Strategies for controlling afucosylation in monoclonal antibodies during upstream manufacturing.

Core fucosylation is a highly prevalent and significant feature of N-glycosylation in therapeutic monoclonal antibodies produced by mammalian cells where its absence (afucosylation) plays a key role in treatment safety and efficacy. Notably, even slight changes in the level of afucosylation can have a considerable impact on the antibody-dependent cell-mediated cytotoxicity. Therefore, implementing control over afucosylation levels is important in upstream manufacturing to maintain consistent quality across batches of product, since standard downstream processing does not change afucosylation.

CNN-Based Brain Tumor Detection Model Using Local Binary Pattern and Multilayered SVM Classifier.

In this paper, an autonomous brain tumor segmentation and detection model is developed utilizing a convolutional neural network technique that included a local binary pattern and a multilayered support vector machine. The detection and classification of brain tumors are a key feature in order to aid physicians; an intelligent system must be designed with less manual work and more automated operations in mind. The collected images are then processed using image filtering techniques, followed by image intensity normalization, before proceeding to the patch extraction stage, which results in patch extracted images.

Speech as a Biomarker for COVID-19 Detection Using Machine Learning.

The use of speech as a biomedical signal for diagnosing COVID-19 is investigated using statistical analysis of speech spectral features and classification algorithms based on machine learning. It is established that spectral features of speech, obtained by computing the short-time Fourier Transform (STFT), get altered in a statistical sense as a result of physiological changes. These spectral features are then used as input features to machine learning-based classification algorithms to classify them as coming from a COVID-19 positive individual or not.

Unusual upper critical fields of the topological nodal-line semimetal candidate SnNbSe.

We report superconductivity in SnNbSe, a topological nodal-line semimetal candidate with a noncentrosymmetric crystal structure. The superconducting transition temperatureof this compound is extremely sensitive to Sn concentrationand Se deficiency, 5.0 K for SnNbSeand 8.

Fermi surfaces of the topological semimetal CaSnprobed through de Haas van Alphen oscillations.

In the search of topological superconductors, nailing down the Fermiology of the normal state is as crucial a prerequisite as unraveling the superconducting pairing symmetry. In particular, the number of time-reversal-invariant momenta (TRIM) in the Brillouin zone enclosed by Fermi surfaces is closely linked to the topological class of time-reversal-invariant systems, and can experimentally be investigated. We report here a detailed study of de Haas van Alphen quantum oscillations in single crystals of the topological semimetal CaSnwith torque magnetometry in high magnetic fields up to 35 T.