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Microalgae cultivation using wastewater is a combined process for pollutant removal and lipid production that has been widely studied in recent years. In this study, the effects of anaerobic membrane effluent (AME) and municipal wastewater (MW) ratios on microalgae growth and pollutant removal processes were investigated, and the lipid production properties were also explored. Results show that microalgae can grow in all AME/WW ratios, and a 40% AME content is the optimal condition for microalgal biomass accumulation (52.9 mg/L·d) and lipid production (0.378 g/L). Higher AME addition would inhibit microalgae growth. In addition, high ammonia (approximately 97%) and phosphate (around 90%) removal efficiencies can be achieved in all AME/WW ratio conditions, while the total nitrogen removal efficiencies decreased with the addition of AME. Total nitrogen and phosphate are the limiting factors in treating water to meet the requirements of the integrated wastewater discharge standard. This study provided a new method for anaerobic digestion and municipal wastewater treatment and also realized green energy production based on the sustainable development principles.

Low circulating levels of adiponectin are associated with increased inflammation in a wide-range of disease states. In particular, this applies to obesity-related diseases such as type 2 diabetes, heart failure and non-alcoholic fatty liver disease. Numerous studies have shown that adiponectin exerts anti-inflammatory and beneficial metabolic effects. Hence there has been tremendous interest in developing adiponectin-based therapeutics. Here we examined the effect of ALY688, a small peptide adiponectin receptor agonist, on lipopolysaccharide (LPS)-driven inflammation in vivo and in vitro. We show that ALY688 administration significantly diminished LPS-driven production of pro-inflammatory cytokines and chemokines (i.e., IL-1β, TNF-α, IL-12, IFN-β, MCP-1, KC, RANTES) in mice. Moreover, mice injected with ALY688 exhibited a rapid increase in the anti-inflammatory cytokine, TGF-β. Apart from an increase in total CD3+ T cells, there were no marked changes in the circulating immune cells following ALY688 injection. No alterations in cytokine profile was seen in normal mice given ALY688, suggesting that the effects of ALY688 are context-dependent. Mechanistically, we employed phospho-flow cytometry to demonstrate that circulating immune cells responded rapidly to ALY688 injection by upregulating p-AMPK and p-P38, two well established adiponectin downstream signaling events. These results were confirmed in human peripheral blood mononuclear cells (PBMCs), where ALY688 treatment led to a robust increase in phospho-AMPK and phospho-P38. Altogether, these results show that the adiponectin agonist, ALY688, has strong anti-inflammatory effects by triggering AMPK and P38 activation in vivo and in vit Canadian institutes of Health Research & Allysta Pharmaceuticals This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Objectives Regular physical exercise can improve insulin resistance in insulin target tissues. However, the mechanisms about the beneficial effect of exercise on insulin resistance are not yet fully resolved. This study was carried out to address whether insulin resistance improvement by exercise is involved in an anti-inflammatory pathway in the spleen in high-fat diet (HFD) feeding mice. Methods Male C57Bl/6J mice with or without subdiaphragmatic vagotomy (sVNS) were subjected to medium-intensity treadmill exercise during HFD feeding. Glucose tolerance test and insulin tolerance test were detected, and spleen acetylcholine level, choline acetyltransferase activity (ChAT), protein kinase C (PKC) and tumor necrosis factor-alpha (TNF-α) were assayed. Results We found that exercise significantly improves HFD-induced glucose intolerance and insulin resistance, along with an increase in acetylcholine level, ChAT activity, and PKC activity, and decrease in TNF-α level in the system and the spleen from HFD-fed mice. However, sVNS abolished the beneficial effect of exercise on glucose intolerance and insulin resistance, decreased acetylcholine level, ChAT activity, and PKC activity, and increase TNF-α level of the spleen in HFD-mice exercise intervention. Conclusions These data reveal that the prevention of HFD-associated insulin resistance by exercise intervention involves reducing splenic TNF-α level, which is mediated by cholinergic anti-inflammatory activity via influencing PKC activity, ChAT activity, and acetylcholine concentration in mice spleen.

It has been recommended that physical activity be a part of treatment and management regimens of type 2 diabetes mellitus (T2DM), and research has shown that regular physical exercise facilitates glycemic control in these patients. In this analysis, our aim was to systematically show the therapeutic effects of mild to moderate intensity aerobic exercise on glycemic control in patients with T2DM. From February to April 2021, we searched the https://www.clinicaltrials.gov , EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science and Google Scholar databases for trials that showed the effects of aerobic exercise on glycemic control in patients with T2DM. Glycated hemoglobin (HbA1c) was the endpoint in the analysis. The RevMan version 5.4 statistical program was used for statistical analysis, and the mean difference (MD) and 95% confidence intervals (CI) used to represent the data following analysis. Eighteen trials involving 972 participants with T2DM were included in this meta-analysis, of whom 523 were assigned to an exercise group and 449 were assigned to a control group. A comparison pre- versus post-aerobic exercise showed that aerobic exercise significantly improved glycemic control (HbA1c) (MD 0.35, 95% CI 0.23–0.48; P = 0.00001) in these patients with T2DM. A second comparison, T2DM participants in the experimental group post-exercise versus T2DM participants from the control group at the end of the follow-up, also showed that aerobic exercise significantly improved glycemic control (MD − 0.46, 95% CI − 0.69 to − 0.22; P = 0.0001). However, a comparison of HbA1c of T2DM participants in the control group at the beginning of the study compared to those at the end of follow-up did not show any significant improvement in glycemic control (MD 0.08, 95% CI − 0.05 to 0.21; P = 0.21). The current analysis showed that mild to moderate intensity aerobic exercise significantly improved glycemic control in patients with T2DM. Patients with T2DM who regularly participated in aerobic exercise activities had a better control of their disease than those who were not on a regular aerobic exercise regimen. These results lead to the recommendation that at least mild to moderate intensity aerobic exercise should be included in the treatment and management regimens of patients with T2DM.

Yingna Chen,1 Jieya Lu,2 Zhihao Xie,1 Jialing Tang,1 Xuejiao Lian,1 Xiuwen Li1 1School of Pharmacy, School of Medicine, Changzhou University, Changzhou, Jiangsu, People’s Republic of China; 2Department of Nephrology, Yixing Hospital of Traditional Chinese Medicine, Yixing, Jiangsu, People’s Republic of ChinaCorrespondence: Yingna Chen, School of Pharmacy, School of Medicine, Changzhou University, No. 21, Lake Gehu Road, Wujin District, Changzhou, Jiangsu, People’s Republic of China, Tel +86-13813661630, Email chenyingna@cczu.edu.cn Jieya Lu, Department of Nephrology, Yixing Hospital of Traditional Chinese Medicine, 128 Yangquan East Road, Yicheng Street, Yixing, Jiangsu, People’s Republic of China, Tel +86-15906153777, Email ljy7011645@sina.comBackground: Tumor microenvironment has attracted more and more attention in oncology. Alisol B23 acetate (AB23A) inhibits the proliferation of tumor cells including non-small cell lung cancer (NSCLC) cells. However, whether AB23A plays a role in the tumor microenvironment of NSCLC still remains obscure.Methods: After THP-1 cells were polarized to M0 type by PMA, M0 macrophages were differentiated into M1 by LPS and IFNγ, and were differentiated into M2 by IL-4 and IL-13. The differentiation of THP-1 cells was detected by flow cytometry. After AB23A was given to macrophage RT-qPCR and ELISA detected the expressions of IL-6, IL-1β, IL-10 and TGF-β. Western blot and RT-qPCR detected the expressions of CD11b and CD18 at both mRNA and protein levels. Lung cancer cell A549 cells were induced by above related macrophage culture medium. Cell proliferation was detected by CCK-8. Tunel, wound healing and Transwell detected the apoptotic, migration and invasion capabilities. Next, M0 and M1-type macrophages were cultured in the cell culture medium of conventional A549 cells, to which AB23A was added. Subsequently, cell differentiation and inflammatory response were measured. Finally, the expression of CD18 in A549 cells was knocked down to construct NSCLC tumor-bearing mice and AB23A was applied for intragastric administration. Immunohistochemistry detected the polarization of macrophages in tumor tissues. Western blot detected the expressions of CD11b, CD18, invasion-, migration- and apoptosis-related proteins.Results: AB23A promoted the polarization of macrophages towards M1, thus promoting the apoptosis and inhibiting the invasion and migration of A549 cells. The tumor cell culture medium induced M0 macrophages to M2, while AB23A reversed this effect. AB23A targeted CD11b/CD18 and improved the polarization of macrophages, thereby affecting tumor invasion, migration and apoptosis.Conclusion: AB23A affected the polarization of tumor-associated macrophages through the targeted regulation of CD11b/CD18, thus inhibiting the development of lung cancer.Keywords: Alisol B23 acetate, lung cancer, CD11b/CD18, tumor microenvironment

This study aimed to reveal the membrane fouling mechanisms during anaerobic membrane bioreactor (AnMBR) operation for swine wastewater treatment under different organic loading rates (OLR). Results showed that AnMBR could achieve high pollutant removal (71.9-83.6 %) and energy recovery (0.18-0.23 L-CH4/g-COD) at an OLR range of 0.25-0.5 g-COD/g-VSS.d, realizing energy production. However, higher OLR would aggravate the membrane fouling due to accumulation of fine sludge particles, organic foulants, and extracellular polymeric substances (EPS) on cake layer. Based on the high-throughput sequencing, microbial communities significantly changed and fouling-causing bacteria (e.g. Pseudomonas, Methanosarcina and Methanothrix) enriched in the cake layer at higher OLR conditions, leading to lower membrane permeability. Backwash can effectively remove the cake layer from the membrane surface and recover membrane permeability. The present study provides important information about membrane fouling and microbial information that could have significant impact on large-scale AnMBR application.

The whale optimization algorithm is based on the bubble-net attacking behavior of humpback whales and simulates encircling prey, bubble-net attacking and searching for prey to obtain the global optimal solution. However, the basic whale optimization algorithm has the disadvantage of search stagnation, easily falls into a local optimum, has slow convergence speed and has low calculation accuracy. The Levy flight strategy is beneficial for expanding the search range and prevents the algorithm from falling into a local optimum, which enhances the global search ability. The ranking-based mutation operator can increase the selection probability and accelerate the convergence speed to enhance the local search ability. To overcome these shortcomings and avoid premature convergence, the Levy flight strategy and the ranking-based mutation operator are added to the whale optimization algorithm. In this paper, an enhanced whale optimization algorithm is proposed, which realizes complementary advantages to balance exploration and exploitation. Eighteen benchmark test functions and five structural engineering design problems are used to verify the robustness and overall optimization performance of the enhanced whale optimization algorithm. The experimental results show that the enhanced whale optimization algorithm is an effective and feasible method that has a fast convergence speed, high calculation accuracy, strong robustness and stability.

MnZn ferrites were prepared by sol–gel combustion method and coated on flaky FeSiAl particles to decrease the complex permittivity. Surface morphology, phase, and element composition were carried out in terms of scanning electron microscope, transmission electron microscope, X-ray diffraction, Raman spectra, and energy-dispersive X-ray spectroscopy, respectively. Soft magnetic properties were measured by vibrating sample magnetometer. The electromagnetic parameter and reflection loss were also assessed by using vector network analyzer. The results show that the complex permittivity of flaky FeSiAl composites can be well decreased by adjusting the amount of MnZn ferrites. The complex permittivity was decreased obviously, but the complex permeability was decreased slightly after coating; thus, the impedance of composites could reach an ideal matching. When the coating amount was 2.5 g sol, the minimum value of reflection loss (RL) decreased to − 24.3 dB at 11.8 GHz, and the bandwidth of RL exceeding − 10 dB reaches to 3.6 GHz.

In this paper, a water wave optimization (WWO) algorithm is proposed to solve the autonomous underwater vehicle (AUV) path planning problem to obtain an optimal or near-optimal path in the marine environment. Path planning is a prerequisite for the realization of submarine reconnaissance, surveillance, combat and other underwater tasks. The WWO algorithm based on shallow wave theory is a novel evolutionary algorithm that mimics wave motions containing propagation, refraction and breaking to obtain the global optimization solution. The WWO algorithm not only avoids jumps out of the local optimum and premature convergence but also has a faster convergence speed and higher calculation accuracy. To verify the effectiveness and feasibility, the WWO algorithm is applied to solve the randomly generated threat areas and generated fixed threat areas. Compared with other algorithms, the WWO algorithm can effectively balance exploration and exploitation to avoid threat areas and reach the intended target with minimum fuel costs. The experimental results demonstrate that the WWO algorithm has better optimization performance and is robust.

The accuracy and stability of relative pose estimation of an autonomous underwater vehicle (AUV) and a target depend on whether the characteristics of the underwater image can be accurately and quickly extracted. In this paper, a whale optimization algorithm (WOA) based on lateral inhibition (LI) is proposed to solve the image matching and vision-guided AUV docking problem. The proposed method is named the LI-WOA. The WOA is motivated by the behavior of humpback whales, and it mainly imitates encircling prey, bubble-net attacking and searching for prey to obtain the globally optimal solution in the search space. The WOA not only balances exploration and exploitation but also has a faster convergence speed, higher calculation accuracy and stronger robustness than other approaches. The lateral inhibition mechanism can effectively perform image enhancement and image edge extraction to improve the accuracy and stability of image matching. The LI-WOA combines the optimization efficiency of the WOA and the matching accuracy of the LI mechanism to improve convergence accuracy and the correct matching rate. To verify its effectiveness and feasibility, the WOA is compared with other algorithms by maximizing the similarity between the original image and the template image. The experimental results show that the LI-WOA has a better average value, a higher correct rate, less execution time and stronger robustness than other algorithms. The LI-WOA is an effective and stable method for solving the image matching and vision-guided AUV docking problem.

The water wave optimization (WWO) algorithm is inspired by shallow water wave theory and mainly simulates propagation, refraction and breaking to obtain the global optimal solution in the search space. Due to its premature convergence and low optimization efficiency, the basic WWO has a slow convergence speed and low calculation accuracy. To improve the overall optimization performance of the basic WWO, an enhanced WWO based on the elite opposition-based learning strategy and the simplex method (ESWWO) is proposed to solve the function optimization problem and path planning problem for an autonomous underwater vehicle (AUV). The elite opposition-based learning strategy increases the diversity of the population and enhances the global search ability to avoid falling into the local optimum. The simplex method has a fast search speed and strong local search ability to obtain a very accurate solution. The ESWWO algorithm can not only achieve complementary advantages to improve the optimization efficiency of the basic WWO but can also balance exploration and exploitation to obtain the global optimal solution. For the function optimization problem, the ESWWO has strong stability and robustness, and the fitness values of the ESWWO are better than those of other algorithms. For the AUV path planning problem, the ESWWO can avoid threat areas with a minimum fuel cost to obtain the optimal path. The experimental results show that the overall optimization performance of the ESWWO algorithm is superior to that of other algorithms, and thus, ESWWO is an effective and feasible method for solving the function optimization problem and AUV path planning problem.

Multilevel thresholding is an effective and indispensable technology for image segmentation that has attracted extensive attention in recent years. However, the multilevel thresholding method has some disadvantages, such as a large computational complexity and low segmentation accuracy. Therefore, this paper proposes a whale optimization algorithm (WOA) based on Kapur’s entropy method to solve the image segmentation problem. The WOA can effectively balance exploration and exploitation to avoid falling into premature convergence and obtain the global optimal solution. To verify the segmentation performance of the WOA, a series of experiments on underwater images from the experimental pool of Harbin Engineering University are conducted, and the segmentation results are compared with those of the BA, the FPA, MFO, the MSA, PSO and WWO by maximizing the fitness value of Kapur’s entropy method. The fitness value, peak signal-to-noise ratio (PSNR), structure similarity index (SSIM), execution time and Wilcoxon’s rank-sum test are used to evaluate the overall performance of each algorithm. The experimental results reveal that the WOA is superior to the other comparison algorithms and has a higher segmentation accuracy, better segmentation effect and stronger robustness. In addition, the feasibility and efficiency of the WOA are verified.

In this paper, a hybrid whale optimization algorithm based on the Levy flight strategy (LWOA) and lateral inhibition (LI) is proposed to solve the underwater image matching problem in an unmanned underwater vehicle (UUV) vision system. The proposed image matching technique is called the LI-LWOA. The whale optimization algorithm (WOA) simulates encircling prey, bubble-net attacking and searching for prey to obtain the global optimal solution. The algorithm not only can balance the exploration and exploitation but also has high calculation accuracy. The Levy flight strategy can expand the search space to avoid premature convergence and enhance the global search ability. In addition, the lateral inhibition mechanism is applied to conduct image preprocessing, which enhances the intensity gradient and image characters, and improves the image matching accuracy. The LI-LWOA achieves the complementary advantages of the LWOA and lateral inhibition to improve the image matching accuracy and enhance the robustness. To verify the overall optimization performance of the LI-LWOA, a series of underwater image matching experiments that seek to maximize the fitness value are performed, and the matching results are compared with those of other algorithms. The experimental results show that the LI-LWOA has better fitness, higher matching accuracy and stronger robustness. In addition, the proposed algorithm is a more effective and feasible method for solving the underwater image matching problem.

Multilevel thresholding is a simple and important method for image segmentation in various applications that has drawn widespread attention in recent years. However, the computational complexity increases correspondingly when the threshold levels increase. To overcome this drawback, a modified water wave optimization (MWWO) algorithm with the elite opposition-based learning strategy and the ranking-based mutation operator for underwater image segmentation is proposed in this paper. The elite opposition-based learning strategy increases the diversity of the population and prevents the search from stagnating to improve the calculation accuracy. The ranking-based mutation operator increases the selection probability. MWWO can effectively balance exploration and exploitation to obtain the optimal solution in the search space. To objectively evaluate the overall performance of the proposed algorithm, MWWO is compared with six state-of-the-art meta-heuristic algorithms by maximizing the fitness value of Kapur’s entropy method to obtain the optimal threshold through experiments on ten test images. The fitness value, the best threshold values, the execution time, the peak signal to noise ratio (PSNR), the structure similarity index (SSIM), and the Wilcoxon’s rank-sum test are used as important metrics to evaluate the segmentation effect of underwater images. The experimental results show that MWWO has a better segmentation effect and stronger robustness compared with other algorithms and an effective and feasible method for solving underwater multilevel thresholding image segmentation.

Recent studies highlighted the significance of chronic inflammation, which is mediated in part by toll-like receptors 4 (TLR4), in islet β cell dysfunction by high-glucose exposure. However, about it is unclear whether islet β cell dysfunction in response to high glucose is associated with TLR4. This investigation was designed to address the effect of TLR4 deficiency on insulin secretion in mice in response to acute intravenous glucose load. Hyperglycemic clamp was used to impair insulin secretion, and intraperitoneal glucose tolerance test was carried out to analyze insulin secretion function of islet β cells. Our results showed that TLR4 deficiency repressed insulin secretion impairment in response to acute intravenous glucose load. Compared to wild-type mice, TLR4-/- mice did not exhibit increase of IL-1β and TNF-α level in plasma and pancreatic tissue in response to acute intravenous load of high glucose. However, recombinant IL-1β or TNF-α administration restored insulin secretion impairment induced by high glucose in TLR4-/- mice. Taken together, our results demonstrated that TLR4 activation and subsequent IL-1β and TNF-α production contribute to islet β cell dysfunction in mice in response to acute intravenous load of high glucose, which may provide a theoretical basis for diabetes complication improvement by physical exercise.

Background With the advancement of sequencing technologies, a plethora of noncoding RNA (ncRNA) species have been widely discovered, including microRNAs (miRNAs), circular RNAs (circRNAs), and long ncRNAs (lncRNAs). However, the mechanism of these non-coding RNAs in diseases caused by enterovirus d68 (EV-D68) remains unclear. The goal of this research was to identify significantly altered circRNAs, lncRNAs, miRNAs, and mRNAs pathways in RD cells infected with EV-D68, analyze their target relationships, demonstrate the competing endogenous RNA (ceRNA) regulatory network, and evaluate their biological functions. Methods The total RNAs were sequenced by high-throughput sequencing technology, and differentially expressed genes between control and infection groups were screened using bioinformatics method. We discovered the targeting relationship between three ncRNAs and mRNA using bioinformatics methods, and then built a ceRNA regulatory network centered on miRNA. The biological functions of differentially expressed mRNAs (DEmRNAs) were discovered through GO and KEGG enrichment analysis. Create a protein interaction network (PPI) to seek for hub mRNAs and learn more about protein–protein interactions. The relative expression was verified using RT-qPCR. The effects of Fos and ARRDC3 on virus replication were confirmed using RT-qPCR, virus titer (TCID50/ml), Western blotting. Results 375 lncRNAs (154 upregulated and 221 downregulated), 33 circRNAs (32 upregulated and 1 downregulated), 96 miRNAs (49 upregulated and 47 downregulated), and 239 mRNAs (135 upregulated and 104 downregulated) were identified as differently in infected group compare to no-infected group. A single lncRNA or circRNA can be connected with numerous miRNAs, which subsequently coregulate additional mRNAs, according to the ceRNA regulatory network. The majority of DEmRNAs were shown to be connected to DNA binding, transcription regulation by RNA polymerase II, transcription factor, MAPK signaling pathways, Hippo signal pathway, and apoptosis pathway, according to GO and KEGG pathway enrichment analysis. The hub mRNAs with EGR1, Fos and Jun as the core were screened through PPI interaction network. We preliminarily demonstrated that the Fos and ARRDC3 genes can suppress EV-D68 viral replication in order to further verify the results of full transcriptome sequencing. Conclusion The results of whole transcriptome analysis after EV-D68 infection of RD cells were first reported in this study, and for the first time, a ceRNA regulation network containing miRNA at its center was established for the first time. The Fos and ARRDC3 genes were found to hinder viral in RD cells. This study establishes a novel insight host response during EV-D68 infection and further investigated potential drug targets.

Substrate properties play a key role in promoting the caproate yield through lactate-based carbon chain elongation pathway. In the present study, the effect of lactate-to-acetate (LA/AA) carbon ratio (from 0.5 to 5.0) and substrate loading (in terms of substrate/inoculum ratio within the range 20–180 mmol-C/g-VSS) on caproate fermentation was investigated. Results showed that both caproate content and yield increased by increasing the LA/AA ratio up to 3.0, then decreased at higher ratios due to activation of acrylate pathway and dispersion of carbon flux at elevated lactate content. At the optimal LA/AA carbon ratio of 3.0, substrate loading lower than 100 mmol-C/g-VSS was beneficial for efficient substrate utilization with low caproate selectivity, while higher substrate-to-inoculums (S/I) ratio led to incomplete substrate utilization and dispersed carbon flow, which finally reduced the caproate yield. Thus, the highest caproate yield of 0.42 g-COD/g-COD and selectivity of 49.5% were recorded at LA/AA and S/I ratio ratios of 3.0 and 100 mmol-C/g-VSS, respectively. The present study further depictures the novel approach for caproate production with lactate.