A novel MRI-based diagnostic model for predicting placenta accreta spectrum.

Objective To develop and evaluate a diagnostic model based on MRI signs for predicting placenta accreta spectrum. Materials and Methods A total of 155 pregnant women were included in this study, randomly divided into 104 cases in the training set and 51 cases in the validation set. There were 93 Non-PAS cases, and 62 cases in the PAS group. The training set included 62 Non-PAS cases and 42 PAS cases. Clinical factors and MRI signs were collected for univariate analysis. Then, binary logistic regression analysis was used to develop independent diagnostic models with clinical relevant risk factors or MRI signs, as well as those combining clinical risk factors and MRI signs. The ROC curve analysis was used to evaluate the diagnostic performance of each diagnostic model. Finally, the validation was performed with the validation set. Results In the training set, four clinical factors (gestity, parity, uterine surgery history, placental position) and 11 MRI features (T2-dark bands, placental bulge, T2 hypointense interface loss, myometrial thinning, bladder wall interruption, focal exophytic mass, abnormal placental bed vascularization, placental heterogeneity, asymmetric placental thickening/shape, placental ischemic infarction, abnormal intraplacental vascularity) were considered as risk factors for PAS. The AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.779, 0.854, and 0.874, respectively. In the validation set, the AUC of the clinical diagnostic model, MRI diagnostic model, and clinical + MRI model of PAS were 0.655, 0.728, and 0.735, respectively. Conclusion Diagnosis model based on MRI features in this study can well predict placenta accreta spectrum.

Planktonic actinobacterial diversity along a salinity gradient of a river and five lakes on the Tibetan Plateau.

The diversity and community structure of planktonic Actinobacteria in a freshwater river and five fresh/saline/hypersaline lakes on the Tibetan Plateau, China were investigated with a combination of geochemical and 16S rRNA gene phylogenetic analyses. A total of 387 actinobacterial 16S rRNA gene clones were sequenced, and they could be classified into Actinobacteridae, Acidimicrobidae, and unclassified Actinobacteria. The Actinobacteridae sequences were distributed into five suborders (e.g., Corynebacterineae, Frankineae, Micrococcineae, Propionibacterineae, and Streptosporangineae) and unclassified Actinobacteridae. Some actinobacterial members (specifically Micrococcineae) were present in a wide range of salinities (from freshwater to NaCl saturation). Statistical analysis showed that salinity and salinity-related environmental variables (such as ions and total nitrogen) significantly (r > 0.5; P < 0.05) influenced the distribution of planktonic actinobacterial community in the investigated aquatic biotopes. Our data have implications for a better understanding of the distribution of Actinobacteria in high-elevation lakes.

[Abundance of ammonia-oxidizing microorganisms in response to environmental variables of hot springs in Yunnan Province, China].

OBJECTIVE: Investigation of ammonia-oxidizing microorganisms (AOMs) in hot springs is of significant importance to understand global nitrogen cycling. However, we still know little about the abundance of AOMs in hot springs. In this research, the abundance of AOMs in thirteen hot springs located in Yunnan Province, China, and the effects of environmental variables (e. g. temperature, pH and ammonia concentration, and certain ions) on the AOM abundance were studied. METHODS: Microbial abundance in collected hot spring samples was determined by using an integrated approach including reverse-transcription quantitative polymerase chain reaction and catalyzed reporter deposition-fluorescence in situ hybridisation. RESULTS: Total biomass in the collected hot spring samples was 10(8) - 10(9) cells/g, among which ammonia-oxidizing archaea (AOA) occupied 0.02%-1.32%, whereas no ammonia-oxidizing bacteria were detected. Statistical analysis indicated that AOA abundance was significantly (P < 0.05) correlated with concentrations of NH3, NO2-, NO3-, pH and temperature, but not related (P > 0.05) to salinity and concentrations of Fe2+ and salinity. CONCLUSION: AOA were the major component of AOM in the studied hot springs, and play an important role in ammonia oxidation in hot springs. Multiple environmental variables (e. g. NH3, NO2-, NO3-, pH and temperature) were together controlling the AOA distribution among hot springs of different conditions, and some environmental variables, such as Fe2+ and salinity may not be the key factors for AOA in hot springs.

Abundance and diversity of aerobic anoxygenic phototrophic bacteria in saline lakes on the Tibetan plateau.

Aerobic anoxygenic phototrophic (AAP) bacteria are heterotrophic prokaryotes that are capable of utilizing light as an energy source but are not capable of producing molecular oxygen. Recently, multiple studies have found that AAP bacteria are widely distributed in oceans and estuaries and may play an important role in carbon cycling. However, AAP bacteria in inland lake ecosystems have not been investigated in depth. In this study, the abundance and diversity of the pufL-M genes, encoding photosynthetic reaction centers of AAP bacteria, were determined in the oxic water column and anoxic sediments of saline lakes (Qinghai, Erhai, and Gahai Lakes) on the Tibetan Plateau, China. Our results indicated that AAP bacteria were abundant in inland lakes, with the proportion of AAP bacteria (in total bacteria) comparable to those in the oceans, but with a lower diversity. Salinity and pH were found to be potential factors controlling the AAP bacterial diversity and community composition. Our data have implications for a better understanding of the potential role of AAP bacteria in carbon cycling in inland lake ecosystems.