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Navigating dilemmas involving conflicting values is challenging even for humans in high-stakes domains, let alone for AI, yet prior work has been limited to everyday scenarios. To close this gap, we introduce CLASH (Character perspective-based LLM Assessments in Situations with High-stakes), a meticulously curated dataset consisting of 345 high-impact dilemmas along with 3,795 individual perspectives of diverse values. CLASH enables the study of critical yet underexplored aspects of value-based decision-making processes, including understanding of decision ambivalence and psychological discomfort as well as capturing the temporal shifts of values in the perspectives of characters. By benchmarking 14 non-thinking and thinking models, we uncover several key findings. (1) Even strong proprietary models, such as GPT-5 and Claude-4-Sonnet, struggle with ambivalent decisions, achieving only 24.06 and 51.01 accuracy. (2) Although LLMs reasonably predict psychological discomfort, they do not adequately comprehend perspectives involving value shifts. (3) Cognitive behaviors that are effective in the math-solving and game strategy domains do not transfer to value reasoning. Instead, new failure patterns emerge, including early commitment and overcommitment. (4) The steerability of LLMs towards a given value is significantly correlated with their value preferences. (5) Finally, LLMs exhibit greater steerability when reasoning from a third-party perspective, although certain values (e.g., safety) benefit uniquely from first-person framing. 

The rapid development of adeno-associated viral vectors (AAV) to treat genetic disease has placed increased emphasis on the design of efficient downstream manufacturing processes. This study investigated the potential of using single pass tangential flow filtration (SPTFF) as a novel means of concentrating and purifying AAV clarified cell lysate (CCL). AAV stability studies revealed the shear-sensitive nature of the AAV capsids, with evidence of aggregation and fragmentation following repeated passages through a peristaltic pump (as would occur during batch ultrafiltration). SPTFF experiments focused on first identifying the membrane(s) that permitted high yield of AAV (negligible sieving into the permeate) along with substantial host cell protein (HCP) removal. Experiments were then performed at various permeate fluxes, which revealed that stable SPTFF processes can be achieved by operating below a critical flux for fouling (Jfoul). 300 kDa regenerated cellulose (RC) membranes were identified as optimal for this application, given their ability to provide complete AAV retention with high removal of HCP (>90%) when operated below Jfoul. The critical flux during SPTFF was increased by preconditioning the CCL through a positively-charged adsorptive filter, which reduced the concentration of foulants prior to SPTFF. These studies provide the first demonstration of SPTFF for the concentration and purification of AAV clarified cell lysate while minimizing shear exposure. 

Abstract Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decision-making and informs hospital operations involving factors such as patient flow, elective cases, and human resources allocation, while also informing quality of care and risk considerations. The aim of the research reported in this paper is to use survival analysis to model General Internal Medicine (GIM) length of stay, and to use Shapley value to support interpretation of the resulting model. Survival analysis aims to predict the time until a specific event occurs. In our study, we predict the duration from patient admission to discharge to home, i.e., in-hospital length of stay. In addition to discussing the modeling results, we also talk about how survival analysis of hospital length of stay can be used to guide improvements in the efficiency of hospital operations and support the development of quality metrics. 

ABSTRACT To enable adeno‐associated viral vectors (AAV) to achieve their maximum potential, next‐generation manufacturing processes must be developed to make gene therapies more affordable and accessible. This study focused on the design of two different intensified AAV downstream manufacturing processes at bench and pilot scale. Novel clarification methods were studied at bench scale, including the use of BioOptimal™ MF‐SL tangential flow microfilters for continuous removal of cell debris. Membrane adsorbers were used for further clarification, including DNA removal. Single pass tangential flow filtration (SPTFF) was implemented at bench scale by feeding the clarified cell lysate (CCL) into two Pellicon XL50 cassettes with 100 kDa regenerated cellulose membranes. At pilot scale, a multi‐membrane staged SPTFF module was designed to concentrate 10 L of AAV CCL. Both SPTFF systems provided 12X inline volumetric concentration with AAV yield > 99% after an appropriate buffer chase. Host cell protein removal was 48% and 37% for the bench and pilot scale processes, respectively. As an initial proof‐of‐concept, an integrated process was developed at pilot‐scale which linked clarification, SPTFF, and affinity chromatography. The integrated process offered an 81% reduction in total operating time (due to the reduced volume of load material for the affinity column after preconcentration by SPTFF), 36% improvement in affinity resin utilization (due to the higher AAV concentration in the column load), and an estimated 10% reduction in raw material costs. These improvements translated to an 8.5‐fold increase in overall productivity compared to an equivalent batch process, underscoring the potential for SPTFF to intensify large‐scale AAV downstream processing. 

Abstract We prove lower bounds on the density of regular minimal cones of dimension less than seven provided the complements of the cones are topologically nontrivial.