Probing the electronic properties of the electrified silicon/water interface by combining simulations and experiments

Silicon (Si) is broadly used in electrochemical and photoelectrochemical devices, where the capacitive and Faradaic reactions at the Si/water interfaces are critical for signal transduction or noise generation. However, probing the electrified Si/water interface at the microscopic level remains a challenging task. Here we focus on hydrogenated Si surfaces in contact with water, relevant to transient electronics and photoelectrochemical modulation of biological cells and tissues. We show that by carrying out first-principles molecular dynamics simulations of the Si(100)/water interface in the presence of an electric field we can realistically correlate the computed flat-band potential and tunneling current images at the interface with experimentally measured capacitive and Faradaic currents. Specifically, we validate our simulations in the presence of bias by performing pulsed chronoamperometry measurements on Si wafers in solution. Consistent with prior experiments, our measurements and simulations indicate the presence of voltage-dependent capacitive currents at the interface. We also find that Faradaic currents are weakly dependent on the applied bias, which we relate to surface defects present in newly prepared samples

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

First-Principles Studies of Water at Semiconductor Interfaces

Water plays a pivotal role in a wide array of physical and chemical processes. For example, in several batteries, photoelectrochemical cells, and bioelectronic devices, solid-water interfaces are present and critically influence the devices' properties. Water also constitutes a major portion of the Earth's crust and mantle, participating in several geological processes under high-pressure, high-temperature conditions, including metasomatism, carbon transport, and continental crust evolution. To understand the electronic characteristics and structural modifications of water molecules at interfaces or in extreme environments, computational modeling at the atomistic scale is an essential tool. In this thesis, we employed first-principles simulations to study semiconductor-water interfaces and water under extreme conditions. We focused on hydrogenated silicon (Si) surfaces interfaced with water, given silicon's widespread use in electronic devices. Furthermore, we investigated water under pressures and conditions relevant to the Earth's interior (11 GPa and 1000 K). In our interfacial studies, we explored the electronic structure of the hydrogenated Si(100) and water interfaces by performing first-principles molecular dynamics simulations in the presence of an electric field. We correlated the computed flat-band potential and tunneling current images at the interface with experimentally measured capacitive and Faradaic currents. Consistent with chronoamperometry measurements, our simulations indicate that the capacitive currents at the interface are voltage-dependent, while the Faradaic currents are weakly dependent on the applied voltage but are related to surface defects. Next, we investigated the dynamic and vibrational properties of water at the electrified interface. We analyzed the H-bond structures and orientation of water molecules, and we related the structural properties of interfacial water molecules to the OH stretching mode in Raman spectra. The calculated spectra reveal a combined effect of the surface and the electric field on the Raman features observed at the interface. The presence of the surface leads to low-coordinated hydrogen bonding configurations and, hence, a blue-shift of the O-H stretching band relative to that of bulk water. The electric field regulates the orientation of interfacial water molecules, resulting in a stable H-bond network that gives rise to specific Raman peaks in the low-frequency region of the spectrum. Our computational studies provided comprehensive insights into the electronic and dynamic properties of Si-based electrochemical or photoelectrochemical devices. In our study of water in extreme conditions, we carried out calculations of photoelectron spectra of water and a simple solution of NaCl under high pressure and high temperature. We combined first-principles and deep-potential molecular dynamics with dielectric-dependent hybrid functionals. We found notable changes in the spectra relative to ambient conditions; in particular, we observed anion energy levels closer to the valence band maximum of the liquid than those observed at ambient conditions, indicating that as pressure and temperature are increased, the defect levels of chloride and hydroxide ions in water may eventually lie below the valence band maximum of water. We also elucidated the electronic states associated with proton transfer events at high pressure by calculating the projected density of states. Our results represent an important first step in predicting the electronic properties of solutions in supercritical conditions

A Novel Nomogram Combined the Aggregate Index of Systemic Inflammation and PIRADS Score to Predict the Risk of Clinically Significant Prostate Cancer

Background. This study is aimed at constructing a nomogram to predict the risk of clinically significant prostate cancer (csPCa) based on the aggregate index of systemic inflammation (AISI) and prostate imaging-reporting and data system version (PIRADS) score. Methods. Clinical data on patients who had undergone initial prostate biopsy from January 2019 to December 2021 were collected. Patients were randomized in a 7 : 3 ratio to the training cohort and the validation cohort. Potential risk factors for csPCa were identified by univariable and multivariate logistic regression. Nomogram was conducted with these independent risk factors, and calibration curves, the receiver operating characteristic (ROC), and decision curve analysis (DCA) were employed to assess the nomogram’s ability for prediction. Results. A total of 1219 patients were enrolled in this study. Multivariate logistic regression identified that age, AISI, total prostatic specific-antigen (tPSA), free to total PSA (f/tPSA), prostate volume (PV), and PIRADS score were potential risk predictors of csPCa, and the nomogram was developed based on these factors. The area under the curve (AUC) of the training cohort and validation cohort was 0.884 (95% CI: 0.862-0.906) and 0.899 (95% CI: 0.867-0.931). The calibration curves showed that the apparent curves were closer to the ideal curves. The DCA results revealed that the nomogram model seemed to have clinical application value per DCA. Conclusion. The nomogram model can efficiently predict the risk of csPCa and may assist clinicians in determining if a prostate biopsy is necessary

Inhibition of cGAS–STING pathway alleviates neuroinflammation-induced retinal ganglion cell death after ischemia/reperfusion injury

Abstract Acute glaucoma is a vision-threatening disease characterized by a sudden elevation in intraocular pressure (IOP), followed by retinal ganglion cell (RGC) death. Cytosolic double-stranded DNA (dsDNA)—a damage-associated molecular pattern (DAMP) that triggers inflammation and immune responses—has been implicated in the pathogenesis of IOP-induced RGC death, but the underlying mechanism is not entirely clear. In this study, we investigated the effect of the inflammatory cascade on dsDNA recognition and examined the neuroprotective effect of the cyclic GMP-AMP (cGAMP) synthase (cGAS) antagonist A151 on a retinal ischemia/reperfusion (RIR) mouse model. Our findings reveal a novel mechanism of microglia-induced neuroinflammation-mediated RGC death associated with glaucomatous vision loss. We found that RIR injury facilitated the release of dsDNA, which initiated inflammatory responses by activating cGAS–stimulator of interferon genes (STING) pathway. Correspondingly, elevated expressions of cGAS and STING were found in retinal samples from human glaucoma donors. Furthermore, we found that deletion or inhibition of cGAS or STING in microglia transfected with poly(dA:dT) specifically decreased microglia activation and inflammation response. We also observed that A151 treatment promoted poly(dA:dT)--stimulated changes in polarization from the M1 to the M2 phenotype in microglia. Subsequently, A151 administered to mice effectively inhibited the cGAS–STING pathway, absent in melanoma 2 (AIM2) inflammasome and pyroptosis-related molecules. Furthermore, A151 administration significantly reduced neuroinflammation, ameliorated RGC death and RGC-related reductions in visual function. These findings provide a unique perspective on glaucomatous neuropathogenesis and suggest cGAS as an underlying target of retinal inflammation to provide a potential therapeutic for acute glaucoma

Azoramide, a novel regulator, favors adipogenesis against osteogenesis through inhibiting the GLP-1 receptor-PKA-β-catenin pathway

Abstract Background The reciprocal fate decision of mesenchymal stem cells (MSCs) to either bone or adipocytes is determined by Wnt-related signaling and the glucagon-like peptide-1 receptor (GLP-1R). Azoramide, an ER stress alleviator, was reported to have an antidiabetic effect. In this study, we investigated the function of azoramide in regulating the lineage determination of MSCs for either adipogenic or osteogenic differentiation. Methods In this study, microcomputed tomography and histological analysis on bone morphogenetic protein (BMP)2-induced parietal periosteum bone formation assays, C3H10T1/2 and mouse bone marrow MSC-derived bone formation and adipogenesis assays, and specific staining for bone tissue and lipid droplets were used to evaluate the role of azoramide on the lineage determination of MSC differentiation. Cells were harvested for Western blot and quantitative real-time polymerase chain reaction (PCR), and immunofluorescence staining was used to explore the potential mechanism of azoramide for regulating MSC differentiation. Results Based on MSC-derived bone formation assays both in vivo and in vitro, azoramide treatment displayed a cell fate determining ability in favor of adipogenesis over osteogenesis. Further mechanistic characterizations disclosed that both the GLP-1R agonist peptide exendin-4 (Ex-4) and GLP-1R small interfering (si)RNA abrogated azoramide dual effects. Moreover, cAMP-protein kinase A (PKA)-mediated nuclear β-catenin activity was responsible for the negative function of azoramide on bone formation in favor of adipogenesis. Conclusions These data provide the first evidence to show that azoramide may serve as an antagonist against GLP-1R in MSC lineage determination

Introduction to Community Service-Learning (SRCL 1000)

Introduction to Community Service-Learning is a popular general elective open to first to fourth year international and domestic students from a variety of disciplines across campus. Every semester each student volunteers at one of 35 local not-for-profit organizations for a full semester. Students are required to complete 24 hours of service as part of their course work. In this poster session, 10 not-for-profit organizations will be represented by 25 SRCL 1000 students and one visiting scholar. They will demonstrate personal reflections on their service experiences, how their experiences connect to the course work and their organizations, and what they will take back to their own communities after the course is over. The non-for-profits represented are: 11:00 am - 1:30 pm: JUMP (Zifan Guo, Connor Shanks-Sim, Wongsapat Piammanastham & Junhao Li) The Kamloops Food Bank (Austin Ngai & Di Zhang) The ReStore - Habitat for Humanity (Cranstonique Johnson & Sahithi Yarlagadda) St.John Ambulance (Dany Shumbusho) Maple Leaf School (Xingtong Ye, Kanwalpreet Kaur & Wenxuan Fan) BC SPCA (Junxiu Lai, Zhixuan Li, Yuhui Xi & Ayano Yasuda) 2:00 pm - 4:00 pm: JUMP (Tatsuki Shintani, Jinfeng Liu, Yoonkyung Lee, Jingyi Wu & Dhanesh Godbole) Kamloops Immigrant Services (Kazim Amirali) Overlander Residential Care (Francine Smith) Chartwell - Ridgepointe Seniors Living (Ryoko Nanahara & Hina Shimizu

Additional file 1: of Azoramide, a novel regulator, favors adipogenesis against osteogenesis through inhibiting the GLP-1 receptor-PKA-β-catenin pathway

Binding Mode Prediction of Azoramide and figure legend of additional file 2. (DOCX 31 kb