Research progress on the detection of foodborne pathogens based on aptamer recognition.

Foodborne diseases caused by bacterial contamination are a serious threat to food safety and human health. The classical plate culture method has the problems of long detection cycle, low sensitivity and specificity, and complicated operation, which cannot meet the growing demand for rapid quantitative detection of pathogenic bacteria. The frequent outbreak of foodborne diseases has put forward higher requirements for rapid and simple detection technology of foodborne pathogens. Aptamer is a kind of oligonucleotide fragment that can recognize targets with the advantages of high affinity and good specificity. The target can be range from proteins, small molecules, cells bacteria, and even viruses. Herein, the latest advances in sensitive and rapid detection of foodborne pathogens based on aptamer recognition was reviewed. Special attention has been paid to the obtained sequences of aptamers to various foodborne pathogens, the optimization of sequences, and the mechanism of aptamer recognition. Then, the research progress of biosensors for the detection of pathogenic bacteria based on aptamer recognition were summarized. Some challenges and prospects for the detection of foodborne pathogens based on aptamer recognition were prospected. In summary, with the further deepening of aptamer research and improvement of detection technology, aptamer-based recognition can meet the needs of rapid, sensitive, and accurate detection in practical applications.

Serum levels of IL-9 and IL-11 serve as predictors for the occurrence of early neurologic deterioration in patients with cerebral infarction.

BACKGROUND AND AIM: Early neurological deterioration (END) is a common complication of cerebral infarction and a significant contributor to poor prognosis. Our study aimed to investigate the predictive value of interleukin-9 (IL-9) and interleukin-11 (IL-11) in relation to the occurrence of END in patients with cerebral infarction. MATERIALS AND METHODS: 102 patients with cerebral infarction and 64 healthy controls were collected. Patients were categorized into two groups based on the development of END following admission: the END group (n = 44) and the non-END group (n = 58). Enzyme-linked immunosorbent assay was used to determine the serum levels of IL-9, IL-11, and BDNF. RESULTS: Serum IL-9 was higher and IL-11 lower in the END group than those in the non-END group (P < 0.01). IL-9 correlated positively with NIHSS score (r = 0.627) and infarction volume (r = 0.686), while IL-11 correlated negatively (r = -0.613, -0.679, respectively). Logistic regression identified age, NIHSS score, and IL-9 as risk factors (P < 0.01), and IL-11 as protective (P < 0.01). Combined IL-9 and IL-11 had an ROC curve area of 0.849. BDNF correlated negatively with IL-9 (r = -0.703) and positively with IL-11 (r = 0.711). CONCLUSION: Serum IL-9 and IL-11 levels can predict the occurrence of END in patient with cerebral infarction and are correlated with serum BDNF levels.

Solution Combustion Synthesis of Submicron-Sized Titanium Niobium Oxide Anodes for High-Rate and Ultrastable Lithium-Ion Batteries.

Recently, the development of high-rate performance lithium-ion batteries is crucial for the development of next-generation energy storage systems. Nanoarchitecturing of the electrode material is a common strategy to improve the effective Li+ diffusion transport rate. However, this method often results in a reduction of volumetric energy density and battery stability. In this work, we propose a different strategy by synthesizing submicron-sized Ti2Nb10O29 (s-TNO) as a durable high-rate anode material using a facile and scalable solution combustion method, eliminating the dependence nanoarchitectures. The s-TNO electrode material exhibits a large tunnel structure and an excellent pseudocapacitive performance. The results show that this electrode material delivers a commendable reversible capacity of 238.7 mAh g-1 at 0.5 C and retains 78.2% of its capacity after 10,000 cycles at 10 C. This work provides a valuable guide for the synthesis of submicron-structured electrode materials using the solution combustion method, particularly for high-capacity, high-rate, and high-stability electrode materials.

Biochar improves soil quality and wheat yield in saline-alkali soils beyond organic fertilizer in a 3-year field trial.

The objective of this study was to examine the effects of biochar compared to organic fertilizer on soil quality and wheat yield in the saline-alkaline lands. A 3-year field trial was conducted on moderately saline-alkaline land in the Yellow River Delta region (YRD) with six treatments: biochar (B1: 5 t, B2: 10 t, B3: 20 t ha-1 year-1) and organic fertilizer (OF1: 5 t, OF2: 7.5 t ha-1 year-1) as well as control (CK). The results showed that both biochar and organic fertilizer increased total organic carbon (TOC), total nitrogen (TN), NH4+-N, and NO3--N, and reduced pH, thereby increasing soil microbial biomass carbon (MBC) and nitrogen (MBN), MBC/TOC ratio, and MBN/TN ratio, but organic fertilizer increased soil nutrients and microbial biomass better than biochar. Correlation analysis revealed that soil water content (SWC), soil salt content (SSC), and Na+ were the most important factors influencing wheat yield. When compared to CK, the SSC and Na+ decreased by 5.55-7.52% and 3.86-9.39%, respectively, and SWC increased by 5.14-5.62% in the biochar treatment, while they increased by 1.07-10.19%, 1.08-7.58%, and 2.96-3.84% in the organic fertilizer treatment, respectively. Accordingly, wheat yield of biochar treatment was 0.90-14.71% higher than that of organic fertilizer treatment (4.49-4.80 t ha-1) and CK (4.47 t ha-1). Collectively, B2 had the lowest SSC and Na+ and the highest yield and was significantly better than the organic fertilizer treatment, as well as efficiently increasing soil nutrients and microbial biomass, suggesting that it may be a better agricultural practice for improving soil quality and increasing wheat yield in the YRD.

A comparative study of thermophilic and mesophilic anaerobic co-digestion of food waste and wheat straw: Process stability and microbial community structure shifts.

Renewable energy recovery from organic solid waste via anaerobic digestion is a promising way to provide sustainable energy supply and eliminate environmental pollution. However, poor efficiency and operational problems hinder its wide application of anaerobic digestion. The effects of two key parameters, i.e. temperature and substrate characteristics on process stability and microbial community structure were studied using two lab-scale anaerobic reactors under thermophilic and mesophilic conditions. Both the reactors were fed with food waste (FW) and wheat straw (WS). The organic loading rates (OLRs) were maintained at a constant level of 3 kg VS/(m3·d). Five different FW:WS substrate ratios were utilized in different operational phases. The synergetic effects of co-digestion improved the stability and performance of the reactors. When FW was mono-digested, both reactors were unstable. The mesophilic reactor eventually failed due to volatile fatty acid accumulation. The thermophilic reactor had better performance compared to mesophilic one. The biogas production rate of the thermophilic reactor was 4.9-14.8% higher than that of mesophilic reactor throughout the experiment. The shifts in microbial community structures throughout the experiment in both thermophilic and mesophilic reactors were investigated. With increasing FW proportions, bacteria belonging to the phylum Thermotogae became predominant in the thermophilic reactor, while the phylum Bacteroidetes was predominant in the mesophilic reactor. The genus Methanosarcina was the predominant methanogen in the thermophilic reactor, while the genus Methanothrix remained predominant in the mesophilic reactor. The methanogenesis pathway shifted from acetoclastic to hydrogenotrophic when the mesophilic reactor experienced perturbations. Moreover, the population of lignocellulose-degrading microorganisms in the thermophilic reactor was higher than those in mesophilic reactor, which explained the better performance of the thermophilic reactor.

Implicit Block Diagonal Low-Rank Representation.

While current block diagonal constrained subspace clustering methods are performed explicitly on the original data space, in practice, it is often more desirable to embed the block diagonal prior into the reproducing kernel Hilbert feature space by kernelization techniques, as the underlying data structure in reality is usually nonlinear. However, it is still unknown how to carry out the embedding and kernelization in the models with block diagonal constraints. In this paper, we shall take a step in this direction. First, we establish a novel model termed implicit block diagonal low-rank representation (IBDLR), by incorporating the implicit feature representation and block diagonal prior into the prevalent low-rank representation method. Second, mostly important, we show that the model in IBDLR could be kernelized by making use of a smoothed dual representation and the specifics of a proximal gradient-based optimization algorithm. Finally, we provide some theoretical analyses for the convergence of our optimization algorithm. Comprehensive experiments on synthetic and real-world data sets demonstrate the superiorities of our IBDLR over state-of-the-art methods.

Effects of free ammonia on volatile fatty acid accumulation and process performance in the anaerobic digestion of two typical bio-wastes.

The effect of free ammonia on volatile fatty acid (VFA) accumulation and process instability was studied using a lab-scale anaerobic digester fed by two typical bio-wastes: fruit and vegetable waste (FVW) and food waste (FW) at 35°C with an organic loading rate (OLR) of 3.0kg VS/(m3·day). The inhibitory effects of free ammonia on methanogenesis were observed due to the low C/N ratio of each substrate (15.6 and 17.2, respectively). A high concentration of free ammonia inhibited methanogenesis resulting in the accumulation of VFAs and a low methane yield. In the inhibited state, acetate accumulated more quickly than propionate and was the main type of accumulated VFA. The co-accumulation of ammonia and VFAs led to an "inhibited steady state" and the ammonia was the main inhibitory substance that triggered the process perturbation. By statistical significance test and VFA fluctuation ratio analysis, the free ammonia inhibition threshold was identified as 45mg/L. Moreover, propionate, iso-butyrate and valerate were determined to be the three most sensitive VFA parameters that were subject to ammonia inhibition.

[Mesophilic and Thermophilic Anaerobic Co-Digestion of Food Waste and Straw].

The anaerobic co-digestion of food waste and straw is more efficient in avoiding the accumulation of volatile fatty acids and promoting the degradation of lignocellulose in comparison with their individual digestions. The co-digestion of food waste and straw was investigated under mesophilic(35℃) and thermophilic(55℃) condition, respectively. The results indicated that when feeding volatile solid concentration was 3 kg·m-3, the accumulated methane production yield of the mesophilic reactor reached the peak of 272.0 mL·g-1 at a food waste-to-straw ratio of 9:1, while it reached the peak of 402.3 mL·g-1 at a food waste-to-straw ratio of 5:5 for thermophilic reactor. These amounts were significantly higher than those of food waste digestion alone(218.6 mL·g-1 for mesophilic reactor and 322.0 mL·g-1 for thermophilic reactor). Co-digestion promoted the rate of carbon transfer to methane, and further, the rate of the thermophilic reactor was higher than that of the mesophilic reactor. Degradation rate for lignocellulose of thermophilic reactor was 34.7%-45.8%, higher than that of mesophilic reactor, 12.6%-42.2%. It was confirmed by 16S rRNA gene sequences of bacteria and archaea, ITS sequences of fungi based on high-throughput sequencing techniques, which showed the amounts of lignocellulose degrading bacteria and actinomycetes in the thermophilic reactor were both higher than those in the mesophilic reactor.

Study of Reciprocal Effects between Mandatory Pollutant Emissions Reduction Policy and Structural Change within the Manufacturing Sector in a Chinese Coastal Area.

We develop a multicriteria decision-making model coupled with scenario analysis to quantitatively elucidate the reciprocal effect between a mandatory pollutant emissions reduction policy and industrial structure change within the manufacturing sector on the basis of an in-depth study of a well-developed coastal area in East China, Ningbo City, toward 2020. First, 18 two-digit level industries (TDLIs) in the manufacturing sector are screened out due to intensive emissions of the four pollutants (COD, NH3-N, SO2, and NOx). Second, a model is established to identify the optimal solution for the industrial structure adjustment of the 18 TDLIs under two scenarios, the "business-as-usual" scenario and the "industrial structure adjustment" scenario. Both scenarios are expanded into three subscenarios. Quantitative constraint conditions and two criteria are formulated to screen out the optimal solutions. We propose a coefficient of industrial structure adjustment, Ki, which could clearly reflect the policy preference in terms of industrial development and reallocate the quota of the four-pollutant emission among the 18 TDLIs with regards to the different expectations of economy development in 2020. The model will help local authorities make tailored policies to reduce pollution emissions effectively through industrial structure change by delicately allocating the pollutant emission quota and setting reasonable targets of emission intensity reduction among TDLIs.