Hyperoxaluria is a major risk factor for the formation of calcium oxalate stones, but dietary restriction of oxalate intake might not be a reliable approach to prevent recurrence of stones. Hence, ...other approaches to reduce urinary oxalate to manage stone disease have been explored. The gut‐dwelling obligate anaerobe Oxalobacter formigenes (OF) has attracted attention for its oxalate‐degrading property. In this review we critically evaluate published studies and identify major gaps in knowledge. Recurrent stone‐formers are significantly less likely to be colonized with OF than controls, but this appears to be due to antibiotic use. Studies in animals and human subjects show that colonization of the gut with OF can decrease urinary oxalate levels. However, it remains to be determined whether colonization with OF can affect stone disease. Reliable methods are needed to detect and quantify colonization status and to achieve durable colonization. New information about oxalate transport mechanisms raises hope for pharmacological manipulation to decrease urinary oxalate levels. In addition, probiotic use of lactic acid bacteria that metabolize oxalate might provide a valid alternative to OF.
OBJECTIVE
To assess the magnitude of variability among 11 formulae for human body surface area (BSA) and then among eight for plasma volume (PV), as used to represent physiological indices for body ...metabolism, drug dosages and body fluid management, and to evaluate the potential cumulative effect of variance inflation with prostate‐specific antigen (PSA) mass as an endpoint.
PATIENTS AND METHODS
In 3020 men undergoing robotic radical prostatectomy (RRP) at the Vattikuti Urology Institute between 2001 and 2008, the variation in BSA and PV formulae was calculated, as well as PSA mass, using analysis of variance (anova), Bland‐Altman plots, linear regression, and correlation analyses.
RESULTS
For estimating BSA, anova indicated significant variance among the 11 formulae used (P < 0.001) with a between‐groups variance of 5.45. Bland‐Altman plots reported bias when the Dubois formula was compared to other BSA formulae. Furthermore the anova for PV, with BSA as a predictor, indicated significant variance among the eight formulae used (P < 0.001), with a mean between‐group variance of 444.4 and a mean inflation factor of 81.5. Scatter plots between one PV formula (Boer) and others had a good linear fit. For PSA mass, anova indicated significant variance (P < 0.001) using PV as a predictor, with a mean between‐group variance of 16 799.6 and a mean variance inflation factor of 37.8.
CONCLUSIONS
There is significant variation in the BSA calculated by commonly used formulae. This variation is carried over and further magnified in the sequential calculation of PV and PSA mass. Hence arbitrary selection of BSA and PV formulae is likely to affect inferences.
This work investigates the potential of tailoring Large Language Models (LLMs), specifically GPT3.5 and GPT4, for the domain of chip testing. A key aspect of chip design is functional testing, which ...relies on testbenches to evaluate the functionality and coverage of Register-Transfer Level (RTL) designs. We aim to enhance testbench generation by incorporating feedback from commercial-grade Electronic Design Automation (EDA) tools into LLMs. Through iterative feedback from these tools, we refine the testbenches to achieve improved test coverage. Our case studies present promising results, demonstrating that this approach can effectively enhance test coverage. By integrating EDA tool feedback, the generated testbenches become more accurate in identifying potential issues in the RTL design. Furthermore, we extended our study to use this enhanced test coverage framework for detecting bugs in the RTL implementations
Power side-channel (PSC) analysis is pivotal for securing cryptographic
hardware. Prior art focused on securing gate-level netlists obtained as-is from
chip design automation, neglecting all the ...complexities and potential
side-effects for security arising from the design automation process. That is,
automation traditionally prioritizes power, performance, and area (PPA),
sidelining security. We propose a "security-first" approach, refining the logic
synthesis stage to enhance the overall resilience of PSC countermeasures. We
introduce ASCENT, a learning-and-search-based framework that (i) drastically
reduces the time for post-design PSC evaluation and (ii) explores the
security-vs-PPA design space. Thus, ASCENT enables an efficient exploration of
a large number of candidate netlists, leading to an improvement in PSC
resilience compared to regular PPA-optimized netlists. ASCENT is up to 120x
faster than traditional PSC analysis and yields a 3.11x improvement for PSC
resilience of state-of-the-art PSC countermeasures
Graph neural network (GNN)-based representations of hardware designs are used in electronic design automation (EDA) tasks like logic synthesis, verification, and hardware security. While promising, ...state-of-the-art methods are supervised and require target labels and/or need different behavioral register transfer level (RTL) codes of the same function as training data to generalize. We propose ConVERTS, a self-supervised netlist contrastive learning method that generalizes well using one-shot RTL of a design. We demonstrate the effectiveness of ConVERTS on two use-cases: (1) netlist classification, and (2) Recovering functionality of obfuscated designs.
