The Relationship between Bone Remodeling and the Clockwise Rotation of the Facial Skeleton: A Computed Tomographic Imaging-Based Evaluation

Background: Information on the onset and gender differences of midfacial skeletal changes, including the complete understanding of the theory behind the clockwise rotational theory, remains elusive. Methods: One hundred fifty-seven Caucasian individuals (10 men and 10 women aged 20 to 29 years, 30 to 39 years, 40 to 49 years, 50 to 59 years, 60 to 69 years, 70 to 79 years, and 80 to 89 years, and eight men and nine women aged 90 to 98 years) were investigated. Multiplanar computed tomographic scans with standardized angle and distance measurements in all three anatomical axes and in alignment to the sella-nasion (horizontal) line were conducted. Results: Both men and women displayed an increase in orbital floor angle (p < 0.001, maximum at 60 to 69 years), decrease in maxillary angle (p = 0.035, 40 to 49 years), increase in palate angle (p < 0.001, 50 to 59 years), increase in vomer angle (p = 0.022, 30 to 39 years), but a decrease in the pterygoid angle (p = 0.002, 80 to 89 years). Orbital width decreased (p < 0.001, 60 to 69 years), pyriform aperture width increased (p = 0.015, 60 to 69 years), and midfacial height decreased with aging (p < 0.001, 60 to 69 years). Conclusions: Age-related changes of the midfacial skeleton occurred independently of gender, but at various time points in different locations. The observed changes seem to be driven by a bone resorption center located in the posterior maxilla, rather than by a rotational movement of the facial skeleton

Analysis of the diagnostic and economic impact of the combined artificial intelligence algorithm for analysis of 10 pathological findings on chest computed tomography

BACKGROUND: Artificial intelligence technology can help solve the significant problem of missed findings in radiology studies. An important issue is assessing the economic benefits of implementing artificial intelligence. AIM: To evaluate the frequency of missed pathologies detection and the economic potential of artificial intelligence technology for chest computed tomography compared and validated by experienced radiologists. MATERIALS AND METHODS: This was an observational, single-center retrospective study. The study included chest computed tomography without IV contrast from June 1 to July 31, 2022, in Clinical Hospital in Yauza, Moscow. The computed tomography was processed using a complex artificial intelligence algorithm for 10 pathologies: pulmonary infiltrates, typical for viral pneumonia (COVID-19 in pandemic conditions); lung nodules; pleural effusion; pulmonary emphysema; thoracic aortic dilatation; pulmonary trunk dilatation; coronary artery calcification; adrenal hyperplasia; and osteoporosis (vertebral body height and density changes). Two experts analyzed computed tomography and compared results with artificial intelligence. Further routing was determined according to clinical guidelines for all findings initially detected and missed by radiologists. The hospital price list determined the potential revenue loss for each patient. RESULTS: From the final 160 computed tomographies, the artificial intelligence identified 90 studies (56%) with pathologies, of which 81 (51%) were missing at least one pathology in the report. The second-stage lost potential revenue for all pathologies from 81 patients was RUB 2,847,760 ($37,251 or CNY 256,218). Lost potential revenue only for those pathologies missed by radiologists but detected by artificial intelligence was RUB 2,065,360 ($27,017 or CNY 185,824). CONCLUSION: Using artificial intelligence as an assistant to the radiologist for chest computed tomography can dramatically minimize the number of missed abnormalities. Compared with the normal model without artificial intelligence, using artificial intelligence can provide 3.6 times more benefits. Using advanced artificial intelligence for chest computed tomography can save money

Exploiting Multi-Omics Profiling and Systems Biology to Investigate Functions of TOMM34

Although modern biology is now in the post-genomic era with vastly increased access to high-quality data, the set of human genes with a known function remains far from complete. This is especially true for hundreds of mitochondria-associated genes, which are under-characterized and lack clear functional annotation. However, with the advent of multi-omics profiling methods coupled with systems biology algorithms, the cellular role of many such genes can be elucidated. Here, we report genes and pathways associated with TOMM34, Translocase of Outer Mitochondrial Membrane, which plays role in the mitochondrial protein import as a part of cytosolic complex together with Hsp70/Hsp90 and is upregulated in various cancers. We identified genes, proteins, and metabolites altered in TOMM34-/- HepG2 cells. To our knowledge, this is the first attempt to study the functional capacity of TOMM34 using a multi-omics strategy. We demonstrate that TOMM34 affects various processes including oxidative phosphorylation, citric acid cycle, metabolism of purine, and several amino acids. Besides the analysis of already known pathways, we utilized de novo network enrichment algorithm to extract novel perturbed subnetworks, thus obtaining evidence that TOMM34 potentially plays role in several other cellular processes, including NOTCH-, MAPK-, and STAT3-signaling. Collectively, our findings provide new insights into TOMM34’s cellular functions