Abundance and age of viable resting eggs of the calanoid copepod Boeckella poppei Mrazek in sediments: evidence of egg banks in two Antarctic maritime lakes

The existence of egg banks not only ensures the survival of zooplankton through harsh periods, but could also affect microevolutionary dynamics. Whether zooplankton at high latitudes can build up an egg bank in sediments, as occurs at lower latitudes, is still unknown. The distribution and age of viable resting eggs of the calanoid copepod Boeckella poppei Mrazek in sediments of two small freshwater lakes on King George Island were determined by slicing sediment cores at 1-cm intervals. Most viable resting eggs were found near the sediment surface, with abundance sharply declining to very low values at the depth of 5 cm, although eggs were present as deep as 9 cm in the sediments of Yanouhu Lake. The egg abundances in Xihu Lake and Yanouhu Lake were estimated to be 9.2 x 10(4) and 7.2 x 10(4) eggs m(-2), respectively. Pb-210 dating indicated a relatively constant sedimentation rate (0.023 cm year(-1)) in Xihu Lake, which was used to estimate the mean age (46.8 year), the maximum age (195.7 year), and the mortality rate (1.64 % year(-1)) of resting eggs of B. poppei in Xihu Lake. The accumulation of resting eggs with long-term viability in sediments provided the first evidence for the existence of egg banks in two Antarctic maritime lakes. An egg bank may serve as an overwintering strategy for B. poppei in Antarctica, enhance their ability to cope with random extreme changes, and contribute to their broad distribution.National Science Foundation of China [40506002]; Fundamental Research Funds for the Central Universities; Shanghai Committee of Science and Technology [08DZ1203102, 09DZ120010A

Gut microbiome profile of Chinese hypertension patients with and without type 2 diabetes mellitus

Abstract Background The coexistence of hypertension and type 2 diabetes mellitus (T2DM) may largely increase the risk for cardiovascular disease. However, there is no clear consensus on the association between hypertension and the risk of diabetes. Gut microbiota plays important roles in the development of hypertension and T2DM, but whether there is difference between hypertension patients with or without T2DM has not been explored yet. Methods We recruited 101 hypertension patients in this study (72 patients without T2DM named HT group and 29 patients with T2DM named HT-T2DM group). Their blood samples were collected for testing clinical characteristics and fecal samples were tested for bacterial DNA using 16 S ribosomal RNA gene sequencing targeting the V3 and V4 region. The data of 40 samples were downloaded from project PRJNA815750 as health control (HC group) in this study. The community composition and structure of the microbiome, taxonomic difference, co-occurrence network and functional enrichment were analyzed by alpha/beta diversity, LEfSe, Fruchterman Reingold’s algorithm and PICRUSt2 functional analysis, respectively. Results Alpha and beta diversity analysis showed significant differences in microbial community richness and composition among the three groups. The HC group had a significantly higher Simpson index and a distinct microbiota community compared to the HT and HT-T2DM groups, as demonstrated by significant differences in unweighted and weighted UniFrac distances. The LEfSe analysis identified specific taxa that had significantly different abundance among the groups, such as Bacteroides uniformis, Blautia wexlerae, Alistipes putredinis, and Prevotella stercorea in the HC group, Prevotella copri and Phascolarctobacterium faecium in the HT group, and Klebsiella pneumoniae in the HT-T2DM group. Co-occurrence network analysis indicates that Prevotella copri, Mediterraneibacter gnavus, Alistipes onderdonkii and some unidentified species act as key nodes in the network. Differentially functional pathway identified by PICRUSt2 were concentrated in nutrition and energy metabolism, as well as the biosynthesis of other secondary metabolites. Conclusions Our study found significant differences in microbial community richness, composition, and function among the healthy controls, hypertension patients with and without T2DM. Some specific taxa may explain this difference and serve as potential therapeutic targets for hypertension, T2DM, and their coexistence

LASSO Regression-Based Diagnosis of Acute ST-Segment Elevation Myocardial Infarction (STEMI) on Electrocardiogram (ECG)

Electrocardiogram (ECG) is an important tool for the detection of acute ST-segment elevation myocardial infarction (STEMI). However, machine learning (ML) for the diagnosis of STEMI complicated with arrhythmia and infarct-related arteries is still underdeveloped based on real-world data. Therefore, we aimed to develop an ML model using the Least Absolute Shrinkage and Selection Operator (LASSO) to automatically diagnose acute STEMI based on ECG features. A total of 318 patients with STEMI and 502 control subjects were enrolled from Jan 2017 to Jun 2019. Coronary angiography was performed. A total of 180 automatic ECG features of 12-lead ECG were input into the model. The LASSO regression model was trained and validated by the internal training dataset and tested by the internal and external testing datasets. A comparative test was performed between the LASSO regression model and different levels of doctors. To identify the STEMI and non-STEMI, the LASSO model retained 14 variables with AUCs of 0.94 and 0.93 in the internal and external testing datasets, respectively. The performance of LASSO regression was similar to that of experienced cardiologists (AUC: 0.92) but superior (p < 0.05) to internal medicine residents, medical interns, and emergency physicians. Furthermore, in terms of identifying left anterior descending (LAD) or non-LAD, LASSO regression achieved AUCs of 0.92 and 0.98 in the internal and external testing datasets, respectively. This LASSO regression model can achieve high accuracy in diagnosing STEMI and LAD vessel disease, thus providing an assisting diagnostic tool based on ECG, which may improve the early diagnosis of STEMI