Screening of alginate lyase-excreting microorganisms from the surface of brown algae

Additional file 1: Figure S1. Gram staining of the 12 alginate lyase-excreting bacterial strains

Clinical features and diagnostic value of metagenomic next -generation sequencing in five cases of non-HIV related Pneumocystis jirovecii pneumonia in children

BackgroundPneumocystis jirovecii (PJ) is an opportunistic pathogenic fungus, and PJ pneumonia (PJP) is a commonly problem in HIV-positive patients. While PJP is not caused by HIV, it generally advances rapidly and can quickly lead to severe respiratory failure. To improve pediatricians’ understanding of the condition and aid early accurate diagnoses and therapy, we examined the clinical characteristics of five instances of non-HIV related PJP (NH-PJP) in children and the efficacy of metagenomic next-generation sequencing (mNGS) in its diagnosis.MethodsFrom January 2020 to June 2022, five children with NH-PJP were admitted to the PICU of the First Affiliated Hospital of Zhengzhou University. We retrospectively summarize the clinical presentation, previous histories, routine laboratory findings, treatment, outcome of regression, and results of mNGS in these five children.ResultsFive male children between the ages of 11 months and 14 years had an acute onset on NH-PJP, three of the children had chest tightness after activity, shortness of breath and paroxysmal dry cough, — and two had high fever and dry cough. All five of the children had several flocculent high-density pictures in both lungs at the beginning of the disease, and lung auscultation revealed coarse breath sounds in both lungs, one of which was accompanied by a modest quantity of dry rales. PJ nuclear sequences were found in one patient and four patients’ blood and alveolar lavage fluid. All five children were treated with Trimethoprim-sulfamethoxazole (TMP-SMX) in combination with Caspofungin and corresponding symptomatic treatment. Four patients were cured and one patient died.ConclusionChildren commonly encounter an initial exposure to NH-PJP, which manifests as a high fever, dry cough, chest discomfort, dyspnea that worsens over time, fast disease progression, and a high death rate. The clinical presentation of children with PJ infection should be taken into consideration along with the results for diagnose. mNGS has higher sensitivity and a shorter detection period compared to identification of PJP

Responses of soil microbial communities to a short-term application of seaweed fertilizer revealed by deep amplicon sequencing

Numerous studies have reported soil damage from chemical fertilizer application and an obvious promotional effect of seaweed fertilizer fermented with Sargassum horneri on the growth of tomato roots and seedlings due to its alginate oligosaccharide. However, few studies have assessed the effects of the fermented seaweed fertilizer on ecological environment and microorganisms in soil. Herein, our objective is to uncover microbial and soil environmental responses to Sargassum horneri-fermented seaweed fertilizer. After treated tomato-planting plots with Sargassum horneri fermented seaweed fertilizer, soil bacterial community compositions based on 16S rRNA gene amplicon sequencing, enzyme activities in soil and crop yield were analyzed. The bacterial a-diversity was strongly influenced by seaweed fertilizer amendment after 60 days. Non-metric multidimensional scaling (NMDS) analysis showed that a difference in bacterial community compositions between day 0 and day 60 was obvious for soil treated with seaweed fertilizer. The community variation could be caused by invertase activity and dehydrogenase activity in canonical correlation analysis (CCA). Protease activity, polyphenol oxidase activity and urease activity showed an obvious correlation with community variation in the Mantel test. The fertilization increased tomato yield by 1.48-1.83 times, Vc content by 1.24-4.55 times and lycopene content by 1.20-2.33 times. In the present study, a possible reason for bacterial community variation was discovered, which will provide an economical dilution rate of seaweed fertilizer for optimal crop yield and quality. Meanwhile, our study will be beneficial for developing a possible substitute for chemical fertilizer and an improved understanding of soil microbial functions and soil sustainability

Integrating optical imaging techniques for a novel approach to evaluate Siberian wild rye seed maturity

Advances in optical imaging technology using rapid and non-destructive methods have led to improvements in the efficiency of seed quality detection. Accurately timing the harvest is crucial for maximizing the yield of higher-quality Siberian wild rye seeds by minimizing excessive shattering during harvesting. This research applied integrated optical imaging techniques and machine learning algorithms to develop different models for classifying Siberian wild rye seeds based on different maturity stages and grain positions. The multi-source fusion of morphological, multispectral, and autofluorescence data provided more comprehensive information but also increases the performance requirements of the equipment. Therefore, we employed three filtering algorithms, namely minimal joint mutual information maximization (JMIM), information gain, and Gini impurity, and set up two control methods (feature union and no-filtering) to assess the impact of retaining only 20% of the features on the model performance. Both JMIM and information gain revealed autofluorescence and morphological features (CIELab A, CIELab B, hue and saturation), with these two filtering algorithms showing shorter run times. Furthermore, a strong correlation was observed between shoot length and morphological and autofluorescence spectral features. Machine learning models based on linear discriminant analysis (LDA), random forests (RF) and support vector machines (SVM) showed high performance (>0.78 accuracies) in classifying seeds at different maturity stages. Furthermore, it was found that there was considerable variation in the different grain positions at the maturity stage, and the K-means approach was used to improve the model performance by 5.8%-9.24%. In conclusion, our study demonstrated that feature filtering algorithms combined with machine learning algorithms offer high performance and low cost in identifying seed maturity stages and that the application of k-means techniques for inconsistent maturity improves classification accuracy. Therefore, this technique could be employed classification of seed maturity and superior physiological quality for Siberian wild rye seeds

Study of the Effect of Mold Corner Shape on the Initial Solidification Behavior of Molten Steel Using Mold Simulator

The chamfered mold with a typical corner shape (angle between the chamfered face and hot face is 45 deg) was applied to the mold simulator study in this paper, and the results were compared with the previous results from a well-developed right-angle mold simulator system. The results suggested that the designed chamfered structure would increase the thermal resistance and weaken the two-dimensional heat transfer around the mold corner, causing the homogeneity of the mold surface temperatures and heat fluxes. In addition, the chamfered structure can decrease the fluctuation of the steel level and the liquid slag flow around the meniscus at mold corner. The cooling intensities at different longitudinal sections of shell are close to each other due to the similar time-average solidification factors, which are 2.392 mm/s1/2 (section A-A: chamfered center), 2.372 mm/s1/2 (section B-B: 135 deg corner), and 2.380 mm/s1/2 (section D-D: face), respectively. For the same oscillation mark (OM), the heights of OM roots at different positions (profile L1 (face), profile L2 (135 deg corner), and profile L3 (chamfered center)) are very close to each other. The average value of height difference (HD) between two OMs roots for L1 and L2 is 0.22 mm, and for L2 and L3 is 0.38 mm. Finally, with the help of metallographic examination, the shapes of different hooks were also discussed