The combined use of hydraulic stimulation and gas-injection-enhanced drainage is an important technical approach to improve gas recovery from low-permeability coal seams. However, the coupling effect between residual water after hydraulic measures and the gas injection pressure on gas migration and distribution remains unclear. On the basis of a deep coal-rock stimulation and dynamic seepage simulation experimental platform, a large-scale 500 mm cubic water-bearing briquette coal sample was prepared. N2 displacement of CO2 experiments were conducted under different injection pressures (0.6 and 1.0 MPa) and coal moisture contents (4 and 6%). The spatiotemporal evolution of the gas pressure field and the concentration field was systematically investigated. The results show that along the gas flow direction, the pressure rise and CO2 concentration decline exhibit good synergy and hierarchical response. In the lateral direction, the farther from the injection port, the more delayed the pressure response and the slower the CO2 concentration decline. In the vertical direction, water migrates downward under gravity, significantly reducing the displacement efficiency in the lower part. Increasing the injection pressure effectively alleviates the inhibition of water on gas transport, especially in the early and middle stages of the displacement. Increasing the moisture content delays the pressure rise and concentration decline and prolongs the displacement cycle. The coupling effect exhibits significant directional differences. The combined effect of injection pressure and water content on gas pressure shows a "1 + 1 > 2" synergistic enhancement, whereas their effect on CO2 concentration decline shows "1 + 1 < 2" mutual inhibition. This reflects the fundamental difference in the sensitivity of the pressure field and concentration field to water. This study reveals the coupled evolution mechanism of gas pressure and concentration fields during gas injection displacement in water-bearing coal seams, providing a theoretical basis for optimizing injection parameters and improving the gas drainage efficiency.

Seizures upregulate Na+-K+-2Cl-(NKCC1)-mediated Cl−influx and downregulate K+-Cl-(KCC2)-mediated Cl-effluxviathe WNK-SPAK/OSR1 kinases, leading to cytoplasmic chloride ([Cl-]i) accumulation, reduced GABAergic inhibition and anticonvulsant failure. Early studies found that inhibiting WNK-kinase reduced baseline [Cl-]i(ECl) and seizures via increased KCC2 activity. However, increased KCC2 activity alone should not affect EClwhose determinants are more complex. We determined the net effects of WNK-SPAK/OSR1 pathway inhibitor WNK463 on ECland [Cl-]itransients during spontaneous ictal-like discharges (ILDs). We found that WNK463 reduced interictal [Cl-]ibut did not change baseline [Cl-]imeasured in the presence of TTX. WNK463 enhanced neuronal Cl-extrusion during and after ILDs, before abolishing ILDs. Pharmacological inhibition and targeted siRNA silencing demonstrated that the anti-ictal effects of WNK463 involved both NKCC1 and KCC2. Thus, mutual NKCC1 inhibition and KCC2 activation via the WNK-SPAK/OSR1 pathway exert powerful anti-ictal effects by facilitating [Cl-]iextrusion during ILDs.

Contrasting interactions of Cd, Cu, and Zn during uptake and efflux in Daphnia magna.

In migrating cells, the GTPase Rac organizes a protrusive front, whereas Rho organizes a contractile back. How these GTPases are positioned at opposite poles remains unclear. We leverage optogenetics, mechanical perturbations, and mathematical modelling to reveal a surprising mechanochemical long-range mutual activation between front and back polarity programmes that complements their well-known local mutual inhibition. Rac-based protrusions elevate membrane tension, stimulating an mTORC2-dependent activation of Rho at the opposite side of the cell. Conversely, Rho-mediated contractility induces cortical-flow-based regulation of phosphoinositide signalling that triggers Rac activation distally. We develop a minimal mechanochemical model to explain how long-range facilitation, together with local inhibition, enables robust Rho and Rac partitioning. Our findings demonstrate how the actin cortex and plasma membrane interact as an integrated mechanochemical system for long-range Rac-Rho patterning. This circuit is required for efficient polarity and migration in primary human T cells and is conserved in epithelial cells, highlighting the generality of this mechanism.

Sensory neural circuits must encode both the presence and termination of a stimulus. Following odor offset, projection neurons (PNs) in the insect antennal lobe (AL) exhibit transient increases in firing rate, termed OFF responses, yet the circuit mechanisms that generate them in recurrent excitatory-inhibitory networks remain poorly understood. Here, we constructed a biologically-constrained firing rate-based recurrent neural network (RNN) model of the locust AL and trained it on electrophysiological recordings from 110 in vivo PNs to reconstruct their odor-evoked temporal dynamics across five odorants. The trained model faithfully reproduced the firing rates of constrained neurons, while unconstrained PNs and LNs developed biologically plausible temporal response patterns and response-type diversity. Using targeted input and connectivity perturbations, we found that OFF responses arise through two mechanistically distinct pathways. A feedforward pathway transmits offset-type olfactory receptor neuron (ORN) input directly to downstream PNs, while a recurrent pathway generates post-stimulus excitation independently of offset input. Selective perturbation of individual recurrent connections identified LN-LN mutual inhibition as the dominant recurrent pathway, and decomposition of excitatory and inhibitory inputs revealed that it produces net excitation through the transient release of inhibition rather than through increased drive. The two pathways recruit largely non-overlapping PN populations, indicating that OFF response identity is an emergent property of the network state rather than a cell-intrinsic feature. These findings provide a circuit-level account of OFF response generation and demonstrate how data-constrained RNNs can dissect circuit mechanisms directly fromin vivorecordings.

Human exceptional cognition stems from evolutionarily derived cortical adaptations that drive expansive neurogenesis. In this study, we employ the gyrencephalic ferret model to systematically characterize the molecular profiles and lineage dynamics of cortical radial glia (RGs). By applying scRNA-Seq to ferret and human cortices, we identify conserved regulatory programs underlying cortical neurogenesis and gliogenesis. We show that, similar to their human counterparts, ferret cortical outer radial glia (oRGs), exhibit enhanced ERK and PKA signaling. ERK and PKA act in a mutually reinforcing manner to boost oRG self-renewal and neurogenesis, while inhibiting gliogenesis and prolonging the neurogenic period. Furthermore, we identify regional specialization within cortical gliogenic RGs: YAP/TAZ activation drives ventricular zone truncated radial glia (tRGs) toward ependymal glial fate in medial cortex, whereas SHH signaling instructs tRGs within the ventrolateral-to-dorsal cortical axis to generate tripotential intermediate progenitor cells, which serve as a shared source of astrocytes, oligodendrocytes, and cortically-derived olfactory bulb interneurons. Our findings support a model in which cortical neurogenesis, gliogenesis, and evolutionary expansion are co-regulated through an integrated signaling network orchestrated by ERK, PKA, YAP/TAZ, and SHH. This network relies on a precisely balanced interplay of mutual inhibition among these pathways to ensure proper developmental outcomes.

Blue mold decay caused by Penicillium expansum is a major disease of table grapes, causing substantial economic losses. With increasing environmental concern and consumer interest in chemical-free products, eco-friendly biocontrol strategies are necessary. The strains of Wickerhamomyces anomalus incubated with chitosan (WaC) and Bacillus subtilis (Bs) are already reported for their promising efficiency to control blue mold disease caused by P. expansum. However, their individual application is less effective compared to chemical fungicides. The current study determined combined application of these two prominent antagonistic microbes against blue mold decay of grapes. Initially we carried out a compatibility study which confirmed that there was no mutual inhibition among the strains, enabling synergistic formulations. An in vitro study showed that the combined application of WaC and Bs better reduces P. expansum colony diameters at a 4:1 ratio. This ratio also maximally suppressed the pathogen spore germination (62% reduction) and germ tube elongation (67% reduction). The in vivo studies also showed that WaC + Bs (at 4:1) significantly minimized lesion diameters and decay rates of grapes during the 13-day storage, outperforming individual applications. The physicochemical quality parameters of table grapes were also better preserved. The treatments modulated antioxidant and defense enzymatic activities such as PPO, POD, PAL, APX, SOD, and CHI. The elevated phenolic and flavonoid contents, with strong positive correlations among the enzymes, underscored the induced resistance of the host. These findings highlight the synergistic potential of chitosan-enhanced Wa with Bs for effective, sustainable postharvest biocontrol, extending grape shelf life and reducing chemical reliance.

Clayey soils used as engineered barriers in environmental infrastructures are often subjected to coupled thermal (T), mechanical (M), and chemical (C) loadings, which can induce complex consolidation behaviour and influence long-term barrier performance. In this study, the deformation and transport responses of clayey soils under thermo–mechanical–chemical (TMC) coupling are investigated using a previously benchmarked one-dimensional coupled numerical model. Soil settlement behaviour and clay liner performance are analysed under single (T, M, and C), dual (TM, MC, and TC), and triple (TMC) loading conditions. The results reveal distinct deformation characteristics: an initial compression followed by rebound behaviour under chemical loading and an initial expansion followed by contraction under thermal loading. Under combined TMC loading, the settlement process follows a three-stage pattern: initial expansion offset, rapid consolidation, and late-stage rebound. Notably, the interaction among loadings leads to non-additive deformation, highlighting strong mutual inhibition effects. The indicative clay liner thickness varies significantly among different loading scenarios. The thermal loading has the greatest impact on liner thickness, followed by chemical and mechanical loading. These findings offer valuable theoretical insights into soil deformation under multiphysical couplings and provide a scientific basis for optimising barrier design and assessing long-term performance of engineering barriers in contaminated or thermally active environments.

Overcoming the concentration-enantioselectivity trade-off in haloalcohol dehalogenase for high-titer (R)-epichlorohydrin production.

As an important neural network model, the continuous attractor neural network (CANN) demonstrates unique advantages in simulating and explaining the representation and storage mechanisms of continuous variables (such as position, direction, etc.) in the brain. However, in the real brain network, the connections between neurons are not only random or equal, but regulated by various factors. The coding methods and interactions of multiple neuron groups form the collective behavior of the complex brain network. To study the role of complex networks in the brain, this research proposes a selective coupling network model based on CANN, which operates under the dynamic balance between excitatory and inhibitory inputs. In this study, we have investigated the interaction between two classes of CANNs with distinct selective preferences for motion direction recognition under fast excitation and inhibition (E-I) balance. Based on simulation results and theoretical analysis, we found that the fast E-I balance located in the brain can provide indirect linking effects among multiple different networks. The indirect mutual inhibition of the coupled network through E-I balance can promote the accuracy and stability of the network response to a given position. This suggests that a dynamic system of collaborative work activity is possible between different neural networks. We hope that this work could provide insightful references for the development of multi-network coupling in brain-like computing.

Biophysical models of human brain represent the latter as a graph of inter-connected neural regions. Building from the model by Naskar et al. (Network Neuroscience, 2021), our motivation was to understand how these brain regions can be connected at neural level to implement some inhibitory control, which calls for inhibitory connectivity rarely considered in such models. In this model, regions are made of inter-connected excitatory and inhibitory pools of neurons, but are long-range connected only via excitatory pools (mutual excitation). We thus extend this model by generalizing connectivity, and we analyse how connectivity affects the behaviour of this model. Focusing on the simplest paradigm made of a Control area and a Target area, we explore four typical kinds of connectivity: mutual excitation, Target inhibition by Control, Control inhibition by Target, and mutual inhibition. For this, we build an analytical sensitivity framework, nesting up sensitivities of isolated pools, of isolated regions, and of the full system. We show that inhibitory control can emerge only in Target inhibition by Control and mutual inhibition connectivities. We next offer an analysis of how the model sensitivities depends on connectivity structure, depending on a parameter controling the strength of the self-inhibition within Target region. Finally, we illustrate the effect of connectivity structure upon control effectivity in response to an external forcing in the Control area. Beyond the case explored here, our methodology to build analytical sensitivities by nesting up levels (pool, region, system) lays the groundwork for expressing nested sensitivities for more complex network configurations, either for this model or any other one.

Biophysical models of human brain represent the latter as a graph of inter-connected neural regions. Building from the model by Naskar et al. (Network Neuroscience, 2021), our motivation was to understand how these brain regions can be connected at neural level to implement some inhibitory control, which calls for inhibitory connectivity rarely considered in such models. In this model, regions are made of inter-connected excitatory and inhibitory pools of neurons, but are long-range connected only via excitatory pools (mutual excitation). We thus extend this model by generalizing connectivity, and we analyse how connectivity affects the behaviour of this model. Focusing on the simplest paradigm made of a Control area and a Target area, we explore four typical kinds of connectivity: mutual excitation, Target inhibition by Control, Control inhibition by Target, and mutual inhibition. For this, we build an analytical sensitivity framework, nesting up sensitivities of isolated pools, of isolated regions, and of the full system. We show that inhibitory control can emerge only in Target inhibition by Control and mutual inhibition connectivities. We next offer an analysis of how the model sensitivities depends on connectivity structure, depending on a parameter controling the strength of the self-inhibition within Target region. Finally, we illustrate the effect of connectivity structure upon control effectivity in response to an external forcing in the Control area. Beyond the case explored here, our methodology to build analytical sensitivities by nesting up levels (pool, region, system) lays the groundwork for expressing nested sensitivities for more complex network configurations, either for this model or any other one.

Phenotypic heterogeneity is prevalent during aging, yet its underlying molecular drivers remain poorly understood. In budding yeast, two distinct aging trajectories, characterized by either ribosomal DNA (rDNA) instability or mitochondrial decline, have been proposed to be mutually exclusive. Here, we systematically dissect the heterogeneity among aging yeast cells by combining single-cell transcriptomics with longitudinal fluorescence microscopy. Our data reveal distinct transcriptional responses that emerge in aging cells, highlighted by loss of rDNA silencing, a hypoxia response, and the environmental stress response (ESR). Contrary to expectation, we establish that ESR induction is not caused by rDNA instability but is instead a consequence of an early decline in mitochondrial membrane potential. However, the ESR is merely a biomarker of this decline and not itself a determinant of lifespan. While rDNA instability and mitochondrial dysfunction are anticorrelated as terminal phenotypes, we find that they are not necessarily mutually exclusive and can instead proceed concurrently within individual cells. Targeted genetic perturbations that are specific for one pathway do not impinge on the other, which is in contradiction to the idea of mutual inhibition between the two. We therefore propose a "competing hazards model", where independent aging processes progress in parallel, and the observed mode of death is determined by which process first reaches a catastrophic failure point. Our work untangles the causal links between several aging pathways and provides a framework for understanding how distinct aging trajectories emerge from independent molecular events.

Stress can disrupt menstrual cycles, impair fertility and cause reproductive disfunction. The posterodorsal medial amygdala (MePD) integrates stress signals and regulates the gonadotropin-releasing hormone (GnRH) pulse generator through a dense network of GABA and Urocortin-3 (UCN3) neurons, yet the mechanisms underlying the circuitry remain poorly understood. Here, we combine in vivo mini-endoscopic calcium imaging, optogenetics, clustering analysis, and computational modeling to investigate the MePD circuitry in female mice. We uncover two anti-correlated GABA subpopulations in the MePD that are involved in the response to restraint stress and UCN3 neuron stimulation. Computational modeling suggests that mutual inhibition between these GABA groups drives their anti-correlated activity and predicts how these interactions shape downstream responses to stimulation of GABA and UCN3 neurons. In vivo optogenetics confirms that GABA neurons are critical for transmitting UCN3 signals to regulate luteinizing hormone (LH) pulse frequency. Together, our findings reveal amygdala GABAergic circuit mechanisms that mediate stress effects on reproductive health, linking emotional processing and neuroendocrine control.

Microbial interaction has been widely acknowledged as the deterministic factor for microbiota assembly. However, in the microbial environment, such interactions are highly variable and may lead to the random birth, death, and reproduction of neighboring microbes, potentially contributing to stochastic assembly processes. We have developed a Go-board model to simulate and investigate how microbiota assembly is affected by different types of interacting species, interaction strength, and community structure. The infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis (iCAMP) shows that the strong inhibitory effect of deterministic species on stochastic species can lead to a switch of the dominant assembly process from heterogeneous selection to drift. On the other hand, the effects of the inhibition of stochastic species on their deterministic neighbors enhances the relative importance of dispersal limitation in communities with small deterministic populations. The mutual inhibition between deterministic and stochastic species further enhances the stochasticity of microbiota assembly, but this effect is canceled out by the effects of interspecific facilitation and deterministic species with large phylogenetic distance. Our study sheds novel light on the role of microbial interaction in stochastic assembly processes, which is contradictory to the traditional niche-based theory. These findings highlight the importance of assessing interspecific interaction for predicting the true roles of different assembly processes in future studies.

The integrated valorization of whey into multifunctional food ingredients is constrained by sequential processing routes and the need for purified lactose and protein fractions. The simultaneous enzymatic conversion of lactose and whey proteins in a single reactor remains underexplored despite the frequent co-formulation of galacto-oligosaccharides (GOS) and whey protein hydrolysates in functional foods. This study evaluated the feasibility of a one-pot enzymatic system using native whey as the sole substrate for the concurrent production of GOS and antioxidant peptide fractions. A batch process combining β-galactosidase from Aspergillus oryzae and Alcalase® was assessed through a 32 factorial design, analyzing the effects of pH (4.5-6.5) and temperature (40-60 °C) on GOS yield and degree of protein hydrolysis. The system enabled simultaneous transgalactosylation and proteolysis under mildly acidic conditions without significant mutual enzyme inhibition. Multi-response optimization identified pH 6.0 and 59.5 °C as the optimal conditions, yielding 25.7 ± 0.2% GOSs and 10.5 ± 0.3% protein hydrolysis. The antioxidant capacity and emulsifying and foaming properties were strongly dependent on pH, temperature, and reaction time. The results demonstrate that native whey can be directly transformed into a multifunctional ingredient through a one-pot enzymatic strategy, offering a simplified valorization approach.

Aspergillus flavus (A. flavus) and its potent carcinogenic metabolite, aflatoxin B1 (AFB1), pose severe threats to food safety and public health. This study explored the biocontrol potential of Bacillus and Trichoderma strains and their interactions. Through dual-culture assays, Bacillus subtilis Bs92 and Trichoderma citrinoviride GC-T20 were identified as the most inhibitory among 15 isolates each, with their culture filtrates inhibiting A. flavus growth by 48.61% and 74%, respectively. Investigation of the inter-genus interaction revealed strong mutual inhibition: Trichoderma filtrate suppressed Bacillus growth by >90%, while Bacillus filtrate inhibited Trichoderma mycelial growth by 40-90%. To circumvent this antagonism and enhance efficacy, the culture filtrates of Bs92 and GC-T20 were combined. The combined treatment demonstrated superior performance, inhibiting A. flavus radial growth by 69.59% and AFB1 production by 98.69%, significantly outperforming individual applications. These results indicate that the antifungal and anti-aflatoxigenic metabolites produced by Bs92 and GC-T20 are complementary. Their combined use presents a promising synergistic strategy for the biocontrol of A. flavus and AFB1 contamination in food and agricultural products.

Muguka, a high-cathinone cultivar of Catha edulis consumed widely in East Africa, presents a growing health risk when co-administered with diazepam. This theoretical study represents one of the first integrated computational investigations focusing on the interaction between Muguka derived cathinone and diazepam, combining molecular docking, ADMET profiling, and physiologically based pharmacokinetic (PBPK) modeling. The in silico analysis identified overlapping CYP2D6 and CYP2C19 pathways, supporting potential mutual metabolic inhibition. The predictive PBPK models suggest moderate CYP2D6/CYP2C19-mediated drug-drug interactions based on a simulated oral dose of 100 mg cathinone and 30 mg diazepam in a human adult population. Co-administration is predicted to increase cathinone systemic exposure by 1.5-fold (AUC ↑50%) and reduce clearance by 33%, while diazepam exposure is projected to rise by 1.3-fold (AUC ↑30%) with 24% clearance reduction. Molecular docking revealed high-affinity binding of cathinone (-6.4 kcal/mol) at the dopamine transporter (DAT) and diazepam (-6.8 kcal/mol) at the γ-aminobutyric acid-A (GABA-A) receptor, indicating distinct yet potentially complementary CNS targets. Collectively, these computational predictions suggest that co-use may prolong CNS exposure and theoretically enhance neurotoxicity, and dependence risk. This integrated computational framework provides a hypothetical mechanistic evidence for stimulant-benzodiazepine interactions and underscores the need for clinical monitoring and validation.

Tonic inhibition in cerebellar granule cells is crucial for maintaining information coding fidelity during motor coordination. It arises through both activity-dependent and activity-independent mechanisms, and the interplay between these mechanisms changes with age. However, specific molecular and cellular mechanisms and how their change affects network-level computation and motor behavior remain unclear. Here we show that, while net tonic inhibitory current remains unchanged, the main source of tonic γ-aminobutyric acid switches from synaptic spillover (neuronal activity dependent) to astrocytic Best1 (activity independent) throughout adolescence (4–8 weeks) in mice. Computational modeling based on experimental data demonstrated that this switch downregulates the internally generated network activity mediating mutual inhibition between granule cell clusters receiving different inputs, thereby enhancing their independence. Consistent with simulations, three-dimensional posture analysis revealed an age-dependent increase in independent limb movements during spontaneous motion, which was impaired in Best1-knockout mice. Our findings highlight the late-stage development of complex motor coordination driven by the emergence of astrocyte-mediated tonic inhibition.

Multistable perceptual phenomena provide insights into the mind's dynamic states within a stable external environment, and the neural underpinnings of these consciousness changes are often studied with binocular rivalry (BR). Conventional methods to study binocular rivalry suffer from biases and assumptions that limit their ability to describe the continuous nature of these perceptual transitions and to discover what kind of percept was perceived across time. Recently, we developed a new method to avoid those shortcomings, called InFoRM-Rivalry. The method builds customized regions of six principal perceptual categories that are described in the literature, including two exclusive and four mixed perceptual categories, i.e. piecemeal (one) and superimposition (three). We re-analysed data using unsupervised clustering to determine where within these principal categories clusters of perception naturally occur. We show that, on average, 10 ± 8 categories arise and that these categories map predominately onto the exclusive and superimposed principal regions regardless of the stimulus contrast configurations. Next, we estimated the most likely transition pathways during binocular rivalry using a Hidden Markov model and showed that transitions are most likely to appear between monocular exclusive and binocular superimposed categories. These results suggest that binocular rivalry, triggered by low-level grating stimuli, involves conflict between monocular and binocular neural processing sites rather than only mutual inhibition of monocular sites.