Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com

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Κυριακή 19 Φεβρουαρίου 2023

Biomechanical influence of narrow‐diameter implants placed at the crestal and subcrestal level in the maxillary anterior region. A 3D finite element analysis

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Abstract

Purpose

To evaluate the tendency of movement, stress distribution, and microstrain of single-unit crowns in simulated cortical and trabecular bone, implants, and prosthetic components of narrow-diameter implants with different lengths placed at the crestal and subcrestal levels in the maxillary anterior region using 3D finite element analysis.

Materials and Methods

Six 3D models were simulated using Invesalius 3.0, Rhinoceros 4.0, and SolidWorks software. Each model simulated the right anterior maxillary region including a Morse taper implant of Ø 2.9 mm with different lengths (7 mm, 10 mm, and 13 mm) placed at the crestal and subcrestal level and supporting a cement-retained monolithic single crown in the area of tooth #12. The finite element analysis was performed using ANSYS 19.2. The simulated applied force was 178 N at 0°, 30°, and 60°. The results were analyzed using maps of displacement, von Mises stress (vM), maximum principal stress, and microstrain.

Results

Models with implants at the subcrestal level showed greater displacement. von Mises stress increased in the implant and prosthetic components when implants were placed at the subcrestal level compared with the crestal level; the length of the implants had a low influence on the stress distribution. Higher stress and strain concentrations were observed in the cortical bone of the subcrestal placement, independent of implant length. Non-axial loading influenced the increased stress and strain in all the evaluated structures.

Conclusions

Narrow-diameter implants positioned at the crestal level showed a more favorable biomechanical behavior for simulated cortical bone, implants, and prosthetic components. Implant length had a smaller influence on stress or strain distribution than the other variables.

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Implementable Deep Learning for Multi‐sequence Proton MRI Lung Segmentation: A Multi‐center, Multi‐vendor, and Multi‐disease Study

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Background

Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters.

Purpose

Develop a generalizable CNN for lung segmentation in 1H-MRI, robust to pathology, acquisition protocol, vendor, and center.

Study type

Retrospective.

Population

A total of 809 1H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6–85); 42% females) and 31 healthy participants (median age (range): 34 (23–76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets.

Field Strength/Sequence

1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1H-MRI.

Assessment

2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance.

Statistical Tests

Kruskal–Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland–Altman analyses assessed agreement with manually derived lung volumes. A P value of <0.05 was considered statistically significant.

Results

The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880–0.987), Average HD of 1.63 mm (0.65–5.45) and XOR of 0.079 (0.025–0.240) on the testing set and a DSC of 0.973 (0.866–0.987), Average HD of 1.11 mm (0.47–8.13) and XOR of 0.054 (0.026–0.255) on external validation data.

Data Conclusion

The 3D CNN generated accurate 1H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center.

Evidence Level

4.

Technical Efficacy

Stage 1.

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Equity in adjuvant radiotherapy utilization in locally advanced head and neck cancer: A SEER‐data based study

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Abstract

Background

Not all patients with locally advanced head and neck cancer (HNC) who are eligible for adjuvant radiotherapy (RT) following upfront surgery appear to receive it.

Methods

Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Selected patients from 2009 to 2018 had locally advanced HNC, underwent upfront surgery, and were eligible for adjuvant RT. Multivariable logistic regression and chi-squared test were used to analyze available patient and tumor characteristics.

Results

Of 12 549 patients, 84.5% underwent adjuvant RT, 15.5% did not. Characteristics associated with lowest adjuvant RT utilization included cancers of the larynx (p < 0.0001) and gingivae (p < 0.0001), age 80 and above (p < 0.0001), unpartnered status (p < 0.0001), and residence within a nonmetropolitan area (p < 0.0024).

Conclusions

Tumor subsite, age, partnered status, and rural/urban residence correlate with omission of adjuvant RT in locally advanced HNC.

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An evaluation of mechanical and biophysical skin parameters at different body locations

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Abstract

Background

Skin is the largest organ in the body, representing an important interface to monitor health and disease. However, there is significant variation in skin properties for different ages, genders and body regions due to the differences in the structure and morphology of the skin tissues. This study aimed to evaluate the use of non-invasive tools to discriminate a range of mechanical and functional skin parameters from different skin sites.

Materials and methods

A cohort of 15 healthy volunteers was recruited following appropriate informed consent. Four well-established CE-marked non-invasive techniques were used to measure four anatomical regions: palm, forearm, sole and lower lumbar L3, using a repeated measures design. Skin parameters included trans-epidermal water loss (TEWL), pH (acidity), erythema, stratum corneum hydration and stiffness and elasticity using Myoton Pro (skin and muscle probe). Differences between body locations for each parameter and the intra-rater reliability between days were evaluated by the same operator.

Results

The results indicate that parameters differed significantly between skin sites. For the Myoton skin probe, the sole recorded the highest stiffness value of 1006 N/m (SD ± 179), while the lower lumbar recorded the least value of 484 N/m (SD ± 160). The muscle indenter Myoton probe revealed the palm's highest value of 754 N/m (± 108), and the lower lumbar recorded the least value of 208 N/m (SD ± 44). TEWL values were lowest on the forearm, averaging 11 g/m2/h, and highest on the palm, averaging 41 g/m2/h. Similar skin hydration levels were recorded in three of the four sites, with the main difference being observed in the sole averaging 13 arbitrary units. Erythema values were characterised by a high degree of inter-subject variation, and no significant differences between sites or sides were observed. The Myoton Pro Skin showed excellent reliability (intra-class correlation coefficients > 0.70) for all sites with except ion of one site right lower back; the Myoton pro muscle probes showed good to poor reliability (0.90–017), the corneometer showed excellent reliability (>0.75) among all the sites tested, and the TEWL showed Good to poor reliability (0.74–0.4) among sites.

Conclusion

The study revealed that using non-invasive methods, the biophysical properties of skin can be mapped, and significant differences in the mechanical and functional properties of skin were observed. These parameters were reliably recorded between days, providing a basis for their use in assessing and monitoring changes in the skin during health and disease.

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Multifunctional Two-Dimensional Bi2Se3 Nanodiscs for Anti-Inflammatory Therapy of Inflammatory Bowel Diseases

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Publication date: Available online 17 February 2023

Source: Acta Biomaterialia

Author(s): Cong Zhang, Qingrong Li, Jie Shan, Jianghao Xing, Xiaoyan Liu, Yan Ma, Haisheng Qian, Xulin Chen, Xianwen Wang, Lian-Ming Wu, Yue Yu

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An integrated strategy to identify COVID‐19 causal genes and characteristics represented by LRRC37A2

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ABSTRACT

Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a cau sal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.

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Downregulation of miR‐193a/b‐3p during HPV‐induced cervical carcinogenesis contributes to anchorage‐independent growth through PI3K/AKT pathway regulators

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Abstract

Cervical cancer is caused by a persistent infection with high-risk types of HPV and an accumulation of (epi)genetic alterations in host cell. Acquisition of anchorage-independent growth represents a critical hallmark during HPV-induced carcinogenesis, thereby yielding the most valuable biomarkers for early diagnosis and therapeutic targets. In a previous study, we found that miR-193a-3p and miR-193b-3p were involved in anchorage-independent growth. This study aimed to delineate the role of miR-193a/b-3p in HPV-induced carcinogenesis and to identify their target genes related to anchorage-independent growth. Cell viability and colony formation were assessed in SiHa cancer cells and HPV-16 and -18 immortalized keratinocytes upon miR-193a/b-3p overexpression. Both miRNAs reduced cell growth of all three cell lines in low-attachment conditions and showed a minor effect in adherent conditions. Online target predicting programs and publicly available expression data were used to find ca ndidate mRNAs targets of miR-193a/b-3p. Seven targets showed reduced mRNA expression upon miR-193a/b-3p overexpression. For 3 targets Western blot analysis was also performed, all showing a reduced protein expression. A direct interaction was confirmed using luciferase assays for 6 genes: LAMC1, PTK2, STMN1, KRAS, SOS2, and PPP2R5C, which are PIK3/AKT regulators. All 6 targets were overexpressed in cervical cancers and/or precursor lesions. Together with an oberserved downregulation of phosphorylated-AKT upon miR-193a/b-3p overexpression, this underlines the biological relevance of miR-193a/b-3p downregulation during HPV-induced cervical carcinogenesis.

In conclusion, downregulation of miR-193a-3p and miR-193b-3p is functionally involved in the acquisition of HPV-induced anchorage independence by targeting regulators of the PIK3/AKT pathway.

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