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The gut microbiota’s metabolome is composed of bioactive metabolites that confer disease resilience. Probiotics’ therapeutic potential hinges on their metabolome altering ability; however, characterizing probiotics’ metabolic activity remains a formidable task. In order to solve this problem, an artificial model of the human gastrointestinal tract is introduced coined the ABIOME (A Bioreactor Imitation of the Microbiota Environment) and used to predict probiotic formulations’ metabolic activity and hence therapeutic potential with machine learning tools. The ABIOME is a modular yet dynamic system with real-time monitoring of gastrointestinal conditions that support complex cultures representative of the human microbiota and its metabolome. The fecal-inoculated ABIOME was supplemented with a polyphenol-rich prebiotic and combinations of novel probiotics that altered the output of bioactive metabolites previously shown to invoke anti-inflammatory effects. To dissect the synergistic interactions between exogenous probiotics and the autochthonous microbiota a multivariate adaptive regression splines (MARS) model was implemented towards the development of optimized probiotic combinations with therapeutic benefits. Using this algorithm, several probiotic combinations were identified that stimulated synergistic production of bioavailable metabolites, each with a different therapeutic capacity. Based on these results, the ABIOME in combination with the MARS algorithm could be used to create probiotic formulations with specific therapeutic applications based on their signature metabolic activity.

Gulf War Illness (GWI) is a chronic multisymptom disorder that affects approximately 25–32% of Gulf War veterans and is characterized by a number of symptoms such as cognitive impairment, psychiatric disturbances, chronic fatigue and gastrointestinal distress, among others. While the exact etiology of GWI is unknown, it is believed to have been caused by toxic exposures encountered during deployment in combination with other factors such as stress. In the present study we sought to evaluate the hypothesis that exposure to the toxin permethrin could prime neuroinflammatory stress response and elicit psychiatric symptoms associated with GWI. Specifically, we developed a mouse model of GWI, to evaluate the effects of chronic permethrin exposure followed by unpredictable stress. We found that subjecting mice to 14 days of chronic permethrin exposure followed by 7 days of unpredictable stress resulted in the development of depression-like behavior. This behavioral change coincided with distinct alterations in the microglia phenotype, indicating microglial activation in the hippocampus. We revealed that blocking microglial activation through Gi inhibitory DREADD receptors in microglia effectively prevented the behavioral change associated with permethrin and stress exposure. To elucidate the transcriptional networks impacted within distinct microglia populations linked to depression-like behavior in mice exposed to both permethrin and stress, we conducted a single-cell RNA sequencing analysis using 21,566 single nuclei collected from the hippocampus of mice. For bioinformatics, UniCell Deconvolve was a pre-trained, interpretable, deep learning model used to deconvolve cell type fractions and predict cell identity across spatial datasets. Our bioinformatics analysis identified significant alterations in permethrin exposure followed by stress-associated microglia population, notably pathways related to neuronal development, neuronal communication, and neuronal morphogenesis, all of which are associated with neural synaptic plasticity. Additionally, we observed permethrin exposure followed by stress-mediated changes in signal transduction, including modulation of chemical synaptic transmission, regulation of neurotransmitter receptors, and regulation of postsynaptic neurotransmitter receptor activity, a known contributor to the pathophysiology of depression in a subset of the hippocampal pyramidal neurons in CA3 subregions. Our findings tentatively suggest that permethrin may prime microglia towards a state of inflammatory activation that can be triggered by psychological stressors, resulting in depression-like behavior and alterations of neural plasticity. These findings underscore the significance of synergistic interactions between multi-causal factors associated with GWI.

Background Mushrooms are well recognized for their culinary properties as well as for their potency to enhance immune response. In the present study, we evaluated anti-inflammatory properties of an edible oyster mushroom ( Pleurotus ostreatus ) in vitro and in vivo . Methods RAW264.7 murine macrophage cell line and murine splenocytes were incubated with the oyster mushroom concentrate (OMC, 0-100 μg/ml) in the absence or presence of lipopolysacharide (LPS) or concanavalin A (ConA), respectively. Cell proliferation was determined by MTT assay. Expression of cytokines and proteins was measured by ELISA assay and Western blot analysis, respectively. DNA-binding activity was assayed by the gel-shift analysis. Inflammation in mice was induced by intraperitoneal injection of LPS. Results OMC suppressed LPS-induced secretion of tumor necrosis factor-α (TNF-α, interleukin-6 (IL-6), and IL-12p40 from RAW264.7 macrophages. OMC inhibited LPS-induced production of prostaglandin E2 (PGE 2 ) and nitric oxide (NO) through the down-regulation of expression of COX-2 and iNOS, respectively. OMC also inhibited LPS-dependent DNA-binding activity of AP-1 and NF-κB in RAW264.7 cells. Oral administration of OMC markedly suppressed secretion of TNF-α and IL-6 in mice challenged with LPS in vivo . Anti-inflammatory activity of OMC was confirmed by the inhibition of proliferation and secretion of interferon-γ (IFN-γ), IL-2, and IL-6 from concanavalin A (ConA)-stimulated mouse splenocytes. Conclusions Our study suggests that oyster mushroom possesses anti-inflammatory activities and could be considered a dietary agent against inflammation. The health benefits of the oyster mushroom warrant further clinical studies.

In this study, two different research methods are applied to investigate the evolution mechanism and rainfall warning criteria for Maijianwo slope located in Henan Province, China. On the one hand, an indoor-model test is performed under artificial rainfall and based on similarity theory. A set of monitoring system is utilized to track the moisture content, deformation and cracks of critical points of the model during the test. On the other hand, the numerical simulation is carried out to provide an insight into the variation of unstable zone and factor of safety for the landslide with the increasing cumulative rainfall. Results indicate that the evolution process of Maijianwo slope is composed of three stages of initiating, accelerating and failure respectively, and stability of slope decreases gradually as cumulative rainfall increases. Based on the evolution mechanism of retrogressive landslide verified by both model test and numerical simulation, cracking time of critical positions on the slope prior to each stage were set as the initiating time of each stage and the cumulative rainfall associated with each initiating time (E 1  = 75 mm, E 2  = 180 mm) has been defined as the warning criteria for the Maijianwo slope. As the cumulative rainfall in Maijianwo slope reaches 75 and 180 mm, the landslide orange and red warning codes are issued, respectively. Otherwise, the slope is in a safe condition when the cumulative rainfall is less than 75 mm.

Abstract PurposeThyroid hormone withdrawal (THW) inevitably induced hypothyroidism in patients with differentiated thyroid cancer (DTC), and we aimed to evaluate the safety and efficacy of a novel recombinant human thyroid-stimulating hormone (rhTSH, ZGrhTSH) as an alternative of THW in China.MethodsTotally, 64 DTC patients were enrolled with 24 in the dose-escalation cohort equally grouped into 0.9 mg × 1 day, 0.9 mg × 2 day, 1.8 mg × 1 day, and 1.8 mg × 2 day dosage, and 40 further enrolled into 0.9 mg × 2 day dose-expansion cohort. All patients underwent both ZGrhTSH phase and levothyroxine (L-T4) withdrawal phase for self-comparison in terms of TSH levels, the radioactive iodine (RAI) uptake, stimulated thyroglobulin level, and the quality of life (QoL).ResultsIn ZGrhTSH phase, no major serious adverse events were observed, and mild symptoms of headache were observed in 6.3%, lethargy in 4.7%, and asthenia in 3.1% of the patients, and mostly resolved spontaneously within 2 days. Concordant RAI uptake was noticed in 89.1% (57/64) of the patients between ZGrhTSH and L-T4 withdrawal phases. The concordant thyroglobulin level with a cut-off of 1 μg/L was noticed in 84.7% (50/59) of the patients without the interference of anti-thyroglobulin antibody. The QoL was far better during ZGrhTSH phase than L-T4 withdrawal phase, with lower Billewicz (− 51.30 ± 4.70 vs. − 39.10 ± 16.61, P < 0.001) and POMS (91.70 ± 16.70 vs. 100.40 ± 22.11, P = 0.011) scores which indicate the lower the better. Serum TSH level rose from basal 0.11 ± 0.12 mU/L to a peak of 122.11 ± 42.44 mU/L 24 h after the last dose of ZGrhTSH. In L-T4 withdrawal phase, a median of 23 days after L-T4 withdrawal was needed, with the mean TSH level of 82.20 ± 31.37 mU/L. The half-life for ZGrhTSH clearance was about 20 h.ConclusionThe ZGrhTSH held the promise to be a safe and effective modality in facilitating RAI uptake and serum thyroglobulin stimulation, with better QoL of patients with DTC compared with L-T4 withdrawal.

This study analyzed the pollution level, distribution, sources, and ecological impact of six heavy metals (As, Cd, Cr, Cu, Zn and Pb) in soil from Linli County, China. The concentration analysis showed that the concentration of Cd in all samples exceeded the background value, and the exceeding rate reached 100%, while the average concentrations of other elements were similar to the background value, and the exceeding rate was under 15%. The pollution level of Cd was the most severe according to geo-accumulation index and enrichment factor, while other elements were under mild pollution level. The results of self-organizing map (SOM) and positive matrix factorization (PMF) analysis showed that agricultural activities were one of the main sources of heavy metal elements in soil, and natural weathering and industrial pollution could also lead to soil pollution. Cd appeared to be the most significant pollutant element in the soil of Linli County, and it had the largest impact on the ecological environment. Overall, this study provides guidance for soil pollution control and related policies, aiming to reduce the pollution of heavy metal elements in soil and the hazards to the ecological system caused by agricultural production and industrial activities.

Uterine cervical carcinoma (UCC) is one of the most common malignant tumors in females, and UCC has a close relationship with chronic cervicitis. As the endogenous “braking signal,” lipoxins can regulate anti-inflammation and the resolution of inflammation. We investigated the effect of lipoxin A 4 (LXA 4 ) on the proliferation, apoptosis, and migration in lipopolysaccharide (LPS)-stimulated Hela cells. We demonstrated that LXA 4 could significantly suppress p53, cyclin D1 expression, and migration of LPS-stimulated Hela cells via nuclear factor-κB (NF-κB) pathway, and these effects could be blocked by Boc-2, the specific inhibitor of FPR2/ALX (the receptor of LXA 4 ). We presented evidence for a novel role of LXA 4 on the proliferation and migration in LPS-stimulated Hela cells, and FPR2/ALX was involved in the procedures. These results showed that LXA 4 could be a possible candidate for UCC therapy, and blocking the activation of NF-κB would be an effective drug target.

A numerical model was developed to simulate the jet-flow solid fraction of W18Cr4 V high-speed steel during spray forming. The whole model comprises two submodels: one is an individual droplet model, which describes the motion and thermal behaviors of individual droplets on the basis of Newton’s laws of motion and the convection heat transfer mechanism; the other is a droplet distribution model, which is used to calculate the droplet size distribution. After being verified, the model was used to analyze the effects of parameters, including the initial gas velocity, deposition distance, superheat degree, and the ratio of gas-to-metal mass flow rates, on the jet-flow solid fraction. Finally, an equation to predict the jet-flow solid fraction directly and conveniently according to the parameters was presented. The values predicted by the equation show good agreement with those calculated by the numerical model.