Unraveling The Evolution And Diversity Of Giant Plastid Genomes In Chlamydomonadalean Green Algae

Organelle genomes are known to have large sizes and substantial non-coding content, despite conserved coding regions and low substitution rates. Notably, volvocine green algae exhibit significant variation in plastid genome size, with some species harboring ptDNA ten times larger than the average. To explain this variability, my thesis explores two hypotheses. The first proposes that genetic divergence accumulates due to weak negative selection and genetic drift, resulting in similar evolution rates for coding and non-coding regions. The second suggests high evolution rates in non-coding sequences are due to error-prone repair mechanisms. Analyzing new plastid genomes from volvocine green algae, I found a potential for high silent-site substitution rates in intergenic regions. My analysis shows that these hypotheses can be applied to plastid genomes of close relatives to advance our understanding of the mechanisms of sequence evolution specific to non-coding DNA accumulation within the volvocine green algae

Photon Absorption Remote Sensing Imaging of Breast Needle Core Biopsies Is Diagnostically Equivalent to Gold Standard H&E Histologic Assessment

Photon absorption remote sensing (PARS) is a new laser-based microscope technique that permits cellular-level resolution of unstained fresh, frozen, and fixed tissues. Our objective was to determine whether PARS could provide an image quality sufficient for the diagnostic assessment of breast cancer needle core biopsies (NCB). We PARS imaged and virtually H&E stained seven independent unstained formalin-fixed paraffin-embedded breast NCB sections. These identical tissue sections were subsequently stained with standard H&E and digitally scanned. Both the 40× PARS and H&E whole-slide images were assessed by seven breast cancer pathologists, masked to the origin of the images. A concordance analysis was performed to quantify the diagnostic performances of standard H&E and PARS virtual H&E. The PARS images were deemed to be of diagnostic quality, and pathologists were unable to distinguish the image origin, above that expected by chance. The diagnostic concordance on cancer vs. benign was high between PARS and conventional H&E (98% agreement) and there was complete agreement for within-PARS images. Similarly, agreement was substantial (kappa > 0.6) for specific cancer subtypes. PARS virtual H&E inter-rater reliability was broadly consistent with the published literature on diagnostic performance of conventional histology NCBs across all tested histologic features. PARS was able to image unstained tissues slides that were diagnostically equivalent to conventional H&E. Due to its ability to non-destructively image fixed and fresh tissues, and the suitability of the PARS output for artificial intelligence assistance in diagnosis, this technology has the potential to improve the speed and accuracy of breast cancer diagnosis