Molecular characterization of a large cohort of mucopolysaccharidosis patients: Iran Mucopolysaccharidosis RE-diagnosis study (IMPRESsion).

Mucopolysaccharidoses (MPSs) are rare, heterogeneous inborn errors of metabolism (IEM) diagnosed through a combination of clinical, biochemical, and genetic investigations. The aim of this study was molecular characterization of the largest cohort of Iranian MPS patients (302 patients from 289 unrelated families), along with tracking their ethnicity and geographical origins. 185/289 patients were studied using an IEM-targeted NGS panel followed by complementary Sanger sequencing, which led to the diagnosis of 154 MPS patients and 5 non-MPS IEMs (diagnostic yield: 85.9%). Furthermore, 106/289 patients who were referred with positive findings went through reanalysis and confirmatory tests which confirmed MPS diagnosis in 104. Among the total of 258 MPS patients, 225 were homozygous, 90 harbored novel variants, and 9 had copy number variations. MPS IV was the most common type (34.8%) followed by MPS I (22.7%) and MPS VI (22.5%). Geographical origin analysis unveiled a pattern of distribution for frequent variants in ARSB (c.430G>A, c.962T>C [p.Leu321Pro], c.281C>A [p.Ser94*]), GALNS (c.319G>A [p.Ala107Thr], c.860C>T [p.Ser287Leu], c.1042A>G [p.Thr348Ala]), and IDUA (c.1A>C [p.Met1Leu], c.1598C>G [p.Pro533Arg], c.1562_1563insC [p.Gly522Argfs*50]). Our extensive patient cohort reveals the genetic and geographic landscape of MPS in Iran, which provides insight into genetic epidemiology of MPS and can facilitate a more cost-effective, time-efficient diagnostic approach based on the region-specific variants.

Effect of low-level laser therapy on experimental wounds of hard palate mucosa in mice.

Under general anesthesia and sterile conditions, incision wound was induced in the hard palate mucosa of adult male mice. The wounds of groups 1 and 2 were irradiated daily with He-Ne laser at 3 and 7.5 J/cm2 for 120 and 300 s, respectively, while the incision wound of group 3 not exposed served as controls. On day 3 of injury, the laser-treated wounds contained significantly lower neutrophils than the wounds in the control group. By day 7 after injury, the laser-treated wounds contained significantly more fibroblasts and at the same time contained significantly fewer macrophages. In conclusion, an acceleration of the wound healing process of experimental wounds in the hard palate mucosa of mice at low-level laser therapy with a He-Ne laser at energy densities of 3 and 7.5 J/cm2 was observed.

Intraoperative Localization of STN During DBS Surgery Using a Data-Driven Model.

A new approach is presented for localizing the Subthalamic Nucleus (STN) during Deep Brain Stimulation (DBS) surgery based on microelectrode recordings (MERs). DBS is an accepted treatment for individuals living with Parkinson's Disease (PD). This surgery involves implantation of a permanent electrode inside the STN to deliver electrical current. Since the STN is a very small region inside the brain, accurate placement of an electrode is a challenging task for the surgical team. Prior to placement of the permanent electrode, microelectrode recordings of brain activity are used intraoperatively to localize the STN. The placement of the electrode and the success of the therapy depend on this location. In this paper, an objective approach is implemented to help the surgical team in localizing the STN. This is achieved by processing the MER signals and extracting features during the surgery to be used in a Machine Learning (ML) algorithm for defining the neurophysiological borders of the STN. For this purpose, a new classification approach is proposed with the goal of detecting both the dorsal and the ventral borders of the STN during the surgical procedure. Results collected from 100 PD patients in this study, show that by calculating and extracting wavelet transformation features from MER signals and using a data-driven computational deep neural network model, it is possible to detect the borders of the STN with an accuracy of 92%. The proposed method can be implemented in real-time during the surgery to model the neurophysiological nonlinearity along the path of the electrode trajectory during insertion.