Unveiling the Connection between Microbiota and Depressive Disorder through Machine Learning.

In the last few years, investigation of the gut-brain axis and the connection between the gut microbiota and the human nervous system and mental health has become one of the most popular topics. Correlations between the taxonomic and functional changes in gut microbiota and major depressive disorder have been shown in several studies. Machine learning provides a promising approach to analyze large-scale metagenomic data and identify biomarkers associated with depression. In this work, machine learning algorithms, such as random forest, elastic net, and You Only Look Once (YOLO), were utilized to detect significant features in microbiome samples and classify individuals based on their disorder status. The analysis was conducted on metagenomic data obtained during the study of gut microbiota of healthy people and patients with major depressive disorder. The YOLO method showed the greatest effectiveness in the analysis of the metagenomic samples and confirmed the experimental results on the critical importance of a reduction in the amount of Faecalibacterium prausnitzii for the manifestation of depression. These findings could contribute to a better understanding of the role of the gut microbiota in major depressive disorder and potentially lead the way for novel diagnostic and therapeutic strategies.

Alterations of the Composition and Neurometabolic Profile of Human Gut Microbiota in Major Depressive Disorder.

Major depressive disorder (MDD) is among the most prevalent mental disorders worldwide. Factors causing the pathogenesis of MDD include gut microbiota (GM), which interacts with the host through the gut-brain axis. In previous studies of GM in MDD patients, 16S rRNA sequencing was used, which provided information about composition but not about function. In our study, we analyzed whole metagenome sequencing data to assess changes in both the composition and functional profile of GM. We looked at the GM of 36 MDD patients, compared with that of 38 healthy volunteers. Comparative taxonomic analysis showed decreased abundances of Faecalibacterium prausnitzii, Roseburia hominis, and Roseburia intestinalis, and elevated abundances of Escherichia coli and Ruthenibacterium lactatiformans in the GM of MDD patients. We observed decreased levels of bacterial genes encoding key enzymes involved in the production of arginine, asparagine, glutamate, glutamine, melatonin, acetic, butyric and conjugated linoleic acids, and spermidine in MDD patients. These genes produced signature pairs with Faecalibacterium prausntizii and correlated with decreased levels of this species in the GM of MDD patients. These results show the potential impact of the identified biomarker bacteria and their metabolites on the pathogenesis of MDD, and should be confirmed in future metabolomic studies.

Correlation between Intraocular Pressure and Thickness of Extraocular Muscles, the Severity and Activity of Thyroid-associated Orbitopathy.

AIM: To establish the correlation between intraocular pressure (IOP) and thickness of extraocular muscles (EOM), the severity and activity of thyroid-associated orbitopathy (TAO). MATERIALS AND METHODS: 50 patients with TAO were included in the study. They all underwent a thorough ophthalmic examination, Goldmann tonometry (mm Hg) and computer tomography of the orbits, the muscle thickness sum (MTS) of each eye being measured in millimeters. According to the activity of TAO, the patients were divided into two groups - with and without activity, and according to the severity of the disease - into 6 groups: Group 1 ('O') had only subjective symptoms, group 2 ('S') had soft tissue symptoms, group 3 ('P') - proptosis, group 4 ('E') - ocular motility disorders, group 5 ('C') - corneal damage, and group 6 ('Si') - visual impairment; Results: TAO activity was registered in 21 patients (42 eyes, 42%) with MTS 23.39±3.81 and IOP 18.43±4.16. Twenty-nine patients (58 eyes, 58%) with MTS 19±3.21 and IOP 15.98±4.59 showed no TAO activity. The IOP within the groups, in terms of severity, was as follows: group 1 - 19.92+4.05; group 2 - 14.5±2.55; group 3 - 18.04±4.51; group 4 - 18.2±5.05; group 5 - 20.5±4.5; group 6 - 21.5±4.95. A correlation between the IOP and MTS was found. CONCLUSIONS: The IOP in patients with TAO depends on the thickness of the EOM, as well as on the activity and severity of the disease.

Application of Ultrasonic Devices in Management of Periodontal Lesions - Bone Response in a Case of a Tooth with Poor Treatment Prognosis.

BACKGROUND: Surgical treatment of odontogenic jaw cysts may include one of the following four basic methods: enucleation, marsupialization, staged combination of marsupialization and enucleation, or enucleation with curettage. Enucleation/cystectomy, alone or combined with other procedures, is the preferred choice of treatment. OBJECTIVE: The aim of the case report was to present the outcome of an ultrasound-assistant periapical cystectomy in a frontal upper tooth with indications for extraction. RESULTS: Postoperative recovery was uneventful. The functional result was satisfactory. On the follow-up X-rays a reduction of the intraosseous defect by a new bone formation could be observed. CONCLUSION: We found ultrasonic surgery to be a promising approach for safe and effective odontogenic jaw cyst removal reducing the risk of its recurrence.