PATENT CLAIM ANALYSIS

Application Number: 15909699
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-07
Patent Classification: ["356", "072000"]

Abstract:
The present invention relates to a method and system for identifying mechanical properties of a cell nucleus through a label-free cell analysis based on Brillouin light scattering techniques. The present application additionally provides a method and system for identifying cancerous cells based on mechanical properties of the cell nucleus.

Claim (Index 12):
A system for obtaining one or more Brillouin metrics associated with a Brillouin scattering spectrum at multiple points, wherein a least one point is within a nucleus of at least one cell in a sample, the system comprising:\n an illumination source illuminating the sample by a light beam along a first direction; one or more lenses collecting a Brillouin scattered light emitted from the sample in response to the illuminating light beam; an optical arrangement to receive the Brillouin scattered light from the one or more lenses, the optical arrangement to induce a spectral dispersion; a detection unit to detect a spatio-spectral pattern of the Brillouin scattered light, wherein the one or more lenses, the optical arrangement, and the detection unit are positioned along a second direction, wherein multiple points of the sample along the illuminating light beam are measured simultaneously; a processor executing instructions for: calibrating the spectral pattern at each spatial point at the detection unit; and calculating the one or more Brillouin metrics at each measured sample point based on the detected spatio-spectral pattern.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 90.0
- Lexical Diversity: 1.59375
- Patent Class: 356.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15388582', '12114081', '14683066', '16318845', '11672571']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5879922900390683
- 35 USC 102 Novelty (BERT): 0.6401236508140672
- Combined Prediction Score: 0.5932054261165682
- Mean Citation Score: 283.921224
- Max Citation Score: 603.67206
- Similarity Product: 587.5450086086298

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test