Neuromedin S regulates goat ovarian granulosa cell proliferation and steroidogenesis via endoplasmic reticulum Ca2+-YAP1-ATF4-c-Jun pathway.

Neuromedin S (NMS) plays key roles in reproductive regulation, while its function and mechanism in follicular development remain unclear. The current study aims to investigate the specific role and mechanisms of NMS and its receptors in regulating the proliferation and steroidogenesis of ovarian granulosa cells (GCs). Phenotypically, a certain concentration of NMS addition promoted the proliferation and estrogen production of goat GCs, accompanied by an increase in the G1/S cell population and upregulation of the expression levels of cyclin D1, cyclin dependent kinase 6, steroidogenic acute regulatory protein, cytochrome P450, family 11, subfamily A, polypeptide 1, 3beta-hydroxysteroid dehydrogenase, and cytochrome P450, family 11, subfamily A, polypeptide 1, while the effects of NMS treatment were effectively hindered by knockdown of neuromedin U receptor type 2 (NMUR2). Mechanistically, activation of NMUR2 with NMS maintained endoplasmic reticulum (ER) calcium (Ca2+) homeostasis by triggering the PLCG1-IP3R pathway, which helped preserve ER morphology, sustained an appropriate level of endoplasmic reticulum unfolded protein response (UPRer), and suppressed the nuclear translocation of activating transcription factor 4. Moreover, NMS maintained intracellular Ca2+ homeostasis to activate the calmodulin 1-large tumor suppressor kinase 1 pathway, ultimately orchestrating the regulation of goat GC proliferation and estrogen production through the Yes1 associated transcriptional regulator-ATF4-c-Jun pathway. Crucially, the effects of NMS were mitigated by concurrent knockdown of the NMUR2 gene. Collectively, these data suggest that activation of NMUR2 by NMS enhances cell proliferation and estrogen production in goat GCs through modulating the ER and intracellular Ca2+ homeostasis, leading to activation of the YAP1-ATF4-c-Jun pathway. These findings offer valuable insights into the regulatory mechanisms involved in follicular growth and development, providing a novel perspective for future research.

Zearalenone modulates the function of goat endometrial cells via the mitochondrial quality control system.

Zearalenone (ZEN) is a mycotoxin known for its estrogen-like effects, which can disrupt the normal physiological function of endometrial cells and potentially lead to abortion in female animals. However, the precise mechanism by which ZEN regulates endometrial function remains unclear. In this study, we found that the binding receptor estrogen receptors for ZEN is extensively expressed across various segments of the uterus and within endometrial cells, and a certain concentration of ZEN treatment reduced the proliferation capacity of goat endometrial epithelial cells (EECs) and endometrial stromal cells (ESCs). Meanwhile, cell cycle analysis revealed that ZEN treatment leaded to cell cycle arrest in goat EECs and ESCs. To explore the underlying mechanism, we investigated the mitochondrial quality control systems and observed that ZEN triggered excessive mitochondrial fission and disturbed the balance of mitochondrial fusion-fission dynamics, impaired mitochondrial biogenesis, increased mitochondrial unfolded protein response and mitophagy in goat EECs and ESCs. Additionally, ZEN treatment reduced the activities of mitochondrial respiratory chain complexes, heightened the production of hydrogen peroxide and reactive oxygen species, and caused cellular oxidative stress and mitochondrial dysfunction. These results suggest that ZEN has adverse effects on goat endometrium cells by disrupting the mitochondrial quality control system and affecting cell cycle and proliferation. Understanding the underlying molecular pathways involved in ZEN-induced mitochondrial dysfunction and its consequences on cell function will provide critical insights into the reproductive toxicity of ZEN and contribute to safeguarding the health and wellbeing of animals and humans exposed to this mycotoxin.

Electron syntrophy between mixed hydrogenogens and Geobacter metallireducens boosted dark hydrogen fermentation: Clarifying roles of electroactive extracellular polymeric substances.

To modulate the electron transfer behavior of hydrogen-producing bacteria (HPB) for enhanced hydrogen production, Geobacter metallireducens culture (GM) was introduced as an electron syntrophy partner and redox balance regulator in dark fermentation systems with hydrogen-producing sludge (HPS) as inoculum. The highest hydrogen yield was 306.5 mL/g-COD at the GM/HPS volatile solids ratio of 0.08, which was 65.2 % higher than the HPS group. The multi-layered extracellular polymeric substances (EPS) of GM played a significant role in promoting hydrogen production, with c-type cytochromes probably serving as electroactive functional components. The addition of GM significantly improved the NADH/NAD+ ratio, electron transport system activity, hydrogenase activity, and electrochemical properties of HPS. Furthermore, the microbial community structure and metabolic functions were optimized due to the potential syntrophic interaction between Clostridium sensu stricto (dominant HPB) and Geobacter, thus promoting hydrogen production. This study provided novel insights into the interactions among exoelectrogens, electroactive EPS, and mixed HPB.

Atomic Pyridinic Nitrogen as Highly Active Metal-Free Coordination Sites at the Biotic-Abiotic Interface for Bio-Electrochemical CO2 Reduction.

Bio-electrochemical conversion of anthropogenic CO2 into value-added products using cost-effective metal-free catalysts represents a promising strategy for sustainable fuel production. Herein, N-doped carbon nanosheets synthesized via pyrolysis of the zeolitic-imidazolate framework (ZIF) are developed for constructing efficient biohybrids to facilitate CO2 -to-CH4 conversion. The microbial enrichment and bio-interfacial charge transfer are significantly affected by the proportion of the co-existed graphitic-N, pyridinic-N, and pyrrolic-N in the defective carbon nanosheets. It is unfolded that pyridinic-N and pyrrolic-N with the doped N atoms near the edge can significantly enhance the adsorption of their adjacent C atoms toward O, leading to improved microbe enrichment. Especially, pyridinic-N which can provide one p electron to the aromatic π system, greatly enhances the electron-donating capability of the carbon nanosheets to the microorganisms. Correspondingly, due to its largest amount of pyridinic-N doping, the N-doped carbon nanosheets derived from ZIF pyrolysis at 900 °C (denoted 900-NC) achieve the highest methane production of ≈215.7 mmol m-2  day-1 with a high selectivity (Faradaic efficiency = ≈94.2%) at -0.9 V versus Ag/AgCl. This work demonstrates the effectiveness of N-doped carbon catalysts for bio-electrochemical CO2 fixation and contributes to the understanding of N functionalities toward microbiome response and biotic-abiotic charge transfer in various bio-electrochemical systems.

Revealing Co-N4 @Co-NP Bridge-Enabled Fast Charge Transfer and Active Intracellular Methanogenesis in Bio-Electrochemical CO2 -Conversion with Methanosarcina Barkeri.

To significantly advance the bio-electrochemical CO2 -conversion rate and unfold the correlation between the abiotic electrode and the attached microorganisms, an atomic-nanoparticle bridge of Co-N4 @Co-NP crafted in metal-organic frameworks-derived nanosheets is integrated with a model methanogen of Methanosarcina barkeri (M. barkeri). The direct bonding of N in Co-N4 and Fe in member protein of Cytochrome b (Cytb) activates a fast direct electron transfer path while the Co nanoparticles further strengthen this bonding via decreasing the energy gap between the p-band center of N and the d-band center of Fe. This multiorbital tuning operation of Co nanoparticles also enhances the coenzyme F420-mediated electron transfer by enabling the electron flow direct to the hydrogenation sites. Particularly, the increased surface electric field of the Co-N4 @Co-NP bridge-based nanosheet electrode facilitates the interfacial Na+ accumulation to expedite ATPase transport for powering intracellular CO2 conversion. Remarkably, the self-assembled M.barkeri-Co-N4 @Co-NP biohybrid achieves a high methane production rate of 3860 mmol m-2 day-1 , which greatly outperforms other reported biohybrid systems. This work demonstrates a comprehensive scrutinization of biotic-abiotic energy transfer, which may serve as a guiding principle for efficient bio-electrochemical system design.

Co-NC@Co-NP hierarchical nanoforest steering charge exchange efficiency at biotic-abiotic interface for microbial electrochemical carbon reduction.

Converting anthropogenic carbon dioxide (CO2) to value-added products using bio-electrochemical conversions represents a promising strategy for producing sustainable fuel. However, the reaction kinetics are hindered by insufficient attachment of microorganisms and limited charge extraction at the bioinorganic interface. A hierarchical nanoforest with doped cobalt­nitrogen-doped carbon covering cobalt nanoparticle (Co-NC@Co-NP) was integrated with a CO2-to-CH4 conversion microbiome for methane production to address these shortcomings. In-situ nanoforests were developed on the nanosheet by chemical vapor deposition with Co nanoparticles catalyzed. The bio-nanowire-like carbon nanotubes enhanced the electrostatic force for microbe enrichment via the tip effect, providing a maximum of 3.6-fold electron-receiving microbes to utilize reducing equivalents. The Co-NC@Co-NP enhanced the direct electron transfer between microbes and electrodes, reducing the adoption of energy barriers for heme-like proteins. Thus, the optimized electron transfer pathway improved selectivity by a factor of 2.0 compared to the pristine nanosheet biohybrid. Furthermore, the adjusted microbial community structure provided sufficient methanogenesis genes to match the strong electron flow, achieving maximal methane production rates (311.1 mmol/m2/day at -0.9 V vs. Ag/AgCl), 8.62 times higher than those of the counterpart nanosheet biohybrid (36.06 mmol/m2/day). This work demonstrates a comprehensive assessment of biotic-abiotic energy transfer, which may serve as a guiding principle for designing efficient bio-electrochemical systems.

Electron transfer from Geobacter sulfurreducens to mixed methanogens improved methane production with feedstock gases of H2 and CO2.

In order to solve problems of poor utilization of H2 and CO2 in biomethane conversion with mixed methanogens due to multi-channel competition and nondirectional electron transfer, Geobacter sulfurreducens were cocultured with mixed methanogens to promote oriented metabolic pathway of H2 and CO2 to produce CH4. When inoculation volume ratio of G. sulfurreducens to mixed methanogens was 2:4, CH4 yield increased to 0.24 mL/ml H2 (close to the maximum theoretical yield of 0.25 mL/ml H2) and conversion efficiency of H2 to CH4 increased from 72 to 96%. Electrochemical detection and three-dimensional fluorescence spectra showed that the co-culture system had an increased metabolic capacity and spectral intensity of fulvic acid-like compounds was enhanced, which mediated direct interspecific electron transfer to produce CH4. The 16S rRNA gene sequencing showed that relative abundance of G. sulfurreducens and Methanoculleus increased, indicating an established syntrophic relationship between G. sulfurreducens and Methanoculleus.

Microbial electrochemical degradation of lipids for promoting methane production in anaerobic digestion.

In order to solve problems of low methane production from lipids in anaerobic digestion, microbial electrochemical degradation was proposed to promote methane yield of glycerol trioleate (a typical lipid component of food waste). The beta-oxidation of lipids was strengthened with an applied voltage to promote electron transfer and anaerobic digestion. SEM images showed that a lot of spherical and rod-shaped microbes adhered to electrode surfaces. Cyclic voltammetry showed that electron transfer rate constant at 0.8 V was 14.4-fold that at 0 V. Three-dimensional fluorescence spectroscopy showed that small organic degraded molecules were used more efficiently in anaerobic digestion. The methane yield of glycerol trioleate increased to 791.6 mL/g-TVS (at 0.8 V), while methane production peak rate increased to 26.8 mL/g-TVS/d with a shortened peak time to 24th day. The overall energy conversion efficiency in methane production increased from 53.6 to 60.1% due to microbial electrochemical degradation of lipids.

Hybrid Quantum-Classical Neural Network for Calculating Ground State Energies of Molecules.

We present a hybrid quantum-classical neural network that can be trained to perform electronic structure calculation and generate potential energy curves of simple molecules. The method is based on the combination of parameterized quantum circuits and measurements. With unsupervised training, the neural network can generate electronic potential energy curves based on training at certain bond lengths. To demonstrate the power of the proposed new method, we present the results of using the quantum-classical hybrid neural network to calculate ground state potential energy curves of simple molecules such as H2, LiH, and BeH2. The results are very accurate and the approach could potentially be used to generate complex molecular potential energy surfaces.

A quantum algorithm for evolving open quantum dynamics on quantum computing devices.

Designing quantum algorithms for simulating quantum systems has seen enormous progress, yet few studies have been done to develop quantum algorithms for open quantum dynamics despite its importance in modeling the system-environment interaction found in most realistic physical models. In this work we propose and demonstrate a general quantum algorithm to evolve open quantum dynamics on quantum computing devices. The Kraus operators governing the time evolution can be converted into unitary matrices with minimal dilation guaranteed by the Sz.-Nagy theorem. This allows the evolution of the initial state through unitary quantum gates, while using significantly less resource than required by the conventional Stinespring dilation. We demonstrate the algorithm on an amplitude damping channel using the IBM Qiskit quantum simulator and the IBM Q 5 Tenerife quantum device. The proposed algorithm does not require particular models of dynamics or decomposition of the quantum channel, and thus can be easily generalized to other open quantum dynamical models.

Quantum machine learning for electronic structure calculations.

Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations-alongside impressive results using machine learning techniques for computation-hybridizing quantum computing with machine learning for the intent of performing electronic structure calculations is a natural progression. Here we report a hybrid quantum algorithm employing a restricted Boltzmann machine to obtain accurate molecular potential energy surfaces. By exploiting a quantum algorithm to help optimize the underlying objective function, we obtained an efficient procedure for the calculation of the electronic ground state energy for a small molecule system. Our approach achieves high accuracy for the ground state energy for H2, LiH, H2O at a specific location on its potential energy surface with a finite basis set. With the future availability of larger-scale quantum computers, quantum machine learning techniques are set to become powerful tools to obtain accurate values for electronic structures.

Electronic Structure Calculations and the Ising Hamiltonian.

Obtaining exact solutions to the Schrödinger equation for atoms, molecules, and extended systems continues to be a "Holy Grail" problem which the fields of theoretical chemistry and physics have been striving to solve since inception. Recent breakthroughs have been made in the development of hardware-efficient quantum optimizers and coherent Ising machines capable of simulating hundreds of interacting spins with an Ising-type Hamiltonian. One of the most vital questions pertaining to these new devices is, "Can these machines be used to perform electronic structure calculations?" Within this work, we review the general procedure used by these devices and prove that there is an exact mapping between the electronic structure Hamiltonian and the Ising Hamiltonian. Additionally, we provide simulation results of the transformed Ising Hamiltonian for H2 , He2 , HeH+, and LiH molecules, which match the exact numerical calculations. This demonstrates that one can map the molecular Hamiltonian to an Ising-type Hamiltonian which could easily be implemented on currently available quantum hardware. This is an early step in developing generalized methods on such devices for chemical physics.