Sex determination is a crucial process in many organisms and there are many ways in which it is regulated, including through genetic and environmental mechanisms. Despite its popularity as a model for development and disease research, the precise mechanisms of zebrafish (Danio rerio) sex determination remain uncertain. Zebrafish lack the typical heteromorphic sex chromosomes present in many other species, and no specific chromosome or gene that determine sex has been conclusively identified. In a preliminary experiment, a genetic analysis found sex was associated with inheritance of single nucleotide polymorphisms (SNPs) from various regions of the genome. To test the reproducibility of this observation, we used PCR and Sanger sequencing to identify SNPs in candidate causal regions. We tested these to obtain genotypes of individual zebrafish. These fish are being crossed to assess whether significant deviations from genotype ratios are found in males and females, which would suggest that loci linked to these SNPs are in fact involved in sex determination. This work attempts to further elucidate the genetic contribution to sex determination in zebrafish.

The world’s largest high-energy particle accelerator, the Large Hadron Collider, relies on sub-millisecond processing performed on massive amounts of data coming out of its particle detection system, which is due for a major upgrade in 2024. The old particle detection chips will be upgraded to RD53B chips with faster data transmission, allowing for more complicated data processing. The readout systems that interact with the particle detection chips, YARR and FELIX, need to be tested with the RD53B chips and debugged before the system is put in place. The goal of our research is to create an emulator of the RD53B chip that can produce dynamically generated pseudo-realistic data at the same rates that would be seen in the Large Hadron Collider without the need for heavy radiation. This will allow for readout software to be fully functional and debugged before the actual RD53B chips are fabricated and placed into the Large Hadron Collider. We are using Field-Programmable Gate Arrays (FPGAs) to mimic the hardware inside the real RD53B chips. In place of RD53B’s analog sensors, we have substituted digital logic that generates pseudo-realistic data because FPGAs cannot emulate analog hardware. The alpha version of the RD53B emulator with basic communication and pre-programmed data was completed in February. Recently, the beta version of the emulator with dynamically generated data was completed, and we have been testing communication between the emulator and FELIX. With the beta version of the RD53B emulator tested and verified by us, the developers of YARR and FELIX will use our hardware to help verify that their systems will provide accurate readouts from the real RD53B chips. The next steps for the RD53B emulator include a hardware data decompression accelerator, as well as any additional features requested by the YARR and FELIX teams.

Filtering the data produced by the Large Hadron Collider (LHC) is computationally challenging due to the sheer quantity of the data, on the scale of hundreds of terabytes per second. In the coming years, data production for the LHC is projected to increase by a factor of 15 with the high luminosity upgrade. Machine learning algorithms could provide pattern recognition capable of filtering data produced by the LHC. Specialized hardware could increase the throughput to match the data rates required by the LHC. We analyzed several cloud-based specialized hardware solutions including Amazon Web Service FPGAs, Microsoft’s Brainwave Service, Google’s TPU, and NVIDIA GPUs to compare the performance of each of them for particle physics application. The networks accelerated were trained on a variety of data including: Top vs QCD quark classification, Hadron calorimeter data, and electron energy regression. These experiments demonstrate the feasibility of machine learning algorithms in high throughput required situations such as high energy particle physics.

Osteoporosis is the leading cause of decreased bone density in elderly patients, putting them at increased risk of insufficiency fractures. Surgical fixation of these fractures faces high rates of failure in part due to the difficulties in achieving secure fixation of hardware in weakened bones. This has become an increasingly prominent issue in recent years due to the notable increase in sacral insufficiency fractures. This project studies the distribution of bone density across the cortical and trabecular bone of the sacrum in order to highlight areas of variable bone density for better surgical planning of screw placement. We hypothesized that there would be significant differences in local cortical and trabecular bone density associated with age and sex. CT scans of the abdomen/pelvis were obtained for 50 patients without fractures. The sacral bones were segmented and manually edited to produce a 3D model of the sacrum. Bone density values were then determined for the full bone from calibrated CT data. This allowed us to create a linear model including age and sex as a predictor of bone density at each of the surface and internal points. A heat map of the bone models was created using a color scale in order to visualize the cortical and trabecular bone mineral density. A trajectory following the typical path of fixation screws in the S1 and S2 segments were manually identified on these bone models and density values across this were estimated. We were able to locate regions of the sacrum where bone mineral density was significantly associated with age as well as sex. This data can be used to identify areas to avoid or target during the surgical planning of screw fixation to improve screw purchase. Further cadaveric biomechanical investigations are suggested to explore this concept. 

In order for cells to generate copies of themselves they must undergo a highly complex process called mitosis. During mitosis, many enzymes called protein kinases work together to ensure both daughter cells inherit the correct number of chromosomes when the cell divides. Polo-like kinase 1 (Plk1) is a protein kinase that regulates several events during mitosis including centrosome maturation, spindle assembly, sister chromatid cohesion, and cytokinesis. Recently, the A-kinase anchoring protein Gravin (AKAP12) has been implicated in regulating Plk1 function at mitotic centrosomes. Specifically, loss of Gravin has been linked to defective protein signaling at centrosomes, chromosome misalignment, and increased incidence of micronuclei (small nuclei, an aberration often seen in cancer). However, while previous studies used shRNA-mediated knockdown to reduce Gravin levels in cells, it remains unclear how complete loss of this scaffold in human cells influences mitotic signaling events. To test this, our lab generated Gravin knockout U2OS (osteosarcoma) cells using CRISPR/Cas9 genome editing. First, I employed a combination of immunohistochemical staining and quantitative imaging tools to assess how Gravin loss affected chromosome alignment, micronuclei formation, and gamma tubulin accumulation at centrosomes. I found that loss of Gravin in U2OS and HeLa cells caused misaligned chromosomes and micronuclei. Additional experiments I conducted revealed that Gravin-depleted U2OS, HeLa, and MEF cells presented aberrant gamma tubulin accumulation at mitotic spindle poles. Next, a local drug-targeting approach was used to specifically inhibit Plk1 activity at mitotic spindle poles in U2OS cells. I determined that localized inhibition of Plk1 produced similar mitotic defects as observed in cells lacking Gravin. Collectively, these findings suggest that Gravin is required for coordinating proper Plk1 signaling at centrosomes during mitosis while the loss of this scaffold protein leads to mitotic defects. Future work will uncover downstream substrates of Gravin-anchored Plk1 that becomes dysregulated in cells lacking Gravin.

Adolescents with newly diagnosed T1D are at risk for poor physical and psychosocial outcomes. We explored associations between glycemic control (A1C) with diabetes-distress, resilience, and psychosocial comorbidities (e.g., depression) over the first five years of diagnosis. Adolescents, aged 10-17, with newly diagnosed T1D completed validated diabetes-distress and resilience scales one-year post-diagnosis. Psychosocial comorbidities and A1C were extracted from patient charts for 5-years from diagnosis, and A1C values were averaged per year. Regression analyses were used to investigate associations between resilience, diabetes-distress and psychosocial comorbidities with A1C. A1C was assessed annually up to five years post-diagnosis. At one-year post-diagnosis, N=60 adolescents (M=13.22±2.09 years) completed distress (M=27.97±7.01) and resilience scales (M=40.35±17.10). Average A1C at 1-year was 7.73± 1.57 and at 5-years was 8.78 ±1.92. 14% of the sample had at least one psychosocial comorbidity at diagnosis. Between years 1-5 post diagnosis, 28.6% of the sample had at least one comorbidity. The most common comorbidities were depression and anxiety. Diabetes-distress was associated with average A1C in the second year (F(1,29)=4.397, p=.045, R2=.132), third year, (F(1,27)=6.596, p=.016, R2=.196), fourth year, (F(1,24)=10.196, p=.004, R2=.298), and fifth year post-diagnosis (F(1,19)=10.665, p=.004, R2=.360). Resilience was associated with average A1C in the second year (F(1,29)=6.848, p=.014, R2=.191) and fifth years (F(1,19)=4.790, p=.041, R2=.201) post-diagnosis. Total psychosocial comorbidities at diagnosis was associated with average A1C in the second year (F(1,49)=2.209, p<.01), third year (F(1,45)=7.925, p<.01), and fifth year (F(1,28)=7.919, p<.01) post diagnosis. The first year of diagnosis for adolescents with T1D is crucial for detecting patients who are at a higher risk for developing poorer health outcomes. Adolescents who present with psychosocial comorbidities at diagnosis and report poor resilience and high distress one year later are at risk for subsequent poor glycemic control.