BackgroundDue to the inability to be cultured in vitro, the biological characteristics and pathogenicity of Pneumocystis jirovecii remain unclear. Intestinal microflora disorder is related to the occurrence and development of various pulmonary diseases. This work explores the pathogenesis of pneumocystis pneumonia (PCP) in acquired immune deficiency syndrome (AIDS) patients from a microbiome perspective, to provide better strategies for the diagnosis, treatment, and prevention of PCP.MethodsSubjects were divided into three groups: human immunodeficiency virus (HIV)-infected patients combined with PCP, HIV-infected patients without PCP, and HIV-negative. Stool and bronchoalveolar lavage fluid (BALF) samples were collected, total DNA was extracted, and 16S rRNA high-throughput sequencing was performed using an Illumina MiSeq platform. PICRUSt and BugBase were used to predict microflora functions, and correlation analysis of intestinal and lung bacterial flora was conducted.ResultsCompared with the HIV- group, prevotella and another 21 genera in the intestinal microbiome were statistically different in the HIV+ group; 25 genera including Escherichia-Shigella from HIV+PCP+ group were statistically different from HIV+PCP- group. The abundance of Genera such as Porphyromonas was positively or negatively correlated with CD16/CD56+ (μL). Compared with the HIV- group, identification efficiency based on area under the curve (AUC) >0.7 for the HIV+ group identified seven genera in the gut microbiota, including Enterococcus (total AUC = 0.9519). Compared with the HIV+PCP- group, there were no bacteria with AUC >0.7 in the lung or intestine of the HIV+PCP+ group. The number of shared bacteria between BALF and fecal samples was eight species in the HIV- group, 109 species in PCP- patients, and 228 species in PCP+ patients, according to Venn diagram analysis. Changes in various clinical indicators and blood parameters were also closely related to the increase or decrease in the abundance of intestinal and pulmonary bacteria, respectively.ConclusionsHIV infection and PCP significantly altered the species composition of lung and intestinal microbiomes, HIV infection also significantly affected intestinal microbiome gene functions, and PCP exacerbated the changes. The classification model can be used to distinguish HIV+ from HIV- patients, but the efficiency of bacterial classification was poor between PCP+ and PCP- groups. The microbiomes in the lung and gut were correlated to some extent, providing evidence for the existence of a lung-gut axis, revealing a potential therapeutic target in patients with HIV and PCP.

The selective catalytic reduction of NO with hydrocarbons (SCR-HC) is currently one of the promising technologies for the control of nitrogen oxides (NO x ). Iron-based catalysts are very promising for the SCR-HC reaction considering both the NO conversion efficiency and low cost as an environmentally friendly metal. However, these Fe-based catalysts showed poor SCR activity below 300 °C. To improve the reactivity of the iron-based catalysts supported on Alumina-pillared clays at lower temperatures, Cu was used to modify the Fe/Al-pillared interlayered clay (PILC) catalysts and the selective catalytic reduction of NO with C3H6 (SCR-C3H6) was investigated at 150–550 °C over xCu–Fe/Al-PILC catalysts (x = 0.11–0.38, x means the molar ratio of Cu/Fe) prepared by the impregnation method. The catalysts were characterized by means of X-ray diffraction (XRD), N2 adsorption–desorption, H2-temperature-programmed reduction (TPR), ultraviolet–visible spectroscopy (UV–vis), X-ray photoelectron spectroscopy (XPS), pyridine-adsorption infrared spectroscopy (Py-FTIR), etc. The results showed that Cu improved the SCR of NO obviously at lower temperatures, e.g., the NO conversion increased from 5 to 44% at 150 °C and from 15 to 93% at 250 °C, respectively, for the original Fe/Al-PILC catalysts and the 0.13Cu–Fe/Al-PILC catalyst. The interaction of copper and iron promoted the dispersion of iron species on the catalyst surface and improved the reduction ability of the iron species at lower temperatures. An appropriate copper–iron molar ratio can promote the dispersion of iron species to obtain a larger specific surface area and pore volume. Cu improved the formation of isolated Fe3+ and Fe2O3 particles, and the former together with the isolated Cu2+ contributed to the reduction performance at low temperatures, while the latter allowed the catalyst to maintain a high NO conversion at high temperatures. Moreover, Cu increased the surface acidity of the catalysts. A possible reaction pathway was proposed based on an in situ diffuse reflectance Fourier transform infrared spectroscopy (in situ DRIFTS) study, where the active species were mainly monodentate nitrates, acetates, and NCO species. Importantly, the introduction of Cu promoted the formation of more of these active species, which were contributed to the activity of C3H6-SCR.

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To solve the problem that small drones in the sky are easily confused with background objects and difficult to detect, according to the characteristics of irregular movement, small size, and changeable shape of drones, using a regional target recognition algorithm, the structure characteristics of Group Convolution (GC) in Resnext50 are absorbed. The optimized GC-faster-RCNN is obtained by improving the Fast-RCNN algorithm and the following methods are performed. First, a clustering method is used to analyze the dataset, and appropriate prior bounding box types are obtained. Second, the Resnext50 is used to replace the original feature extraction network, and the improved channel attention mechanism is integrated into its network output to enhance its feature map information. Then, we calculate its effective receptive field according to the Feature Pyramid Network (FPN) structure and redesign the prior bounding box of the corresponding size to construct a multi-scale detection network for small targets. Experiments show that the algorithm has a recognition accuracy of up to 94.8% under 1080 P image quality, and a recognition speed of 8FPS, which can effectively detect the positions of 1–5 small UAVs in a picture. This method provides an effective positioning detection for low-altitude UAVs.