Adaptation and robustness in a chemotaxis network

Adaptation is a behavior of biological systems in which a sustained change in input signal leads to a transient output response that returns to the pre--‐stimulated output level. Cells use adaptation to maintain sensitivity to the changes in their environment and to remain in homeostasis while the input signal is perturbed. Signaling networks in both prokaryotic and eukaryotic cells demonstrate adaptation, which is a common feature of chemotaxis, a signal transduction process that enables cells to sense chemical gradients in their extracellular environment and to adjust their movement in response. In the case of Escherichia coli, the bacteria swim in random directions in the absence of a chemical gradient, but will move toward or away from the chemical when a gradient exists. In this study, we use computational methods to study adaptation in the chemotaxis network of Escherichia coli. Based on the well--‐characterized two--‐state model of Barkai and Leibler (Nature 1997), we numerically analyze the chemotactic network with ordinary differential equations and measure the adaptation time and precision of the response to a change in ligand concentration. The adaptation time is the time that the signal takes to reach steady--‐state after a perturbation in input, and precision measures the difference between output and input levels. We find that the network exhibits a sensitive response and precise adaptation to the input stimulus. We also analyze the robustness of the network by randomly varying the kinetic parameters and characterizing the change in behavior. The adaptation demonstrates robustness: although the adaption time varies over a wide range, the precision is nearly perfect regardless of the values of the parameters. This shows that adaptation in this network depends more strongly on the topology of the network than on the values of kinetic parameters

Regorafenib induces Bim-mediated intrinsic apoptosis by blocking AKT-mediated FOXO3a nuclear export

Abstract Regorafenib (REGO) is a synthetic oral multi-kinase inhibitor with potent antitumor activity. In this study, we investigate the molecular mechanisms by which REGO induces apoptosis. REGO induced cytotoxicity, inhibited the proliferation and migration ability of cells, and induced nuclear condensation, and reactive oxygen species (ROS)-dependent apoptosis in cancer cells. REGO downregulated PI3K and p-AKT level, and prevented FOXO3a nuclear export. Most importantly, AKT agonist (SC79) not only inhibited REGO-induced FOXO3a nuclear localization and apoptosis but also restored the proliferation and migration ability of cancer cells, further demonstrating that REGO prevented FOXO3a nuclear export by deactivating PI3K/AKT. REGO treatment promotes Bim expression via the FOXO3a nuclear localization pathway following PI3K/AKT inactivation. REGO induced Bim upregulation and translocation into mitochondria as well as Bim-mediated Bax translocation into mitochondria. Fluorescence resonance energy transfer (FRET) analysis showed that REGO enhanced the binding of Bim to Bak/Bax. Knockdown of Bim, Bak and Bax respectively almost completely inhibited REGO-induced apoptosis, demonstrating the key role of Bim by directly activating Bax/Bak. Knockdown of Bax but not Bak inhibited REGO-induced Drp1 oligomerization in mitochondria. In conclusion, our data demonstrate that REGO promotes apoptosis via the PI3K/AKT/FOXO3a/Bim-mediated intrinsic pathway

A New Few-Shot Learning Method of Bacterial Colony Counting Based on the Edge Computing Device

Bacterial colony counting is a time consuming but important task for many fields, such as food quality testing and pathogen detection, which own the high demand for accurate on-site testing. However, bacterial colonies are often overlapped, adherent with each other, and difficult to precisely process by traditional algorithms. The development of deep learning has brought new possibilities for bacterial colony counting, but deep learning networks usually require a large amount of training data and highly configured test equipment. The culture and annotation time of bacteria are costly, and professional deep learning workstations are too expensive and large to meet portable requirements. To solve these problems, we propose a lightweight improved YOLOv3 network based on the few-shot learning strategy, which is able to accomplish high detection accuracy with only five raw images and be deployed on a low-cost edge device. Compared with the traditional methods, our method improved the average accuracy from 64.3% to 97.4% and decreased the False Negative Rate from 32.1% to 1.5%. Our method could greatly improve the detection accuracy, realize the portability for on-site testing, and significantly save the cost of data collection and annotation over 80%, which brings more potential for bacterial colony counting

In Situ DRIFTS Investigation on CeO_x Catalyst Supported by Fly-Ash-Made Porous Cordierite Ceramics for Low-Temperature NH₃-SCR of NO_X

A series of CeOx catalysts supported by commercial porous cordierite ceramics (CPCC) and synthesized porous cordierite ceramics (SPCC) from fly ash were prepared for selective catalytic reduction of NOx with ammonia (NH3-SCR). A greater than 90% NOx conversion rate was achieved by the SPCC supported catalyst at 250−300 °C when the concentration of loading precursor was 0.6 mol/L (denoted as 0.6Ce/SPCC), which is more advantageous than the CPCC supported ones. The EDS mapping results reveal the existence of evenly distributed impurities on the surface of SPCC, which hence might be able to provide more attachment sites for CeOx particles. Further measurements with temperature programmed reduction by hydrogen (H2-TPR) demonstrate more reducible species on the surface of 0.6Ce/SPCC, thus giving rise to better NH3-SCR performance at a low-temperature range. The X-ray photoelectron spectroscopy (XPS) analyses reveal that the Ce atom ratio is higher in 0.6Ce/SPCC, indicating that a higher concentration of catalytic active sites could be found on the surface of 0.6Ce/SPCC. The in situ diffused reflectance infrared fourier transform spectroscopy (DRIFTS) results indicate that the SCR reactions over 0.6Ce/SPCC follow both Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) mechanisms. Hence, the SPCC might be a promising candidate to provide support for NH3-SCR catalysts, which also provide a valuable approach to recycling the fly ash

Mechanistic and Experimental Study of the CuxO@C Nanocomposite Derived from Cu3(BTC)2 for SO2 Removal

A tunable and efficient strategy was adopted to synthesize highly porous nano-structured CuO−carbonized composites (CuxO@C) using Cu3(BTC)2 as a sacrificial template. The as-synthesized CuO nanocomposites exhibited hollow octahedral structures, a large surface area (89.837 m2 g−1) and a high proportion of Cu2O active sites distributed on a carbon frame. Based on DFT calculations, both the Cu atoms on the surface (CuS) and oxygen vacancy (OV) exhibited strong chemical reactivity. On the perfect CuO (111), the CuS transferred charge to O atoms on the surface and SO2 molecules. A strong adsorption energy (−1.41 eV) indicated the existence of the chemisorption process. On the oxygen-deficient CuO (111), the O2 preferably adsorbed on OV and then formed SO3 by bonding with SO2, followed by the cleavage of the O−O bond. Furthermore, the CuO nanocomposites exhibited an excellent ratio of S/Cu in SO2 removal experiments compared with CuO nanoparticles produced by coprecipitation

Mechanistic and Experimental Study of the Cu_xO@C Nanocomposite Derived from Cu₃(BTC)₂ for SO₂ Removal

A tunable and efficient strategy was adopted to synthesize highly porous nano-structured CuO−carbonized composites (CuxO@C) using Cu3(BTC)2 as a sacrificial template. The as-synthesized CuO nanocomposites exhibited hollow octahedral structures, a large surface area (89.837 m2 g−1) and a high proportion of Cu2O active sites distributed on a carbon frame. Based on DFT calculations, both the Cu atoms on the surface (CuS) and oxygen vacancy (OV) exhibited strong chemical reactivity. On the perfect CuO (111), the CuS transferred charge to O atoms on the surface and SO2 molecules. A strong adsorption energy (−1.41 eV) indicated the existence of the chemisorption process. On the oxygen-deficient CuO (111), the O2 preferably adsorbed on OV and then formed SO3 by bonding with SO2, followed by the cleavage of the O−O bond. Furthermore, the CuO nanocomposites exhibited an excellent ratio of S/Cu in SO2 removal experiments compared with CuO nanoparticles produced by coprecipitation

Rapid Antibiotic Adsorption from Water Using MCM-41-Based Material

The contamination of antibiotics in the environment has raised serious concerns, impacting both human life and ecosystems. This has led to a growing focus on the development of cost-effective and environmentally friendly adsorbent materials. Mesoporous molecular sieve MCM-41, known for its strong adsorption capacity, low cost, and efficient regenerative properties, holds significant promise for addressing this issue. In this study, we investigated the adsorption behavior of demolded MCM-41 materials in relation to tetracycline, doxycycline, and levofloxacin at different temperatures and pH levels. Our experiments encompassed the adsorption of these three common antibiotics, revealing that a neutral or weakly acidic pH environment promoted adsorption, whereas alkaline conditions hindered it. Utilizing the equilibrium isotherm model, we determined the theoretical maximum adsorption capacities for tetracycline (TC), doxycycline (DOX), and levofloxacin (LFX) as 73.41, 144.83, and 33.67 mg g−1, respectively. These findings underscore the significant potential of MCM-41 in mitigating antibiotic wastewater contamination

A Rapid Digital PCR System with a Pressurized Thermal Cycler

We designed a silicon-based fast-generated static droplets array (SDA) chip and developed a rapid digital polymerase chain reaction (dPCR) detection platform that is easy to load samples for fluorescence monitoring. By using the direct scraping method for sample loading, a droplet array of 2704 microwells with each volume of about 0.785 nL can be easily realized. It was determined that the sample loading time was less than 10 s with very simple and efficient characteristics. In this platform, a pressurized thermal cycling device was first used to solve the evaporation problem usually encountered for dPCR experiments, which is critical to ensuring the successful amplification of templates at the nanoliter scale. We used a gradient dilution of the hepatitis B virus (HBV) plasmid as the target DNA for a dPCR reaction to test the feasibility of the dPCR chip. Our experimental results demonstrated that the dPCR chip could be used to quantitatively detect DNA molecules. Furthermore, the platform can measure the fluorescence intensity in real-time. To test the accuracy of the digital PCR system, we chose three-channel silicon-based chips to operate real-time fluorescent PCR experiments on this platform

Additional file 1 of Comparison of the clinical characteristics in parents and their children in a series of family clustered Mycoplasma pneumoniae infections

Additional file 1: Supplemental table 1. Epidemic characteristics of MP infection in adults and children from Oct. 2022 to Oct. 2023