Characterization of an ETV6-NTRK3 rearrangement with unusual, but highly significant FISH signal pattern in a secretory carcinoma of the salivary gland: a case report

Background Fusions of neurotrophic tropomyosin receptor kinase genes NTRK1, NTRK2 and NTRK3 with various partner genes occur in both common and rare tumours and are of paramount predictive value due to the availability of very effective pan-Trk inhibitors like Larotrectinib and Entrectinib. Detection of NTRK fusions is mainly performed by fluorescence in situ hybridization (FISH) and next generation sequencing (NGS). The case described here showed a very unusual, but highly significant FISH signal pattern with an NTRK3 break apart probe, indicative of a functional NTRK3 rearrangement. Case presentation We describe here the case of a male patient who was originally diagnosed with an adenocarcinoma of the parotid gland without evidence of metastases. After the development of multiple lung metastases, an extensive immunohistochemical and molecular examination of archived tumour tissue including analysis of NTRK was performed. NTRK expression was detected by immunohistochemistry (IHC) and then comprehensively analysed further by FISH, quantitative reverse transcription PCR (RT-qPCR), and NGS. NTRK3 break apart FISH showed multiple and very faint single 3′ signals in addition to fusion signals. Quantitative reverse transcription PCR and NGS confirmed an ETV6:exon5-NTRK3:exon15 fusion. Diagnosis was therefore revised to metastatic secretory carcinoma of the salivary gland, and the patient subsequently treated with Larotrectinib, resulting in persisting partial remission. Conclusions Our findings underline the importance to be aware of non-canonical signal patterns during FISH analysis for detection of NTRK rearrangements. Very faint single 3′ signals can indicate a functional NTRK rearrangement and therefore be of high predictive value.

Synthesis and Spectroscopic Characterizations of Ni(II) Thiosemicarbazone Bearing Anthracene

The X-ray structure of 9-anthraldehyde-4-methyl-3-thiosemicarbazone was firstly determined. The Ni(II) complex with this ligand was prepared upon reaction with chloride salt. Mass spectrometry result confirms correct formulation of the complex. Unusual 1H NMR signal pattern of anthracene moiety reveal cis arrangement cemented by intramolecular p–p stackings between aromatic rings. As a result of this interaction, the electronic structure of anthracene ring is perturbed and gives rise to structureless and broad absorption and emission bands.

Hybrid LPG-FBG Based High-Resolution Micro Bending Strain Sensor

Sensitivity and reliability are essential factors for the practical implementation of a wearable sensor. This study explores the possibility of using a hybrid high-resolution Bragg grating sensor for achieving a fast response to dynamic, continuous motion and Bragg signal pattern monitoring measurement. The wavelength shift pattern for real-time monitoring in picometer units was derived by using femtosecond laser Bragg grating processing on an optical wave path with long-period grating. The possibility of measuring the demodulation system’s Bragg signal pattern on the reflection spectrum of the femtosecond laser precision Bragg process and the long-period grating was confirmed. By demonstrating a practical method of wearing the sensor, the application of wearables was also explored. It is possible to present the applicability of sophisticated micro transformation measurement applications in picometer units.

Design of Mirror Therapy System Base on Multi-Channel Surface-Electromyography Signal Pattern Recognition and Mobile Augmented Reality

Numerous studies have proven that the mirror therapy can make rehabilitation more effective on hemiparesis following a stroke. Using surface electromyography (SEMG) to predict gesture presents one of the important subjects in related research areas, including rehabilitation medicine, sports medicine, prosthetic control, and so on. However, current signal analysis methods still fail to achieve accurate recognition of multimode motion in a very reliable way due to the weak physiological signal and low noise-ratio. In this paper, a mirror therapy system based on multi-channel SEMG signal pattern recognition and mobile augmented reality is studied. Besides, wavelet transform method is designed to mitigate the noise. The spectrogram obtained by analyzing electromyography signals is proposed to be used as an image. Two approaches, including Convolutional Neural Network (CNN) and grid-optimized Support Vector Machine (SVM), are designed to classify the SEMG of different gestures. The mobile augmented reality provides a virtual hand movement in the real environment to perform mirror therapy process. The experimental results show that the overall accuracy of SVM is 93.07%, and that of CNN is up to 97.8%.