Moso bamboo (Phyllostachys edulis) expansion enhances soil pH and alters soil nutrients and microbial communities.

Amid global environmental concerns, the issue of bamboo expansion has garnered significant attention due to its extensive and profound impacts on the ecosystems. Bamboo expansion occurs in native and introduced habitats worldwide, particularly in Asia. However, the effects of bamboo expansion on soil pH, nutrient levels, and microbial communities are complex and vary across different environments. To address this knowledge gap, we conducted a meta-analysis with 2037 paired observations from 81 studies. The results showed that soil pH increased by 6.99 % (0-20 cm) and 4.49 % (20-40 cm) after bamboo expansion. Notably, soil pH increased more in the coniferous forest with bamboo expansion than in the broadleaf forest. Soil pH progressively increased over time since the establishment of bamboo stands. The extent of soil pH elevation was significantly positively correlated with the proportion of bamboo within the forest stand and mean annual solar radiation. In contrast, it was significantly negatively correlated with the mean annual temperature. The elevation of pH is closely related to expansion stage and expanded forest type rather than primarily shaped by climatic factors across a large scale. We also found that bamboo expansion into coniferous forests brought about a notable 14.14 % reduction in total nitrogen (TN). Varied expansion stages resulted in TN reductions of 6.88 % and 7.99 % for mixed forests and bamboo stands, respectively, compared to native forests. Pure bamboo stands exhibited a remarkable 30.39 % increase in ammonium nitrogen and a significant 21.12 % decrease in nitrate nitrogen compared to their native counterparts. Furthermore, bamboo expansion contributed to heightened soil fungal diversity. Taken together, our findings highlight that bamboo expansion leads to an increase in soil pH and alters soil N components and fungal microbial communities, providing valuable insights for future ecological conservation and resource management.

Artificial Intelligence-Assisted Score Analysis for Predicting the Expression of the Immunotherapy Biomarker PD-L1 in Lung Cancer.

Programmed cell death ligand 1 (PD-L1) is a critical biomarker for predicting the response to immunotherapy. However, traditional quantitative evaluation of PD-L1 expression using immunohistochemistry staining remains challenging for pathologists. Here we developed a deep learning (DL)-based artificial intelligence (AI) model to automatically analyze the immunohistochemical expression of PD-L1 in lung cancer patients. A total of 1,288 patients with lung cancer were included in the study. The diagnostic ability of three different AI models (M1, M2, and M3) was assessed in both PD-L1 (22C3) and PD-L1 (SP263) assays. M2 and M3 showed improved performance in the evaluation of PD-L1 expression in the PD-L1 (22C3) assay, especially at 1% cutoff. Highly accurate performance in the PD-L1 (SP263) was also achieved, with accuracy and specificity of 96.4 and 96.8% in both M2 and M3, respectively. Moreover, the diagnostic results of these three AI-assisted models were highly consistent with those from the pathologist. Similar performances of M1, M2, and M3 in the 22C3 dataset were also obtained in lung adenocarcinoma and lung squamous cell carcinoma in both sampling methods. In conclusion, these results suggest that AI-assisted diagnostic models in PD-L1 expression are a promising tool for improving the efficiency of clinical pathologists.

Soil Properties Interacting With Microbial Metagenome in Decreasing CH4 Emission From Seasonally Flooded Marshland Following Different Stages of Afforestation.

Wetlands are the largest natural source of terrestrial CH4 emissions. Afforestation can enhance soil CH4 oxidation and decrease methanogenesis, yet the driving mechanisms leading to these effects remain unclear. We analyzed the structures of communities of methanogenic and methanotrophic microbes, quantification of mcrA and pmoA genes, the soil microbial metagenome, soil properties and CH4 fluxes in afforested and non-afforested areas in the marshland of the Yangtze River. Compared to the non-afforested land use types, net CH4 emission decreased from bare land, natural vegetation and 5-year forest plantation and transitioned to net CH4 sinks in the 10- and 20-year forest plantations. Both abundances of mcrA and pmoA genes decreased significantly with increasing plantation age. By combining random forest analysis and structural equation modeling, our results provide evidence for an important role of the abundance of functional genes related to methane production in explaining the net CH4 flux in this ecosystem. The structures of methanogenic and methanotrophic microbial communities were of lower importance as explanatory factors than functional genes in terms of in situ CH4 flux. We also found a substantial interaction between functional genes and soil properties in the control of CH4 flux, particularly soil particle size. Our study provides empirical evidence that microbial community function has more explanatory power than taxonomic microbial community structure with respect to in situ CH4 fluxes. This suggests that focusing on gene abundances obtained, e.g., through metagenomics or quantitative/digital PCR could be more effective than community profiling in predicting CH4 fluxes, and such data should be considered for ecosystem modeling.

[Development and Application of Reverse Transcription Loop-mediated Isothermal Amplification Method for Detection of Porcine Rotavirus of Swine].

We wished to establish a method for rapid and sensitive detection of reverse transcription loop-mediated isothermal amplification(RT-LAMP)for the rapid and sensitive detection of porcine rotavirus (PoRV). According to the published PoRV VP7 sequences in GenBank,6specific primers were designed. According to the concentrations of foward and reverse primers, Bst DNA polymerase, Mg(2+), and dNTP, reaction conditions were optimized. Results revealed the concentration ratio of foward and reverse primers to be 200 nmol/L:2, 400 nmol (1:12), Bst DNA polymerase concentration to be 0.64U/µL,Mg2+concentration to be 2.5mmol/L, and dNTP concentration to be 1.0mmol/L in 1hat 60℃.The amplification effect achieved a "ladder" effect, with amplified bands being shown only for PoRV. RT-LAMP was specific and did not elicit a cross reaction with porcine epidemic diarrhea virus, transmissible gastroenteritis virus of pigs, or classical swine fever virus. The sensitivity of RT-LAMP was 1.0×10(2) copies/µL. After the reaction, inspection by the naked eye revealed positive amplification products to appears as cloudy-white precipitates, and addition of SYBR Green I showed a color change. These data demonstrate that RT-LAMP is suitable for the rapid and sensitive detection of PoRV.

[Relationship between urban green-land landscape patterns and air pollution in the central district of Yichang city].

In this paper, four types of landscape structures and their green-land landscape patterns, including the landscapes of dominant green-land patch pattern, even green-land patch pattern, dominant wooded corridor pattern and building or concrete covering pattern (control) in the central district of Yichang city in Hubei Province, were analyzed respectively on the basis of landscape ecological theory. The atmospheric noise and the contents of SO2, NOx and total suspension particle (TSP) of the landscapes were monitored respectively by comparative method. The results showed that the landscape of building or concrete covering pattern (control) was mostly composed of woodless corridors and building or concrete covering patches with the tiptop green-land fragmentation index (18.125 3 ind x hm(-2)) and only had 1.00% green-land coverage, which had a relatively higher atmospheric noise and the highest TSP content in the landscape. The landscape of dominant green-land patch pattern had the highest green-land coverage (up to 43.59%) dominated by great green-land patches and the least fragmentation index (0.453 9 ind x hm(-2)), in which, the atmospheric noise weakened by 28.12% and the TSP content reduced significantly by 86.42%, comparing to the control. The landscape of even green-land patch pattern had the relatively lower green-land coverage (11.34%) and fragmentation index (2.751 1 ind x hm(-2)), which was mainly composed of the middle or small green-land patches and wooded corridors with a regular distribution. In the landscape, the TSP content reduced obviously by 46.62% of the control, while the effect of dust retention was only 53.95% of that in the landscape of dominant green-land patch pattern. In the landscape of dominant wooded corridor pattern, which was a traffic center and turned into a main pollution resource in the city, there were a relatively higher green-land fragmentation index (6.870 0 ind x hm(-2)) and the highest wooded corridor density (0.844 3 hm x hm(-2)) with only 6.13% green-land coverage, and the atmospheric noise and the TSP and NOx content increased by 21.47%, 5.08% and 9.06%, respectively, comparing to control. It was obvious that the greater the average area of the green-land patch and the lower the fragmentation index of green-land patches, the more effective the green-land on purifying air pollution.