Gemtelligence: Accelerating Gemstone classification with Deep Learning

The value of luxury goods, particularly investment-grade gemstones, is greatly influenced by their origin and authenticity, sometimes resulting in differences worth millions of dollars. Traditionally, human experts have determined the origin and detected treatments on gemstones through visual inspections and a range of analytical methods. However, the interpretation of the data can be subjective and time-consuming, resulting in inconsistencies. In this study, we propose Gemtelligence, a novel approach based on deep learning that enables accurate and consistent origin determination and treatment detection. Gemtelligence comprises convolutional and attention-based neural networks that process heterogeneous data types collected by multiple instruments. Notably, the algorithm demonstrated comparable predictive performance to expensive laser-ablation inductively-coupled-plasma mass-spectrometry (ICP-MS) analysis and visual examination by human experts, despite using input data from relatively inexpensive analytical methods. Our innovative methodology represents a major breakthrough in the field of gemstone analysis by significantly improving the automation and robustness of the entire analytical process pipeline

Dicer and Hsp104 Function in a Negative Feedback Loop to Confer Robustness to Environmental Stress

SummaryEpigenetic mechanisms can be influenced by environmental cues and thus evoke phenotypic variation. This plasticity can be advantageous for adaptation but also detrimental if not tightly controlled. Although having attracted considerable interest, it remains largely unknown if and how environmental cues such as temperature trigger epigenetic alterations. Using fission yeast, we demonstrate that environmentally induced discontinuous phenotypic variation is buffered by a negative feedback loop that involves the RNase Dicer and the protein disaggregase Hsp104. In the absence of Hsp104, Dicer accumulates in cytoplasmic inclusions and heterochromatin becomes unstable at elevated temperatures, an epigenetic state inherited for many cell divisions after the heat stress. Loss of Dicer leads to toxic aggregation of an exogenous prionogenic protein. Our results highlight the importance of feedback regulation in building epigenetic memory and uncover Hsp104 and Dicer as homeostatic controllers that buffer environmentally induced stochastic epigenetic variation and toxic aggregation of prionogenic proteins