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Case study on force compliant robot arm controller for nasopharyngeal swab insertion
Abstract The nasopharyngeal (NP) swab sample test, commonly used to detect COVID-19 and other respiratory illnesses, involves moving a swab through the nasal cavity to collect samples from the nasopharynx. While typically this is done by human healthcare workers, there is a significant societal interest to enable robots to do this test to reduce exposure to patients and to free up human resources. The task is challenging from the robotics perspective because of the dexterity and safety requirements. While other works have implemented specific hardware solutions, our research differentiates itself by using a ubiquitous rigid robotic arm. This work presents a case study where we investigate the strengths and challenges using compliant control system to accomplish NP swab tests with such a robotic configuration. To accomplish this, we designed a force sensing end-effector that integrates with the proposed torque controlled compliant control loop. We then conducted experiments where the robot inserted NP swabs into a 3D printed nasal cavity phantom. Ultimately, we found that the compliant control system outperformed a basic position controller and shows promise for human use. However, further efforts are needed to ensure the initial alignment with the nostril and to address head motion.
Deep learning-based sex estimation of 3D hyoid bone models in a Croatian population using adapted PointNet++ network
Fine hydrochar in hydrothermal hydrolysate promotes startup and gas production of swine manure anaerobic digestion
Induction of lung mucosal immunity by a next-generation inhaled aerosol COVID-19 vaccine: an open-label, multi-arm phase 1 clinical trial
Behavior of silica mesoporous materials for capacitive deionization desalination
Non-invasive assessment of stem cell DNA integrity in response to environmental stressors
Advanced multiscale machine learning for nerve conduction velocity analysis
LINC01518 functions as an oncogene in head and neck squamous cell carcinoma (HNSCC) by modulating miR-1-3p/Slug and miR-216b-5p/GRP78 axis
Abstract HNSCC is a highly aggressive cancer of the head and neck region, and there is an urgent need to find novel potential targets for its diagnosis and treatment. Long non-coding RNAs (lncRNAs) have emerged as important therapeutic and diagnostic targets for multiple cancers, including HNSCC. LINC01518 promotes the proliferation of oesophageal cancer cells, but the involvement of LINC01518 in HNSCC pathophysiology is unknown. We show that LINC01518 expression is significantly upregulated in high-grade HNSCC tumor samples in comparison to normal tissue, and transforming growth factor- β (TGF-β) promotes LINC01518 expression in HNSCC cell lines. Loss-of-function studies suggest that LINC01518 promotes cell proliferation, migration, and invasion in HNSCC cells. In addition, LINC01518 depletion sensitizes HNSCC cells to cisplatin-mediated apoptosis. Mechanistically, LINC01518 acts as a competitive endogenous RNA and binds to miR-1-3p and miR-216b-5p, resulting in up-regulation of their target genes Slug and GRP78, respectively. Our findings suggest that LINC01518 is an attractive therapeutic target for HNSCC.
Machine learning for experimental design of ultrafast electron diffraction
Pan-cancer copy number analysis identifies optimized size thresholds and co-occurrence models for individualized risk stratification
Abstract Chromosome instability leading to aneuploidy and accumulation of copy number gains or losses is a hallmark of cancer. Copy number alteration (CNA) signatures are increasingly used for cancer risk stratification, but size thresholds for defining CNAs across cancers are variable and the biological and clinical implications of CNA size heterogeneity and co-occurrence are incompletely understood. Here we analyze CNA and clinical data from 691 meningiomas and 10,383 tumors from The Cancer Genome Atlas to develop cancer- and chromosome-specific size-dependent CNA and CNA co-occurrence models to predict tumor control and overall survival. Our results shed light on technical considerations for biomarker development and reveal prognostic CNAs with optimized size thresholds and co-occurrence patterns that refine risk stratification across a diversity of cancer types. These data suggest that consideration of CNA size, focality, number, and co-occurrence can be used to identify biomarkers of aggressive tumor behavior that may be useful for individualized risk stratification.
Multi-scale fusion semantic enhancement network for medical image segmentation
The relationship between paracingulate sulcus length and visual hallucinations in Parkinson’s disease suggests a neurobiological predisposition
Variabilities in the stroking parameters during short course 50 m time trials in all four competitive swimming strokes
Abstract The purpose of this study was to identify intra- and inter-individual variabilities during short course 50 m sprints. Swimming velocity (SV), stroke frequency (SF), and stroke length (SL) for each stroke cycle in 189 male and 160 female swimmers’ 50 m time trials (with their specialised stroke) were analysed. The inter-individual variability for each kinematic variable was analysed using the inter-individual standard deviation of the Gaussian Process regression. Intra-participant variability was analysed using k-means clustering with kinematic data extracted from the first, mid-, and last strokes. In all strokes and both sexes, swimmers showed large inter-individual kinematic variabilities at the first and last strokes, which justified the need to separate these strokes from the clean-swimming segment in race analyses. Intra-individual kinematic patterns were categorised into four clusters with different within-lap SV patterns. Particularly, many front crawl and backstroke swimmers showed a faster velocity in mid-pool than in the transition, while many butterfly swimmers showed the fastest SV in the transition. This might suggest a greater difficulty in the transition technique in alternating strokes than in butterfly. Race analyses should focus on not only the overall trend but also individual variabilities to investigate the swimmers’ behaviour during swimming races.
Expression of ALDH1 isotypes and its potential as a prognostic and diagnostic marker in patients with muscle invasive bladder cancer
Character generation and visual quality enhancement in animated films using deep learning
Near infrared sensitized exciton upconversion luminescence from inorganic perovskite nanocrystals
Abstract Lead halide perovskites serve as an important class of photoelectrical materials in modern technological applications, such as light emitting diodes, photodetectors, and solar cells. However, the inability to respond to near infrared light poses a tight constraint on their performances. This study reports a class of broadband near infrared-responsive inorganic lead halide perovskite nanocrystals, which emit a palette of tunable upconversion luminescence via organic dye-lanthanide tandem sensitization. The coordination of dyes (IR783) to the surface of ytterbium-doped cesium lead halide nanocrystals entails an intense and broad spectral response range of near infrared light (600-860 nm). Sub-10 Wcm−2 light irradiance at 804 nm induced ultrabright exciton luminescence (tunable from 520 to 625 nm), about 27,500 folds brighter than the one without dye sensitization, with upconversion brightness reaching 3.22 M−1cm−1. Transient absorption spectra revealed an ultrafast triplet energy transfer process (9.28 × 108 s−1) from dyes to ytterbium dopants with near-unity efficiency (98.4%), followed by cooperative sensitization that excites delocalized excitons. These broadband near infrared-responsive inorganic perovskite nanocrystals have implications for applications ranging from solar cells to near infrared imaging and sensing.