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Renal proximal tubular cells are highly vulnerable to different types of assaults during filtration and reabsorption, leading to acute renal dysfunction and eventual chronic kidney diseases (CKD). The chemotherapeutic drug cisplatin elicits cytotoxicity causing renal tubular cell death, but its executing mechanisms of action are versatile and elusive. Here, we show that cisplatin induces renal tubular cell apoptosis and ferroptosis by disrupting glutathione (GSH) metabolism. Upon cisplatin treatment, GSH metabolism is impaired leading to GSH depletion as well as the execution of mitochondria-mediated apoptosis and lipid oxidation-related ferroptosis through activating IL6/JAK/STAT3 signaling. Inhibition of JAK/STAT3 signaling reversed cell apoptosis and ferroptosis in response to cisplatin induction. Using a cisplatin-induced acute kidney injury (CAKI) mouse model, we found that inhibition of JAK/STAT3 significantly mitigates cisplatin nephrotoxicity with a reduced level of serum BUN and creatinine as well as proximal tubular distortion. In addition, the GSH booster baicalein also reclaims cisplatin-induced renal tubular cell apoptosis and ferroptosis as well as the in vivo nephrotoxicity. In conclusion, cisplatin disrupts glutathione metabolism, leading to renal tubular cell apoptosis and ferroptosis. Rewiring glutathione metabolism represents a promising strategy for combating cisplatin nephrotoxicity.

Few evidence-based interventions exist to improve person-centred maternity care in low-resource settings. This study aimed to understand whether a quality improvement (QI) intervention could improve person-centred maternity care (PCMC) experiences for women delivering in public health facilities in Kenya. A pre-post design was used to examine changes in PCMC scores across three intervention and matched control facilities at baseline (n = 491) and endline (n = 677). A QI intervention, using the Model for Improvement, was implemented in three public health facilities in Nairobi and Kiambu Counties in Kenya. Difference-in-difference analyses using models that included main effects of both treatment group and survey round was conducted to understand the impact of the intervention on PCMC scores. Findings suggest that intervention facilities' average total PCMC score decreased by 5.3 points post-intervention compared to baseline (95% CI: -8.8, -1.9) and relative to control facilities, holding socio-demographic and facility variables constant. Additionally, the intervention was significantly associated with a 1.8-point decrease in clinical quality index pre-post-intervention (95% CI: -2.9, -0.7), decreased odds of provider visits, and less likelihood to plan to use postpartum family planning. While improving the quality of women's experiences during childbirth is a critical component to ensure comprehensive, high-quality maternity care experiences and outcomes, further research is required to understand which intervention methods may be most appropriate to improve PCMC in resource-constrained settings.

Latinx physician rates are lower than non-Latinx white physicians. Many pathway programs to careers in medicine have been established for underrepresented students, yet few focus on premedical college education or undergraduate pathway programs, which marks a critical junction in the commitment to and preparation for application to medical school. Moreover, little is known about the program components which prepare and support learners. Framed by Swail's Model for Persistence and Achievement, we characterize how a given program's components impact support and growth for participating students. Using the process step of the Context, Input, Process, and Product evaluation model, we conducted focus groups at the end of the program, with four cohorts of student participants between 2019 and 2022. Focus groups identified strengths and limitations in content and delivery to improve program effectiveness and plan for the future of a program. We used thematic analysis, following an inductive approach, to analyze data from transcribed focus groups. A total of 66 of 81 (81.5%) students participated in focus groups. Students described that supportive program components include long-term mentorship and advising that builds trust, academic preparation for medical school, early exposure to clinical career exploration, tools to articulate students' personal narrative, methods to recognize and address challenging situations in the professional environment, community leadership development, and leveraging health policy and advocacy to empower students to create systems change within communities. Our findings affirm and provide a needed account of program components known to be contributors to student success in undergraduate pathway programs. Our evaluation also characterizes additional supportive processes not discussed elsewhere. Our findings contribute to knowledge about development and implementation of undergraduate pathway programs and the components by which these programs create opportunities for success among underrepresented students aspiring to careers in medicine.

OBJECTIVES: Artificial intelligence (AI) holds great promise for transforming the healthcare industry. However, despite its potential, AI is yet to see widespread deployment in clinical settings in significant part due to the lack of publicly available clinical data and the lack of transparency in the published AI algorithms. There are few clinical data repositories publicly accessible to researchers to train and test AI algorithms, and even fewer that contain specialized data from the perioperative setting. To address this gap, we present and release the Medical Informatics Operating Room Vitals and Events Repository (MOVER). MATERIALS AND METHODS: This first release of MOVER includes adult patients who underwent surgery at the University of California, Irvine Medical Center from 2015 to 2022. Data for patients who underwent surgery were captured from 2 different sources: High-fidelity physiological waveforms from all of the operating rooms were captured in real time and matched with electronic medical record data. RESULTS: MOVER includes data from 58 799 unique patients and 83 468 surgeries. MOVER is available for download at https://doi.org/10.24432/C5VS5G, it can be downloaded by anyone who signs a data usage agreement (DUA), to restrict traffic to legitimate researchers. DISCUSSION: To the best of our knowledge MOVER is the only freely available public data repository that contains electronic health record and high-fidelity physiological waveforms data for patients undergoing surgery. CONCLUSION: MOVER is freely available to all researchers who sign a DUA, and we hope that it will accelerate the integration of AI into healthcare settings, ultimately leading to improved patient outcomes.

INTRODUCTION: Men with a detectable PSA after radical prostatectomy (RP) are often offered salvage therapy while those with an undetectable PSA are monitored. We aim to better characterize the natural history of men with an initially undetectable PSA who subsequently developed a detectable PSA > 6 months after RP. METHODS: Retrospective analysis of men who underwent RP for clinically localized prostate cancer at the University of California, San Francisco from 2000 to 2022. The primary outcome was biochemical recurrence, defined as 2 consecutive PSA > = 0.03 ng/mL starting 6 months after surgery. Secondary outcomes were salvage treatment, post-salvage treatment, metastasis free survival (MFS), prostate cancer specific mortality (PCSM), and all-cause mortality (ACM). This cohort was compared to a previously described cohort who had an immediately detectable post-operative PSA. RESULTS: From our cohort of 3348 patients, we identified 2868 men who had an undetectable post-op PSA. Subsequently, 642 men had a delayed detectable PSA at a median of 25 months (IQR 15, 43) with median follow-up of 72 months after RP. PSA at time of failure was <0.10 ng/mL for 65.7% of men. Of those with a delayed detectable PSA, 46% underwent salvage treatment within 10 years after RP at a median PSA of 0.08 ng/mL (IQR 0.05, 0.14). High CAPRA-S score (HR 1.09, CI 1.02-1.17, p = 0.02) and PSA doubling time (PSA-DT) of <6 months (HR 7.58, CI 5.42-10.6, p < 0.01) were associated with receiving salvage treatment. After salvage treatment, 62% of men had recurrent PSA failure within 10 years. Overall, MFS was 92%, PCSM 3%, and ACM 6% at 10 years. For those who received tertiary treatment for recurrent PSA failure, MFS was 54%, PCSM 23% and ACM 23% at 10 years time. CONCLUSIONS: Men who develop a detectable PSA > 6 months post-operatively may have excellent long-term outcomes, even in the absence of salvage therapy.

Emerging technological advances hold potential to assist the long-term care (LTC) workforce in caring for an aging population in the home and LTC settings. Technology may alter workforce needs and mitigate rising workforce demand. This study identified and assessed emerging technologies that may assist, replace, and/or support recruitment and retention of the LTC workforce and identified barriers and facilitators to their implementation. We identified a variety of technologies with applications for LTC, created a taxonomy of technology types and functions across LTC settings, and conducted semi-structured interviews with a sample of company leaders to assess perceived impact of their products and services on the LTC workforce. Thematic analysis of those interviews found that technology is not currently positioned to replace the LTC workforce but may facilitate work and support worker recruitment and retention. More rigorous evaluation of technologies in LTC and financing mechanisms are needed to support widespread adoption.

Scientific computing sometimes involves computation on sensitive data. Depending on the data and the execution environment, the HPC (high-performance computing) user or data provider may require confidentiality and/or integrity guarantees. To study the applicability of hardware-based trusted execution environments (TEEs) to enable secure scientific computing, we deeply analyze the performance impact of AMD SEV and Intel SGX for diverse HPC benchmarks including traditional scientific computing, machine learning, graph analytics, and emerging scientific computing workloads. We observe three main findings: 1) SEV requires careful memory placement on large scale NUMA machines (1×−3.4× slowdown without and 1×−1.15× slowdown with NUMA aware placement), 2) virtualization−a prerequisite for SEV−results in performance degradation for workloads with irregular memory accesses and large working sets (1×−4× slowdown compared to native execution for graph applications) and 3) SGX is inappropriate for HPC given its limited secure memory size and inflexible programming model (1.2×−126× slowdown over unsecure execution). Finally, we discuss forthcoming new TEE designs and their potential impact on scientific computing.

A well-mixed diluted sample is essential for unbiased measurement of cookstove emissions. Most cookstove testing labs employ a dilution tunnel, also referred to as a “duct,” to mix clean dilution air with cookstove emissions before sampling. It is important that the emissions be well-mixed and unbiased at the sampling port so that instruments can take representative samples of the emission plume. Some groups have employed mixing baffles to ensure the gaseous and aerosol emissions from cookstoves are well-mixed before reaching the sampling location [2, 4]. The goal of these baffles is to to dilute and mix the emissions stream with the room air entering the fume hood by creating a local zone of high turbulence. However, potential drawbacks of mixing baffles include increased flow resistance (larger blowers needed for the same exhaust flow), nuisance cleaning of baffles as soot collects, and, importantly, the potential for loss of PM2.5 particles on the baffles themselves, thus biasing results. A cookstove emission monitoring system with baffles will collect particles faster than the duct’s walls alone. This is mostly driven by the available surface area for deposition by processes of Brownian diffusion (through the boundary layer) and turbophoresis (i.e. impaction). The greater the surface area available for diffusive and advection-driven deposition to occur, the greater the particle loss will be at the sampling port. As a layer of larger particle “fuzz” builds on the mixing baffles, even greater PM2.5 loss could occur. The micro structure of the deposited aerosol will lead to increased rates of particle loss by interception and a tendency for smaller particles to deposit due to impaction on small features of the micro structure. If the flow stream could be well-mixed without the need for baffles, these drawbacks could be avoided and the cookstove emissions sampling system would be more robust.

Cycle-level architectural simulation of Trusted Execution Environ- ments (TEEs) can enable extensive design space exploration of these secure architectures. Existing architectural simulators which sup- port TEEs are either based on hardware-level implementations or abstract analytic models. In this paper, we describe the implementation of the gem5 models necessary to run and evaluate the RISC- V-based open source TEE, Keystone, and we discuss how this simulation environment opens new avenues for designing and studying these trusted environments. We show that the Keystone simulations on gem5 exhibit similar performance as the previous hardware eval- uations of Keystone. We also describe three simple example use cases (understanding the reason of trusted execution slowdown, performance of memory encryption, and micro-architecture impact on trusted execution performance) to demonstrate how the ability to simulate TEEs can provide useful information about their behavior in the existing form and also with enhanced designs.