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Mongolian people possess a unique dietary habit characterized by high consumption of meat and dairy products and fewer vegetables, resulting in the highest obesity rate in East Asia. Although obesity is a known cause of type 2 diabetes (T2D), the T2D rate is moderate in this population; this is known as the “Mongolian paradox.” Since the gut microbiota plays a key role in energy and metabolic homeostasis as an interface between food and body, we investigated gut microbial factors involved in the prevention of the co-occurrence of T2D with obesity in Mongolians. We compared the gut microbiome and metabolome of Mongolian adults with obesity with T2D (DO: n = 31) or without T2D (NDO: n = 35). Dysbiotic signatures were found in the gut microbiome of the DO group; lower levels of Faecalibacterium and Anaerostipes which are known as short-chain fatty acid (SCFA) producers and higher levels of Methanobrevibacter, Desulfovibrio, and Solobacterium which are known to be associated with certain diseases. On the other hand, the NDO group exhibited a higher level of fecal SCFA concentration, particularly acetate. This is consistent with the results of the whole shotgun metagenomic analysis, which revealed a higher relative abundance of SCFA biosynthesis-related genes encoded largely by Anaerostipes hadrus in the NDO group. Multiple logistic regression analysis including host demographic parameters indicated that acetate had the highest negative contribution to the onset of T2D. These findings suggest that SCFAs produced by the gut microbial community participate in preventing the development of T2D in obesity in Mongolians.

A wheat gluten fermentation process with the inoculation of different microorganisms under salt-free conditions has the potential to produce varying flavour profiles. As research on the co-fermentation of yeasts and lactic acid bacteria (LAB) in salt-free wheat gluten fermentation is scarce, the current work studied the flavour impact on fermented wheat gluten by the co-inoculation of Latilactobacillus sakei with one yeast (Saccharomyces boulardii or Pichia kluyveri). The results showed that similar glucose and organic acid levels were detected, but early death of yeasts was observed during liquid-state fermentation (LSF) in co-fermentations. The concentrations of most free amino acids were comparable. Volatile compound analysis showed synergistic effects in co-cultured fermentations on the production of certain compounds such as isoamyl acetate. Principal component analysis revealed clear differences in volatile profiles between co-fermentation and single-strain fermentation. Therefore, a fermented sauce produced by co-inoculating LAB and yeast with a new and fruitier flavour was developed.

[C10H11N2+, PF6−], triclinic, P1‾$P\overline{1}$ (no. 2), a = 8.9854(3) Å, b = 9.1004(3) Å, c = 9.2312(3) Å, α = 66.667(3)°, β = 74.875(3)°, γ = 74.024(3)°, V = 656.40(4) Å3, Z = 2, Rgt(F) = 0.0513, wRref(F2) = 0.1515, T = 296(2) K.

Abstract Background The gut microbiome has proven to be an important factor affecting obesity; however, it remains a challenge to identify consistent biomarkers across geographic locations and perform precisely targeted modulation for obese individuals. Results This study proposed a systematic machine learning framework and applied it to 870 human stool metagenomes across five countries to obtain comprehensive regional shared biomarkers and conduct a personalized modulation analysis. In our pipeline, a heterogeneous ensemble feature selection diagram is first developed to determine an optimal subset of biomarkers through the aggregation of multiple techniques. Subsequently, a deep reinforcement learning method was established to alter the targeted composition to the desired healthy target. In this manner, we can realize personalized modulation by counterfactual inference. Consequently, a total of 42 species were identified as regional shared biomarkers, and they showed good performance in distinguishing obese people from the healthy group (area under curve (AUC) =0.85) when demonstrated on validation datasets. In addition, by pooling all counterfactual explanations, we found that Akkermansia muciniphila, Faecalibacterium prausnitzii, Prevotella copri, Bacteroides dorei, Bacteroides eggerthii, Alistipes finegoldii, Alistipes shahii, Eubacterium sp. _CAG_180, and Roseburia hominis may be potential broad-spectrum targets with consistent modulation in the multi-regional obese population. Conclusions This article shows that based on our proposed machine-learning framework, we can obtain more comprehensive and accurate biomarkers and provide modulation analysis for the obese population. Moreover, our machine-learning framework will also be very useful for other researchers to further obtain biomarkers and perform counterfactual modulation analysis in different diseases.

The differences in spatial-temporal distribution patterns and dominant driving factors of vegetation evolution among sub-regions during different historical periods were not clear. Therefore, this study introduced the gravity center model and geodetector to analyze the spatial-temporal change characteristics and dominant driving factors of normalized difference vegetation index (NDVI) in China during 1981–2019 from the perspective of geographic divisions. Results showed that (1) during 1981–2019, the average vegetation coverage in China showed an increasing trend and zones with obviously increasing vegetation NDVI were mainly distributed in the middle reaches of the Yellow River basin and the upper reaches of the Yangtze River. (2) During 1981–2019, the gravity center of national vegetation NDVI was mainly concentrated in Yan’an City and Tongchuan City, showing a southward migration trend as a whole, which indicates that the increment and growth rates of the southern part were greater than those of the northern part. (3) The growth of vegetation in southern China was primarily affected by the temperature, while that of northern China was largely influenced by precipitation. (4) During 1981–2019, the dominant interactive factors of vegetation change for all subregions changed greatly: natural factor (climate or terrain) ∩ other factors → landuse ∩ other factors.

Objective To compare the diagnostic value of contrast-enhanced ultrasound （CEUS） and enhanced magnetic resonance imaging （MRI） in indeterminate pelvic masses. Methods CEUS and MRI were performed on 46 cases of sonographically indeterminate pelvic masses according to International Ovarian Tumor Analysis （IOTA） simple rules. Two independent sonographers and two radiologists reviewed the images before and after combining with medical history and serum tumor markers, respectively. The results of CEUS and MRI were compared with pathologic findings （n = 43） or follow-up data after clinical treatment （n = 3） as gold standard. The diagnostic values of CEUS and MRI before and after combining with medical history and tumor markers were compared. Results The diagnostic accuracy of CEUS in indeterminate pelvic masses was 67.4% without combining with medical history and tumor markers, which was lower than 80.4% of MRI. There was a statistical significance （P < 0.05）. However, there was no statistical significance between them after combining with tumor markers and/or medical history （both P > 0.05）. The accuracy of CEUS combined with medical history and tumor markers in diagnosing pelvic masses was 91.3%, which was statistically different from CEUS without considering any medical histories （P < 0.05）. Conclusion When combining with medical history and tumor markers, CEUS yields an equivalent diagnostic accuracy in differentiating malignant from benign pelvic masses compared with MRI. CEUS has high clinical value for diagnosing indeterminate pelvic masses.

Wheat-gluten, the protein-rich portion of wheat, can be processed to produce a highly savory sauce product after solid and liquid-state fermentation (SSF and LSF) with the inoculation of selected lactic acid bacteria (LAB) and yeast under salt-free condition. However, limited research has been done on the impact of different types of microbes in this process. This work studied the flavour impact on fermented wheat-gluten by the single inoculation of Latilactobacillus sakei or one yeast (Saccharomyces boulardii or Pichia kluyveri). Glucose was depleted during LSF in all treatments. Lactic acid production increased over time in L. sakei-fermented samples but not in yeast-fermented samples. Cysteine, serine and arginine remained low over LSF in L. sakei-fermented samples but increased in yeast-fermented samples. More fruity esters such as isoamyl acetate and isobutyl acetate were detected in samples fermented by P. kluyveri, while S. boulardii boosted the production of alcohols such as 3-methyl butanol and 2-phenylethyl alcohol. Principal component analysis revealed a clear difference in volatile profiles of the samples fermented with different strains. Therefore, the fermented sauce can potentially be processed into different flavor directions, and based on the flavor profile, be used in different food applications.

The human gut microbiome is a complex ecosystem that is closely related to the aging process. However, there is currently no reliable method to make full use of the metagenomics data of the gut microbiome to determine the age of the host. In this study, we considered the influence of geographical factors on the gut microbiome, and a total of 2604 filtered metagenomics data from the gut microbiome were used to construct an age prediction model. Then, we developed an ensemble model with multiple heterogeneous algorithms and combined species and pathway profiles for multi-view learning. By integrating gut microbiome metagenomics data and adjusting host confounding factors, the model showed high accuracy (R2 = 0.599, mean absolute error = 8.33 years). Besides, we further interpreted the model and identify potential biomarkers for the aging process. Among these identified biomarkers, we found that Finegoldia magna, Bifidobacterium dentium, and Clostridium clostridioforme had increased abundance in the elderly. Moreover, the utilization of amino acids by the gut microbiome undergoes substantial changes with increasing age which have been reported as the risk factors for age-associated malnutrition and inflammation. This model will be helpful for the comprehensive utilization of multiple omics data, and will allow greater understanding of the interaction between microorganisms and age to realize the targeted intervention of aging.

Objective To investigate how to choose surgical approaches for juvenile nasopharyngeal angiofibroma (JNA) at stages Ⅰ and Ⅱ, and explore the function and limitation of endoscopic surgery. Methods Clinical data of 20 JNA patients undergoing conventional or endoscopic surgeries in the First Affiliated Hospital of the Army Medical University between January 2002 and December 2018 were collected and retrospectively analyzed. Of them, 9 patients (open surgery group) were given conventional open surgeries (including 5 cases of facial degloving approach and 4 cases of transpalatal approach), and the other 11 patients (endoscopy group) were operated with the aid of endoscopy. The choice of surgical methods, intraoperative blood loss, length of hospitalization, incidence of complications and recurrence, and follow-up data were compared between the 2 groups. Results The enrolled patients were all males, at a mean age of 14.6 years, and pathologically diagnosed with NA. The endoscopy group had less intraoperative blood loss (509 vs 1 072 mL), shorter operation time (135 vs 283 min), shorter length of hospital stay (5.5 vs 10.8 d) and lower recurrence rate (0/11 vs 2/9) when compared to the open surgery group. Conclusion Endoscopic surgery is a safe and reliable technique for JNA, with the advantages of milder traumatic injury, less blood loss, lower recurrence, and shorter hospital stay. Endoscopic surgery after embolization is an ideal method for the treatment of small and medium-sized JNA. For the patients with higher stages of JNA, nasal endoscopy combined with external nasal approach may be considered.

The incidence and prevalence of inflammatory disorders have increased globally, and is projected to double in the next decade. Gut microbiome-based therapeutics have shown promise in ameliorating chronic inflammation. However, they are largely experimental, context- or strain-dependent and lack a clear mechanistic basis. This hinders precision probiotics and poses significant risk, especially to individuals with pre-existing conditions. Molecules secreted by gut microbiota act as ligands to several health-relevant receptors expressed in human gut, such as the G-protein coupled receptors (GPCRs), Toll-like receptor 4 (TLR4), pregnane X receptor (PXR), and aryl hydrocarbon receptor (AhR). Among these, the human AhR expressed in different tissues exhibits anti-inflammatory effects and shows activity against a wide range of ligands produced by gut bacteria. However, different AhR ligands induce varying host responses and signaling in a tissue/organ-specific manner, which remain mostly unknown. The emerging systems biology paradigm, with its powerful in silico tool repertoire, provides opportunities for comprehensive and high-throughput strain characterization. In particular, combining metabolic models with machine learning tools can be useful to delineate tissue and ligand-specific signaling and thus their causal mechanisms in disease and health. The knowledge of such a mechanistic basis is indispensable to account for strain heterogeneity and actualize precision probiotics.

It is well known that the gut microbiota plays an extremely important role in modulating host physiological functions such as immunity and metabolic homeostasis. In recent years, accumulated evidence has revealed that the gut microbiota can regulate the functions of the central nervous system (CNS) through the gut–brain axis, which provides a novel insight into the interactions between the gut and brain. This review focuses on the molecular mechanism of the crosstalk between the gut microbiota and the brain via the gut–brain axis, and on the onset and development of neurological disorders triggered by gut microbiota dysbiosis. These topics are followed by a critical analysis of potential intervention strategies targeting gut microbiota dysbiosis, including the use of probiotics, prebiotics, synbiotics, and diets. While research on the microbiota–gut–brain axis is still in its relative infancy, clarifying the molecular mechanism that underlies how the gut microbiota regulates neurological functions not only holds the promise of revealing potentially novel pathogeneses of neurological disorders, but also may lead to the development of potential diagnosis biomarkers and intervention strategies targeting microbiota dysbiosis for neurological disorders.

Ventral anterior homeobox 2 (VAX2) gene is a key regulating factor for the development of the ventral region of the eye, and has recently attracted much attention from the cancer treatment field. Our study aimed to explore the effect of VAX2 on papillary thyroid carcinoma (PTC).

China is the largest producer and consumer of coal in the world. Qinhuangdao Port is not only the largest coal export port in the world, but also an important coal transportation hub in China. The study of the change of coal price in Qinhuangdao Port is of great significance to the study of the change of coal price in the whole country. In this paper, in order to avoid the large prediction error of a single prediction model, an ARIMA-SVM parallel combination model is constructed, and the appropriate weight ratio of ARIMA and SVM model is obtained by calculation, so as to obtain more reliable prediction results. The results show that the international competitiveness of the domestic coal market is insufficient, the coal trading system is incomplete and depends too much on coal resources. For this reason, the government should promote the adjustment of energy structure, improve the mode of transportation, actively improve the coal futures trading system, and realize the upgrading of coal industry.

In this study, we investigated the inactivation efficacy of endospore-forming bacteria, Bacillus pumilus, irradiated by low-energy X-rays of different beam qualities. The different low-energy X-rays studied had cut-off energies of 50, 100 and 150 keV. Bacillus pumilus spores (in biological indicator strips) were irradiated at step doses between 6.5 to 390 Gy. The resulting bacteria populations were then quantified by a pour plate method. Results showed that X-rays of lower energies were more effective in inactivating bacterial spores. In addition, an increment in bacterial population was observed at doses below 13Gy. We attributed this increase to a radiation-induced activation of bacterial spores. Four kinetic models were then evaluated for their prediction of bacterial spore behavior under irradiation. This included: (i) first-order kinetics model; (ii) Shull model; (iii) Sapru model; and (iv) probabilistic model. From R2 and AIC analyses, we noted that the probabilistic model performed the best, followed by the Sapru model. We highlighted that for simplicity in curve fitting the Sapru model should be used instead of the probabilistic model. A 12-log reduction in bacterial population (corresponding to a sterility assurance level of 10-6 as required in the sterilization of medical devices) was computed to be achievable at doses of 1000, 1600 and 2300 Gy for the three different X-ray cut-off energies respectively. These doses are an order in magnitude lesser than that required in gamma irradiation. This highlights the applicability of cheaper and safer table-top X-ray sources for sterilization application.

This study evaluates the ability of Lactobacillus rhamnosus GG (LGG) to activate DC and neutrophils and modulate T cell activation and the impact of bacterial dose on these responses. Murine bone marrow derived DC or neutrophils were stimulated with LGG at ratios of 5 : 1, 10 : 1, and 100 : 1 (LGG : cells) and DC maturation (CD40, CD80, CD86, CD83, and MHC class II) and cytokine production (IL-10, TNF-α, and IL-12p70) were examined after 2 h and 18 h coculture and compared to the ability of BCG (the present immunotherapeutic agent for bladder cancer) to stimulate these cells. A 2 h exposure to 100 : 1 (high dose) or an 18 h exposure to 5 : 1 or 10 : 1 (low dose), LGG : cells, induced the highest production of IL-12 and upregulation of CD40, CD80, CD86, and MHC II on DC. In DCs stimulated with LGG activated neutrophils IL-12 production decreased with increasing dose. LGG induced 10-fold greater IL-12 production than BCG. T cell IFNγ and IL-2 production was significantly greater when stimulated with DC activated with low dose LGG. In conclusion, DC or DC activated with neutrophils exposed to low dose LGG induced greater Th1 polarization in T cells and this could potentially exert stronger antitumor effects. Thus the dose of LGG used for immunotherapy could determine treatment efficacy.

The mutual synergistic regulation of the multi-functional sites on a single receptor molecule for ion-binding/recognition is vital for the new receptor design and needs to be well explored from experiment and theory. In this work, a new macrocyclic ion receptor (BEBUR) with three functional zones, including two ether holes and one biurea groups, is designed expecting to mutually enhance the ion-binding performance. The binding behaviors of BEBUR mainly for Cl− and Cs+ are deeply investigated by using density functional theoretical calculations. It is found that Cl−/Cs+ binding can be mutually enhanced and synergistically regulated via corresponding conformational changes of the receptor, well reflecting an electrical complementary matching and mutual reinforcement effect. Moreover, solvent effect calculations indicate that BEBUR may be an excellent candidate structure for Cl−-binding with the enhancement of counter ion (Cs+) in water and toluene. In addition, visualization of intermolecular noncovalent interaction is used for analysis on the nature of the binding interactions between receptor and ions. [ABSTRACT FROM AUTHOR]

With the development of the electricity market, competition has been introduced in the generation side. It is the overall development trend of the electricity market reformulation to optimize the allocation of different resources through bidding. Therefore, it is significant to research the bidding strategies of the generation companies and the large consumers. This paper reviews the existing research methods of bidding strategy. According to the different market mechanisms, the market participators will choose different bidding strategies based on their own cases. We analyze the applicability of bidding strategies under the different conditions, and give suggestions on how to select bidding strategy for the different market participators under different conditions.

Colonizing commensal bacteria after birth are required for the proper development of the gastrointestinal tract. It is believed that bacterial colonization pattern in neonatal gut affects gut barrier function and immune system maturation. Studies on the development of faecal microbiota in infants showed that the neonatal gut was first colonized with enterococci followed by other microbiota such as Bifidobacterium. Other studies showed that babies who developed allergy were less often colonized with Enterococcus during the first month of life as compared to healthy infants. Many studies have been conducted to elucidate how bifidobacteria or lactobacilli, some of which are considered probiotic, regulate infant gut immunity. However, fewer studies have been focused on enterococi. In our study, we demonstrate that E. faecalis, isolated from healthy newborns, suppress inflammatory responses activated in vivo and in vitro. We found E. faecalis attenuates proinflammatory cytokine secretions, especially IL-8, through JNK and p38 signaling pathways. This finding shed light on how the first colonizer, E.faecalis, regulates inflammatory responses in the host.