Areoana analysis of moss leaf cell structure of two Cyrtomnium species (Mniaceae, Bryophyta)

Two species of the moss genus Cyrtomnium were studied for the parameters of their leaf cells. The computer program AREOANA, specially designed for this kind of studies, allows involving large datasets in the analysis. In this study, it processed 81 leaves with altogether 140 000 cellsyesBelgorod State National Research Universit

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

The Size of the Human Proteome: The Width and Depth

This work discusses bioinformatics and experimental approaches to explore the human proteome, a constellation of proteins expressed in different tissues and organs. As the human proteome is not a static entity, it seems necessary to estimate the number of different protein species (proteoforms) and measure the number of copies of the same protein in a specific tissue. Here, meta-analysis of neXtProt knowledge base is proposed for theoretical prediction of the number of different proteoforms that arise from alternative splicing (AS), single amino acid polymorphisms (SAPs), and posttranslational modifications (PTMs). Three possible cases are considered: (1) PTMs and SAPs appear exclusively in the canonical sequences of proteins, but not in splice variants; (2) PTMs and SAPs can occur in both proteins encoded by canonical sequences and in splice variants; (3) all modification types (AS, SAP, and PTM) occur as independent events. Experimental validation of proteoforms is limited by the analytical sensitivity of proteomic technology. A bell-shaped distribution histogram was generated for proteins encoded by a single chromosome, with the estimation of copy numbers in plasma, liver, and HepG2 cell line. The proposed metabioinformatics approaches can be used for estimation of the number of different proteoforms for any group of protein-coding genes

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

NGS-based identification of druggable alterations and signaling pathways – hepatocellular carcinoma case report

Aim. To identify potential cancer driving or clinically relevant molecular events for a patient with hepatocellular carcinoma. Methods. In order to achieve this goal, we performed RNA-seq and exome sequencing for the tumor tissue and its matched control. We annotated the alterations found using several publicly available databases and bioinformatics tools. Results. We identified several differentially expressed genes linked to the classical sorafenib treatment as well as additional pathways potentially druggable by therapies studied in clinical trials (Erlotinib, Lapatinib and Temsirolimus). Several germline mutations, found in XRCC1, TP53 and DPYD, according to the data from other clinical trials, could be related to the increased sensitivity to platinum therapies and reduced sensitivity to 5-Fluorouracil. We also identified several potentially driving mutations that could not be currently linked to therapies, like deletion in CIRBP, SNVs in BTG1, ERBB3, TCF7L2 et al. Conclusions. The presented study shows the potential usefulness of the integrated approach to the NGS data analysis, including the analysis of germline mutations and transcriptome in addition to the cancer panel or the exome sequencing data.Мета. Ідентифікувати потенційно онкодрайверні або клінічно значущі молекулярні події у пацієнта з гепатоклітинною карциномою. Методи. РНК- та екзомне секвенування пухлинної тканини та відповідного контролю. Анотування знайдених змін, використовуючи декілька загальнодоступних баз даних та біоінформатичних програм. Ми також порівняли транскрипційний профіль досліджуваної пухлини з транскриптомами клітинних ліній з бази даних Genomics of Drug Sensitivity in Cancer. Результати. Ідентифіковано кілька генів, що дифференційно експресуються, і пов’язані як з класичною терапією сорафенібом, так і з додатковими сигнальними шляхами, що потенційно вразливі до терапії препаратами, які досліджувались у клініческих випробуваннях (ерлотініб, лапатініб та темсіролімус). Декілька гермінативних мутацій, знайдених в XRCC1, TP53 та DPYD, згідно з даними інших клінічних випробувань, можуть бути пов’язані з підвищеною чутливістю до платинових терапій та зменшеною чутливістю до 5-фторурацилу. Ми також ідентифікували декілька потенційно драйверних мутацій, які на цей час не можуть бути пов’язані з терапіями, наприклад делеції у CIRBP, заміни в BTG1, ERBB3, TCF7L2 тощо. Висновки. Запропоноване дослідження демонструє потенційну корисність інтегрованого підходу до NGS аналізу даних, в тому числі аналізу гермінативних мутацій та транскриптому у додаток до використання онкологічних генних панелей або даних секвенування екзому.Цель. Выявлении ключевых или клинически значимых молекулярных событий для пациента с гепатоцеллюлярной карциномой. Методы. РНК- и экзомное секвенирования опухолевой и нормальной ткани. Мы проаннотировали найденные генетические нарушения, используя несколько общедоступных баз данных и биоинформатических инструментов. Результаты. Мы определили несколько дифференциально экспрессированных генов, связанных с классической схемой лечения препаратом сорафениб, а также дополнительные пути потенциально поддающиеся терапии препаратами, включенными в клинические испытания (Эрлотиниб, Лапатиниб и Темсиролимус). Несколько герминативных мутаций, найденных в XRCC1, TP53 и DPYD, по данным из других клинических испытаний, могут быть связаны с повышенной чувствительностью к препаратам платины и пониженной чувствительностью к 5-фторурацилу. Мы также определили несколько потенциально драйверных мутаций в генах CIRBP, замены в BTG1, ErbB3, TCF7L2 и др., которые в настоящее время не связаны с тера­пией. Выводы. Данное исследование показывает потенциальную значимость комплексного подхода к анализу данных NGS, в том числе анализа герминативных мутаций и транскриптома в дополнение к данным из генных панелей или секвенирования экзома