Comparison of ultrasound−based ADNEX model with magnetic resonance imaging for discriminating adnexal masses: a multi-center study

ObjectivesThe ADNEX model offered a good diagnostic performance for discriminating adnexal tumors, but research comparing the abilities of the ADNEX model and MRI for characterizing adnexal tumors has not been reported to our knowledge. The aim of this study was to evaluate the diagnostic accuracy of the ultrasound-based ADNEX (Assessment of Different NEoplasias in the adneXa) model in comparison with that of magnetic resonance imaging (MRI) for differentiating benign, borderline and malignant adnexal masses.MethodsThis prospective study included 529 women with adnexal masses who underwent assessment via the ADNEX model and subjective MRI analysis before surgical treatment between October 2019 and April 2022 at two hospitals. Postoperative histological diagnosis was considered the gold standard.ResultsAmong the 529 women, 92 (17.4%) masses were diagnosed histologically as malignant tumors, 67 (12.7%) as borderline tumors, and 370 (69.9%) as benign tumors. For the diagnosis of malignancy, including borderline tumors, overall agreement between the ADNEX model and MRI pre-operation was 84.9%. The sensitivity of the ADNEX model of 0.91 (95% confidence interval [CI]: 0.85–0.95) was similar to that of MRI (0.89, 95% CI: 0.84–0.94; P=0.717). However, the ADNEX model had a higher specificity (0.90, 95% CI: 0.87–0.93) than MRI (0.81, 95% CI: 0.77–0.85; P=0.001). The greatest sensitivity (0.96, 95% CI: 0.92–0.99) and specificity (0.94, 95% CI: 0.91–0.96) were achieved by combining the ADNEX model and subjective MRI assessment. While the total diagnostic accuracy did not differ significantly between the two methods (P=0.059), the ADNEX model showed greater diagnostic accuracy for borderline tumors (P<0.001).ConclusionThe ultrasound-based ADNEX model demonstrated excellent diagnostic performance for adnexal tumors, especially borderline tumors, compared with MRI. Accordingly, we recommend that the ADNEX model, alone or with subjective MRI assessment, should be used for pre-operative assessment of adnexal masses

Evolutionary Analysis of Structural Protein Gene VP1 of Foot-and-Mouth Disease Virus Serotype Asia 1

Foot-and-mouth disease virus (FMDV) serotype Asia 1 was mostly endemic in Asia and then was responsible for economically important viral disease of cloven-hoofed animals, but the study on its selection and evolutionary process is comparatively rare. In this study, we characterized 377 isolates from Asia collected up until 2012, including four vaccine strains. Maximum likelihood analysis suggested that the strains circulating in Asia were classified into 8 different groups (groups I–VIII) or were unclassified (viruses collected before 2000). On the basis of divergence time analyses, we infer that the TMRCA of Asia 1 virus existed approximately 86.29 years ago. The result suggested that the virus had a high mutation rate (5.745 × 10−3 substitutions/site/year) in comparison to the other serotypes of FMDV VP1 gene. Furthermore, the structural protein VP1 was under lower selection pressure and the positive selection occurred at many sites, and four codons (positions 141, 146, 151, and 169) were located in known critical antigenic residues. The remaining sites were not located in known functional regions and were moderately conserved, and the reason for supporting all sites under positive selection remains to be elucidated because the power of these analyses was largely unknown

Epigenetic targeting of Hedgehog pathway transcriptional output through BET bromodomain inhibition

Hedgehog signaling drives oncogenesis in several cancers and strategies targeting this pathway have been developed, most notably through inhibition of Smoothened. However, resistance to Smoothened inhibitors occurs via genetic changes of Smoothened or other downstream Hedgehog components. Here, we overcome these resistance mechanisms by modulating GLI transcription via inhibition of BET bromodomain proteins. We show the BET bromodomain protein, BRD4, regulates GLI transcription downstream of SMO and SUFU and chromatin immunoprecipitation studies reveal BRD4 directly occupies GLI1 and GLI2 promoters, with a substantial decrease in engagement of these sites upon treatment with JQ1, a small molecule inhibitor targeting BRD4. Globally, genes associated with medulloblastoma-specific GLI1 binding sites are downregulated in response to JQ1 treatment, supporting direct regulation of GLI activity by BRD4. Notably, patient- and GEMM-derived Hedgehog-driven tumors (basal cell carcinoma, medulloblastoma and atypical teratoid/rhabdoid tumor) respond to JQ1 even when harboring genetic lesions rendering them resistant to Smoothened antagonists

Loosen Couple Workflow Mode of Lean Operator Improvement Based on Positive Feedback

informatio

Quantitative analysis of vertebral fat fraction and R2* in osteoporosis using IDEAL-IQ sequence

Abstract Objective To investigate the correlation between FF, R2* value of IDEAL-IQ sequence and bone mineral density, and to explore their application value in the osteoporosis. Methods We recruited 105 women and 69 men aged over 30 years who voluntarily underwent DXA and MRI examination of lumbar spine at the same day. Participants were divided into normal, osteopenia and osteoporosis group based on T-score and BMD value of DXA examination. One-way ANOVA was adopted to compare the quantitative parameters among the three groups. Independent samples t-test was utilized to compare FF and R2* value between men and women.Pearson correlation analysis was used to research the correlation between FF, R2* value and BMD. Results Age, height, weight, BMD and FF value were significantly different among three groups (p < 0.05). No significant difference was found in FF value between male and female group, while R2* value were significantly different. Vertebral FF was moderately negatively correlated with aBMD, especially in women (r = -0.638, p < 0.001). R2* was mildly to moderately positively correlated with aBMD in men (r = 0.350, p = 0.003), but not in women. Moreover, FF was positively correlated with age, R2* was negatively correlated with age in men, and BMD was negatively correlated with age. Conclusions The vertebral FF value of IDEAL-IQ sequence has the potential to be a new biological marker for the assessment of osteoporosis. Vertebral FF is moderately negatively correlated with aBMD, especially in women, allowing accuratly quantify the bone marrow fat. R2* value is mildly to moderately correlated with BMD in men and can be served as a complementary tool in the assessment of osteoporosis

Clinical lipidomics: a new way to diagnose human diseases

Abstract Lipidomics is a measurement of a large scale of lipid species to understand roles of their carbon atoms, dual bonds, or isomerism in the lipid molecule. Clinical lipidomics was recently defined “as a new integrative biomedicine to discover the correlation and regulation between a large scale of lipid elements measured and analyzed in liquid biopsies from patients with those patient phenomes and clinical phenotypes”. The first step to translate lipidomics into clinical lipidomics is to settle a number of standard operation procedures and protocols of lipidomics performance and measurement. Clinical lipidomics is the part of clinical trans-omics which was coined as a new emerging scientific discipline where clinical phenomes are integrated with molecular multiomics. We believe it is the time to translate lipid science and lipidomics into clinical application and to understand the importance of clinical lipidomics as one of the most helpful approaches during the design and decision-making of therapeutic strategies for individuals. We emphasize here that clinical lipidomics should be merged with clinical phenomes, e.g. patient signs and symptoms, biomedical analyses, pathology, images, and responses to therapies, although it is difficult to integrate and fuse the information of clinical lipidomics with clinical phenomes. It will be a great achievement if we can draw the networks of lipidomic species fused with networks of genes and proteins to describe the molecular mechanisms of the disease in multi-dimensions

State-of-Charge Estimation for Li-Ion Power Batteries Based on a Tuning Free Observer

A battery’s state-of-charge (SOC) can be used to estimate the mileage an electric vehicle (EV) can travel. It is desirable to make such an estimation not only accurate, but also economical in computation, so that the battery management system (BMS) can be cost-effective in its implementation. Existing computationally-efficient SOC estimation algorithms, such as the Luenberger observer, suffer from low accuracy and require tuning of the feedback gain by trial-and-error. In this study, an algorithm named lazy-extended Kalman filter (LEKF) is proposed, to allow the Luenberger observer to learn periodically from the extended Kalman filter (EKF) and solve the problems, while maintaining computational efficiency. We demonstrated the effectiveness and high performance of LEKF by both numerical simulation and experiments under different load conditions. The results show that LEKF can have 50% less computational complexity than the conventional EKF and a near-optimal estimation error of less than 2%