Comparison of six machine learning methods for differentiating benign and malignant thyroid nodules using ultrasonographic characteristics.

BACKGROUND: Several machine learning (ML) classifiers for thyroid nodule diagnosis have been compared in terms of their accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and area under the receiver operating curve (AUC). A total of 525 patients with thyroid nodules (malignant, n = 228; benign, n = 297) underwent conventional ultrasonography, strain elastography, and contrast-enhanced ultrasound. Six algorithms were compared: support vector machine (SVM), linear discriminant analysis (LDA), random forest (RF), logistic regression (LG), GlmNet, and K-nearest neighbors (K-NN). The diagnostic performances of the 13 suspicious sonographic features for discriminating benign and malignant thyroid nodules were assessed using different ML algorithms. To compare these algorithms, a 10-fold cross-validation paired t-test was applied to the algorithm performance differences. RESULTS: The logistic regression algorithm had better diagnostic performance than the other ML algorithms. However, it was only slightly higher than those of GlmNet, LDA, and RF. The accuracy, sensitivity, specificity, NPV, PPV, and AUC obtained by running logistic regression were 86.48%, 83.33%, 88.89%, 87.42%, 85.20%, and 92.84%, respectively. CONCLUSIONS: The experimental results indicate that GlmNet, SVM, LDA, LG, K-NN, and RF exhibit slight differences in classification performance.

Full-length chloroplast genome of Dongxiang wild rice reveals small single-copy region switching.

Background: Plant chloroplast DNA (cpDNA) typically has a circular structure, including a large single-copy region (LSC), a small single-copy region (SSC) and two inverted repeats (IR1 and IR2). The organization of these four elementary regions LSC-IR1-SSC-IR2 is highly conserved across all plant cpDNAs. Very few structural variations (SVs) occurring at the elementary-region level have been reported. Results: In the present study, we assembled the full-length cpDNA of Dongxiang wild rice line 159 (DXWR159). Using the long PacBio subreads, we discovered a large inversion of SSC and a large duplication of IR in DXWR159 cpDNAs. Significantly, we reported for the first time forward and reverse SSCs of cpDNAs in similar proportions and named the frequent inversion of a whole SSC as SSC switching. Conclusions: Our study helps researchers to correctly assemble the chloroplast genomes. Our recombination model explained the formation of large SVs in cpDNAs and provided insights into a novel scientific question that if there are common mechanisms in the formation or translocation of all kinds of transposon-like elements (TLEs). We propose that: (1) large inversion is the most accepted mutation type of SVs in cpDNAs; (2) SSC switching ubiquitous occurs in plant cpDNAs; and (3) further investigation of molecular mechanism underlying SSC switching may reveal new driving forces for large SVs.

How the Replication and Transcription Complex Functions in Jumping Transcription of SARS-CoV-2.

Background: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although unprecedented efforts are underway to develop therapeutic strategies against this disease, scientists have acquired only a little knowledge regarding the structures and functions of the CoV replication and transcription complex (RTC). Ascertaining all the RTC components and the arrangement of them is an indispensably step for the eventual determination of its global structure, leading to completely understanding all of its functions at the molecular level. Results: The main results include: 1) hairpins containing the canonical and non-canonical NSP15 cleavage motifs are canonical and non-canonical transcription regulatory sequence (TRS) hairpins; 2) TRS hairpins can be used to identify recombination regions in CoV genomes; 3) RNA methylation participates in the determination of the local RNA structures in CoVs by affecting the formation of base pairing; and 4) The eventual determination of the CoV RTC global structure needs to consider METTL3 in the experimental design. Conclusions: In the present study, we proposed the theoretical arrangement of NSP12-15 and METTL3 in the global RTC structure and constructed a model to answer how the RTC functions in the jumping transcription of CoVs. As the most important finding, TRS hairpins were reported for the first time to interpret NSP15 cleavage, RNA methylation of CoVs and their association at the molecular level. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, providing a crucial basis for future studies.

Temperature gradient-based high-cell density fed-batch fermentation for the production of pyruvate oxidase by recombinant E. coli.

Pyruvate oxidase (PyOD) is a very powerful enzyme for clinical diagnostic applications and environmental monitoring. Influences of temperature on cell growth, plasmid stability, and PyOD expression during the PyOD fermentation process by recombinant Escherichia coli were investigated. Based on the influences of temperature on the physiological metabolism, a novel high-cell density fed-batch cultivation with gradient temperature decrease strategy for effective PyOD production was achieved, under which the biomass (OD600) of recombinant E. coli could reach to 71 and the highest PyOD activity in broth could reach to 3,307 U/L in 26 hr fermentation.

Correlation between high density lipoprotein and monocyte subpopulations among stable coronary atherosclerotic heart disease patients.

High density lipoprotein (HDL) is a structurally and functionally heterogeneous molecular particle whose function is unclear in atherosclerosis at present. Studies show that small HDL functional imbalance may exist in Coronary Atherosclerotic Heart Disease (CAD) patients. Monocyte is considered to play an important role in atherosclerosis, in accordance with the expression of superficial CD14 and CD16, it can be divided into three subpopulations. The purpose of this study was to explore the relation between HDL and monocyte subpopulations among CAD patients. We report 90 cases of stable CAD patients and define the monocyte subpopulations as classical monocyte (CD14++CD16-; CM), intermediate monocyte (CD14+CD16+; IM), and non-classical monocyte (CD14+CD16++; NCM); HDL group is measured by polyacrylamide gel electrophoresis. The results indicated that the small HDL in blood serum has a correlation with proinflammatory NCM in circulation but a negative correction with CM and no relationship with diabetes, saccharify hemoglobin, hypertension, smoking history and taking dose of statins drugs and severity of disease. In conclusion, this study primarily confirms that micromolecule HDL level correlates with the increase of non-classical monocyte subpopulations and decrease of classical monocyte quantity. Thus demonstrates the proinflammatory correlation between micromolecule HDL and internal immunity in the development of stable atherosclerosis.