scholarly journals Histological characterization of denticulate palatal plates in an Early Permian dissorophoid

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3727 ◽  
Author(s):  
Bryan M. Gee ◽  
Yara Haridy ◽  
Robert R. Reisz

Denticles are small, tooth-like protrusions that are commonly found on the palate of early tetrapods. Despite their widespread taxonomic occurrence and similar external morphology to marginal teeth, it has not been rigorously tested whether denticles are structurally homologous to true teeth with features such as a pulp cavity, dentine, and enamel, or if they are bony, tooth-like protrusions. Additionally, the denticles are known to occur not only on the palatal bones but also on a mosaic of small palatal plates that is thought to have covered the interpterygoid vacuities of temnospondyls through implantation in a soft tissue covering; however, these plates have never been examined beyond a simple description of their position and external morphology. Accordingly, we performed a histological analysis of these denticulate palatal plates in a dissorophoid temnospondyl in order to characterize their microanatomy and histology. The dentition on these palatal plates has been found to be homologous with true teeth on the basis of both external morphology and histological data through the identification of features such as enamel and a pulp cavity surrounded by dentine. In addition, patterns of tooth replacement and ankylosis support the hypothesis of structural homology between these tiny teeth on the palatal plates and the much larger marginal dentition. We also provide the first histological characterization of the palatal plates, including documentation of abundant Sharpey’s fibres that provide a direct line of evidence to support the hypothesis of soft tissue implantation. Finally, we conducted a survey of the literature to determine the taxonomic distribution of these plates within Temnospondyli, providing a broader context for the presence of palatal plates and illustrating the importance of maintaining consistency in nomenclature.

Author(s):  
Luigi Canullo ◽  
David Penarrocha ◽  
Paolo Pesce ◽  
Cristina Zarauz ◽  
Rossano Lattanzio ◽  
...  

2020 ◽  
Vol 101 (4) ◽  
pp. 245-255 ◽  
Author(s):  
P.A. Gondim Teixeira ◽  
L. Simon ◽  
F. Sirveaux ◽  
B. Marie ◽  
M. Louis ◽  
...  

2008 ◽  
Vol 53 (22) ◽  
pp. 6569-6590 ◽  
Author(s):  
Hani Eskandari ◽  
Septimiu E Salcudean ◽  
Robert Rohling ◽  
Jacques Ohayon

2021 ◽  
Vol 22 (14) ◽  
pp. 7518
Author(s):  
Marcella Tazzari ◽  
Laura Bergamaschi ◽  
Alessandro De Vita ◽  
Paola Collini ◽  
Marta Barisella ◽  
...  

Soft tissue sarcomas (STSs) are a family of rare malignant tumors encompassing more than 80 histologies. Current therapies for metastatic STS, a condition that affects roughly half of patients, have limited efficacy, making innovative therapeutic strategies urgently needed. From a molecular point of view, STSs can be classified as translocation-related and those with a heavily rearranged genotype. Although only the latter display an increased mutational burden, molecular profiles suggestive of an “immune hot” tumor microenvironment are observed across STS histologies, and response to immunotherapy has been reported in both translocation-related and genetic complex STSs. These data reinforce the notion that immunity in STSs is multifaceted and influenced by both genetic and epigenetic determinants. Cumulative evidence indicates that a fine characterization of STSs at different levels is required to identify biomarkers predictive of immunotherapy response and to discover targetable pathways to switch on the immune sensitivity of “immune cold” tumors. In this review, we will summarize recent findings on the interplay between genetic landscape, molecular profiling and immunity in STSs. Immunological and molecular features will be discussed for their prognostic value in selected STS histologies. Finally, the local and systemic immunomodulatory effects of the targeted drugs imatinib and sunitinib will be discussed.


2021 ◽  
Vol 14 (2) ◽  
pp. e239797
Author(s):  
Fergus Cooper ◽  
Rafael Moleron ◽  
Andrea Chapman ◽  
Muhammad Shakeel

Leiomyosarcomas are soft tissue tumours that rarely occur in the larynx. This case report describes the presentation and management of a 77-year-old man referred to the otolaryngology clinic with hoarseness who was found to have a large supraglottic leiomyosarcoma after panendoscopy and biopsies. He subsequently underwent laryngectomy for treatment of this tumour but, unexpectedly, the histological analysis of the laryngectomy specimen revealed a second primary tumour in the larynx—a squamous cell carcinoma (SCC). The patient had further treatment with neck radiotherapy. Three years after treatment, there are no signs of recurrence of either tumour. This case report discusses the very few similar cases of leiomyosarcoma coexisting with SCC in the larynx, collating the evidence surrounding the treatment of this rare presentation.


2002 ◽  
Vol 4 (6) ◽  
pp. 497-498 ◽  
Author(s):  
Ernest C. Borden ◽  
John R. Goldblum

2016 ◽  
Vol 16 (08) ◽  
pp. 1640019 ◽  
Author(s):  
JAEHYUN SHIN ◽  
YONGMIN ZHONG ◽  
JULIAN SMITH ◽  
CHENGFAN GU

Dynamic soft tissue characterization is of importance to robotic-assisted minimally invasive surgery. The traditional linear regression method is unsuited to handle the non-linear Hunt–Crossley (HC) model and its linearization process involves a linearization error. This paper presents a new non-linear estimation method for dynamic characterization of mechanical properties of soft tissues. In order to deal with non-linear and dynamic conditions involved in soft tissue characterization, this method improves the non-linearity and dynamics of the HC model by treating parameter [Formula: see text] as independent variable. Based on this, an unscented Kalman filter is developed for online estimation of soft tissue parameters. Simulations and comparison analysis demonstrate that the proposed method is able to estimate mechanical parameters for both homogeneous tissues and heterogeneous and multi-layer tissues, and the achieved performance is much better than that of the linear regression method.


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