy on CH4 emissions was significantly modified by nitrogen fertilization. Methanotrophs were more sensitive than methanogens in response to simulated climate change and its legacy effect, especially in the urea treated soil. Significant negative correlations were observed between the abundances of ammonia oxidizers and methanotrophs. Additionally, results of partial least path modeling (PLS-PM) indicated that the interactions of methanogens and methanotrophs with ammonia oxidizing archaea (AOA) had significant positive relationships with in situ CH4 emissions under the simulated climate change condition. Our work highlights the important role of AOA for CH4 emissions under climate change conditions. Further research is needed to better understand this effect in other ecosystems.