Investigation and identification of the first mushroom poisoning case caused by Amanita sychnopyramis f. subannulata in Jiangxi

Objective To investigate and identify a case caused by mushroom poisoning in May 2019 in Jiangxi Province. Methods The case was studied with the epidemiological information, clinical data, and suspicious mushroom samples were identified by morphological and molecular studies. Results The epidemiological information showed that all the patients had eaten different quantity of mushrooms which were picked and boiled by themselves, the average incubation period was 2.5 hours, and the symptoms of dizziness, gastrointestinal discomfort, vomiting, numbness of limbs and so on had existed orderly of the patients. The morphological and molecular studies identified the samples were Amanita sychnopyramis f. subannulata. Conclusion The incident was the first reported case caused by Amanita sychnopyramis f. subannulata in Jiangxi Province. The poisonous mushroom species can be identified combined with epidemiology, morphology and molecular studies. The situation of s mushroom poisoning in Jiangxi Province is still serious and the relevant departments should strengthen prevention and control

Analysis of nontyphoidal Salmonella clinical isolates antibiotic resistance based on whole genome sequencing in Jiangxi Province in 2018

Objective Understanding of bacterial antibiotic resistance is the basis for guiding clinical anti-infective therapy and monitoring antimicrobial resistance trends. The study was aimed to investigate the antibiotic resistance characteristics of nontyphoidal Salmonella isolates from foodborne disease cases in Jiangxi Province in 2018, study the correlations between resistance phenotypes and genotypes, and evaluate the application prospects of whole genome sequencing (WGS) in antimicrobial resistance surveillance. Methods In this study, 58 nontyphoidal Salmonella strains were isolated from foodborne disease patients in Jiangxi Province in 2018 and were tested for susceptibility to 14 antimicrobials using broth microdilution. The 58 isolates were subjected to WGS, and resistance genes were identified from assembled sequences that compared with ResFinder database. Results 77.59% (45/58) of isolates were resistant to tetracycline, and 72.41% (42/58) were resistant to ampicillin. 100.00% of isolates were susceptible to imipenem. 56.90% (33/58) of isolates displayed resistance to at least 3 classes of antibiotics, and 3.45% (2/58) of isolates had resistance to at least 6 of 8 classes tested. A total of 47 unique resistance genes referred to 11 classes of antibiotics, plus mutations in gyrA, gyrB and parC structural of quinolone resistance-determining region (QRDR), were identified. 100.00% (58/58) of isolates had aminoglycoside resistance genes, and 72.41% (42/58) of isolates harboured tetracycline resistance genes. Macrolide resistance genes were presented in 3.45% (2/58) of isolates. 77.59% (45/58) of isolates were contained at least 3 classes of antibiotics resistance genes, and 1.72% (1/58) of isolates harboured at least 9 classes of resistance genes. The overall resistance genotypes and phenotypes were consistent in 93.43% (611/654) of cases. Except quinolones, the correlations were above 91% for tested antibiotics. Correlations were 100% for some classes of antibiotics. Conclusion The antibiotic resistance phenomenon of these isolates was serious. The resistance phenotypes were in good accordance with genotypes, and WGS can be used as an effective tool to predict the antibiotic resistance of nontyphoidal Salmonella. As more new antibiotic resistance genes were discovered, the consistency of resistance genotypes and phenotypes will be further improved

Profiling the peripheral blood T cell receptor repertoires of gastric cancer patients

Cancer driven by somatic mutations may express neoantigens that can trigger T-cell immune responses. Since T-cell receptor (TCR) repertoires play critical roles in anti-tumor immune responses for oncology, next-generation sequencing (NGS) was used to profile the hypervariable complementarity-determining region 3 (CDR3) of the TCR-beta chain in peripheral blood samples from 68 gastric cancer patients and 49 healthy controls. We found that most hyper-expanded CDR3 are individual-specific, and the gene usage of TRBV3-1 is more frequent in the tumor group regardless of tumor stage than in the healthy control group. We identified 374 hyper-expanded tumor-specific CDR3, which may play a vital role in anti-tumor immune responses. The patients with stage IV gastric cancer have higher EBV-specific CDR3 abundance than the control. In conclusion, analysis of the peripheral blood TCR repertoires may provide the biomarker for gastric cancer prognosis and guide future immunotherapy

A Class-Incremental Detection Method of Remote Sensing Images Based on Selective Distillation

With the rapid development of remote sensing technology and the growing demand for applications, the classical deep learning-based object detection model is bottlenecked in processing incremental data, especially in the increasing classes of detected objects. It requires models to sequentially learn new classes of objects based on the current model, while preserving old categories-related knowledge. Existing class-incremental detection methods achieve this goal mainly by constraining the optimization trajectory in the feature of output space. However, these works neglect the case where the previously learned background is a new category to learn, resulting in performance degradation in the new category because of the conflict between remaining the background-related knowledge or updating the background-related knowledge. This paper proposes a novel class-incremental detection method incorporated with the teacher-student architecture and the selective distillation (SDCID) strategy. Specifically, it is the asymmetry architecture, i.e., the teacher network temporarily stores historical knowledge of previously learned objects, and the student network integrates historical knowledge from the teacher network with the newly learned object-related knowledge, respectively. This asymmetry architecture reveals the significance of the distinct representation of history knowledge and new knowledge in incremental detection. Furthermore, SDCID selectively masks the shared subobject of new images to learn and previously learned background, while learning new categories of images and then transfers the classification results of the student model to the background class following the judgment model of the teacher model. This manner avoids interferences between the background category-related knowledge from a teacher model and the learning of other new classes of objects. In addition, we proposed a new incremental learning evaluation metric, C-SP, to comprehensively evaluate the incremental learning stability and plasticity performance. We verified the proposed method on two object detection datasets of remote sensing images, i.e., DIOR and DOTA. The experience results in accuracy and C-SP suggest that the proposed method surpasses existing class-incremental detection methods. We further analyzed the influence of the mask component in our method and the hyper-parameters sensitive to our method

Evolution of Inclusions in Steelmaking Process of Rare Earth Steels Containing Arsenic with Alumina Crucibles

In order to determine strategies for removing arsenic from rare earth arsenic-containing steels, the evolution of inclusions in the whole steelmaking process with alumina crucibles was investigated. It has been proven that adding lanthanum has a significant effect on both the existing state and content of arsenic in steel. The content of arsenic steeply decreased after adding 0.148% lanthanum by generating La–S–As inclusions. The addition of 0.054% lanthanum did not dramatically affect the content of arsenic. Both 0.148% and 0.054% additions of lanthanum modified the existing Si–Mn–Al–O inclusions, making them first change to La-containing inclusions, and then change back to Si–Mn–Al–O inclusions. During this process, the compositions of inclusions changed from (SiO2–MnO)-rich to Al2O3-rich ones, owing to the reactions between lanthanum and alumina crucibles. The addition of 0.148% lanthanum resulted in a relatively severe reaction with the alumina crucible. This led to the decomposition of a part of the existing La–S–As inclusions and a slight increase in the arsenic content. Therefore, it is noted that choosing an appropriate holding time after adding rare earth elements to molten steel has a significant effect on the arsenic removal and saving the consumption of rare earth elements

Regionally differentiated promotion of electric vehicles in China considering environmental and human health impacts

Private passenger vehicles, with its high emissions of CO _2 and air pollutants, poses a severe threat to global climate and human health, particularly for a large developing country like China. Although both energy efficiency improvement of internal combustion engine vehicles (ICEVs) and the wide adoption of electric vehicles (EVs) could contribute to reducing emissions, how they should be jointly implemented in provinces with a heterogeneous context to maximize their net benefits remains insufficiently explored. Here, based on an integrated modeling framework associated with one factual (REF) and four counterfactual scenarios to explore the priority and best-ranked ordering of both EVs’ penetration and high energy-efficient ICEVs in 31 Chinese provinces to achieve the most environmental and human health benefits from 2011 to 2018. The results demonstrate that electrification of the passenger fleet, which is charged by a slightly cleaner power source relative to 2011, yields significant co-benefits of CO _2 reduction and air quality improvement. Compared with REF, the fleet electrification scenario would lead to 3167 cases of avoided mortality and attain US$4.269 billion of health benefits in 2018, accounting for 0.03% of China’s gross domestic product. Nonetheless, highly efficient ICEVs are found to harbor decarbonization potential and health benefits in northern China. Based on these results, Sichuan, Hebei and seven other provinces in east China should promote EVs imminently; conversely, eight provinces with a high share of thermal power must continually advance their implementation of ICEVs in the near future. Such prioritization of EVs and ICEV development at the provincial level provides timely insights for devising tailored policies regarding passenger car transition and for maximizing climate and health benefits based on regional heterogeneity

Promoted Mid-Infrared Photodetection of PbSe Film by Iodine Sensitization Based on Chemical Bath Deposition

In recent years, lead selenide (PbSe) has gained considerable attention for its potential applications in optoelectronic devices. However, there are still some challenges in realizing mid-infrared detection applications with single PbSe film at room temperature. In this paper, we use a chemical bath deposition method to deposit PbSe thin films by varying deposition time. The effects of the deposition time on the structure, morphology, and optical absorption of the deposited PbSe films were investigated by x-ray diffraction, scanning electron microscopy, and infrared spectrometer. In addition, in order to activate the mid-infrared detection capability of PbSe, we explored its application in infrared photodetection by improving its crystalline quality and photoconductivity and reducing tge noise and high dark current of PbSe thin films through subsequent iodine treatment. The iodine sensitization PbSe film showed superior photoelectric properties compared to the untreated sample, which exhibited the maximum of responsiveness, which is 30.27 A/W at 808 nm, and activated its detection ability in the mid-infrared (5000 nm) by introducing PbI2, increasing the barrier height of the crystallite boundary and carrier lifetimes. This facile synthesis strategy and the sensitization treatment process provide a potential experimental scheme for the simple, rapid, low-cost, and efficient fabrication of large-area infrared PbSe devices

In-situ construction of abundant active centers on hierarchically porous carbon electrode toward high-performance phosphate electrosorption: Synergistic effect of electric field and capture sites

Phosphate removal is crucial for eutrophication control and water quality improvement. Electro-assisted adsorption, an eco-friendly electrosorption process, exhibited a promising potential for wastewater treatment. However, there are few works focused on phosphate electrosorption, and reported electrodes cannot attach satisfactory removal capacities and rates. Herein, electro-assisted adsorption of phosphate via in-situ construction of La active centers on hierarchically porous carbon (LaPC) has been originally demonstrated. The resulted LaPC composite not only possessed a hierarchically porous structure with uniformly dispersed La active sites, but also provided good conductivity for interfacial electron transfer. The LaPC electrode achieved an ultrahigh phosphate electrosorption capability of 462.01 mg g−1 at 1 V, outperforming most existing electrodes. The superior phosphate removal performance originates from abundant active centers formed by the coupling of electric field and capture sites. Besides, the stability and selectivity toward phosphate capture were maintained well even under comprehensive conditions. Moreover, a series of kinetics and isotherms models were employed to validate the electrosorption process. This work demonstrates a deep understanding and promotes a new level of phosphate electrosorption

Uncovering the key mechanisms of how deep decarbonization benefits air pollution alleviation in China

Addressing climate change and air pollution goals in conjunction would be efficient and cost-effective. Dealing with these two challenges is a common issue for urban clusters pursuing sustainable development. Expected to become the fourth international first-class bay area, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) takes the lead in exploring a green and low-carbon transition path as a key element of being a pioneering economic reform demonstration zone. Based on an integrated modeling framework that couples an energy-economy model (IMED|CGE), decomposition analysis, and regression methods, the potential contribution of achieving the climate mitigation target to air pollutant reduction in the GBA by 2050 was quantified. The results showed that the transport sector has the most significant potential for carbon reduction. Energy intensity and structural transformations are the main contributors to reducing carbon emissions, with the latter becoming increasingly important over time. Climate policy can effectively reduce air pollutant emissions; however, this effect varies for different pollutants and sectors. Based on the assessment of the synergy index and cost of abatement, sectors with priority for synergic governance were identified. The regression results indicated that the carbon shadow price would be significantly more effective in reducing air pollutant emissions in the post-2030 period than before 2030, except for SO _2 and NH _3 , partially because of the existing actions that cause the synergistic effects to decline. In addition, end-of-pipe removal measures still play a relatively significant role in reducing air pollutants, particularly VOC, NH _3, and primary PM _2.5 . Thus, the findings suggest that priority should be given to sectors with huge synergistic benefits, such as transportation and power generation while paying attention to possible trade-offs

Potential Health-Promoting Effects of Two Candidate Probiotics Isolated from Infant Feces Using an Immune-Based Screening Strategy

Commensal microorganisms in the human gut are a good source of candidate probiotics, particularly those with immunomodulatory effects that may improve health outcomes by regulating interactions between the gut microbiome and distal organs. Previously, we used an immune-based screening strategy to select two potential probiotic strains from infant feces in China, Bifidobacterium breve 207-1 (207-1) and Lacticaseibacillus paracasei 207-27 (207-27). In this study, the in vitro immunological effects and potential in vivo general health benefits of these two strains were evaluated using Lacticaseibacillus rhamnosus GG (LGG) as the control. The results showed that 207-1 and 207-27 significantly and differentially modulated the cytokine profiles of primary splenic cells, while did not induce abnormal systemic immune responses in healthy mice. They also modulated the gut microbiota composition in a strain-dependent manner, thus decreasing Gram-negative bacteria and increasing health-promoting taxa and short-chain fatty acid levels, particularly butyric acid. Conclusively, 207-1 and 207-27 shaped a robust gut environment in healthy mice in a strain-specific manner. Their potential immunomodulatory effects and other elite properties will be further explored using animal models of disease and subsequent clinical trials. This immune-based screening strategy is promising in efficiently and economically identifying elite candidate probiotics