A Model for Providing Psychological Support to Healthcare Leaders and Teams in Times of Crisis.

OBJECTIVE: Pre-pandemic, the healthcare workforce was already at risk for higher burnout than the general population and, in some roles (e.g., physicians, nurses), at higher risk for clinical distress and suicide. Studies of healthcare workforce well-being during and after past pandemics reflect that distress can persist after a pandemic subsides, if adequate support within the workplace is not forthcoming and accessible. The current report presents the rationale for and development of a wellness consult service to provide support to leaders and teams in an academic medical center during the COVID-19 pandemic and now as teams work to recover and rebuild after years of significant pandemic and other stressors. METHODS: Healthcare workers who participated in supportive Listening Sessions or Interactive Workshops facilitated by the wellness consult service were invited to complete an anonymous post-session survey. RESULTS: Between March 2020 and November 2022, 185 leaders and teams participated in 342 supportive Listening Sessions and Interactive Workshops. Of the respondents to the post-session survey (N = 701), 89% rated the intervention as "good to excellent" and 84% were likely or very likely to recommend this service. Leaders rated the experience more highly than non-leaders (F (1,307) = 13.99, p < 0.001) and were more likely to report feeling emotionally supported (F (1,304) = 19.836, p < 0.001). CONCLUSIONS: Supporting leader and team well-being may be critical to post-pandemic recovery of the healthcare workforce. The current report presents a feasible, theory-driven model for doing so, which was rated as highly satisfactory by participants.

False Positives and the Challenge of Testing the Alien Hypothesis.

The origin of life and the detection of alien life have historically been treated as separate scientific research problems. However, they are not strictly independent. Here, we discuss the need for a better integration of the sciences of life detection and origins of life. Framing these dual problems within the formalism of Bayesian hypothesis testing, we demonstrate via simple examples how high confidence in life detection claims require either (1) a strong prior hypothesis about the existence of life in a particular alien environment, or conversely, (2) signatures of life that are not susceptible to false positives. As a case study, we discuss the role of priors and hypothesis testing in recent results reporting potential detection of life in the venusian atmosphere and in the icy plumes of Enceladus. While many current leading biosignature candidates are subject to false positives because they are not definitive of life, our analyses demonstrate why it is necessary to shift focus to candidate signatures that are definitive. This indicates a necessity to develop methods that lack substantial false positives, by using observables for life that rely on prior hypotheses with strong theoretical and empirical support in identifying defining features of life. Abstract theories developed in pursuit of understanding universal features of life are more likely to be definitive and to apply to life-as-we-don't-know-it. We discuss Molecular Assembly theory as an example of such an observable which is applicable to life detection within the solar system. In the absence of alien examples these are best validated in origin of life experiments, substantiating the need for better integration between origins of life and biosignature science research communities. This leads to a conclusion that extraordinary claims in astrobiology (e.g., definitive detection of alien life) require extraordinary explanations, whereas the evidence itself could be quite ordinary.

Toward uncovering an operating system in plant organs.

Molecular motifs can explain information processing within single cells, while how assemblies of cells collectively achieve this remains less well understood. Plant fitness and survival depend upon robust and accurate decision-making in their decentralised multicellular organ systems. Mobile agents, including hormones, metabolites, and RNAs, have a central role in coordinating multicellular collective decision-making, yet mechanisms describing how cell-cell communication scales to organ-level transitions is poorly understood. Here, we explore how unified outputs may emerge in plant organs by distributed information processing across different scales and using different modalities. Mathematical and computational representations of these events are also explored toward understanding how these events take place and are leveraged to manipulate plant development in response to the environment.

Assembly theory explains and quantifies selection and evolution.

Scientists have grappled with reconciling biological evolution1,2 with the immutable laws of the Universe defined by physics. These laws underpin life's origin, evolution and the development of human culture and technology, yet they do not predict the emergence of these phenomena. Evolutionary theory explains why some things exist and others do not through the lens of selection. To comprehend how diverse, open-ended forms can emerge from physics without an inherent design blueprint, a new approach to understanding and quantifying selection is necessary3-5. We present assembly theory (AT) as a framework that does not alter the laws of physics, but redefines the concept of an 'object' on which these laws act. AT conceptualizes objects not as point particles, but as entities defined by their possible formation histories. This allows objects to show evidence of selection, within well-defined boundaries of individuals or selected units. We introduce a measure called assembly (A), capturing the degree of causation required to produce a given ensemble of objects. This approach enables us to incorporate novelty generation and selection into the physics of complex objects. It explains how these objects can be characterized through a forward dynamical process considering their assembly. By reimagining the concept of matter within assembly spaces, AT provides a powerful interface between physics and biology. It discloses a new aspect of physics emerging at the chemical scale, whereby history and causal contingency influence what exists.

On the non-uniqueness problem in integrated information theory.

Integrated Information Theory (IIT) 3.0 is among the leading theories of consciousness in contemporary neuroscience. The core of the theory relies on the calculation of a scalar mathematical measure of consciousness, Φ, which is inspired by the phenomenological axioms of the theory. Here, we show that despite its widespread application, Φ is not a well-defined mathematical concept in the sense that the value it specifies is non-unique. To demonstrate this, we introduce an algorithm that calculates all possible Φ values for a given system in strict accordance with the mathematical definition from the theory. We show that, to date, all published Φ values under consideration are selected arbitrarily from a multitude of equally valid alternatives. Crucially, both [Formula: see text] and [Formula: see text] are often predicted simultaneously, rendering any interpretation of these systems as conscious or not, non-decidable in the current formulation of IIT.

The Carbon Footprint and Cost of Virtual Residency Interviews.

Background: The shift from in-person to virtual residency interviews may impact greenhouse gas emissions (GHGE) and costs but the direction and amount of this change is not yet clear. Objective: To estimate GHGE and financial impacts of virtual interviews among applicants and programs. Methods: In 2020-2021 we sent a postinterview survey to 1429 applicants from 7 residency programs and 1 clinical psychology program at 1 institution. The survey collected origin of travel and transit type if in-person interviews had been held and excluded responses if the applicant would not have participated in an in-person interview, or if travel type or original city was missing. We used the International Civil Aviation Organization calculator to estimate flight-related GHGE in metric tons of carbon dioxide equivalent (MTCO2e) and Google Maps to estimate ground travel, with a standard CO2e per mile. Flight, hotel, and airport taxi costs were estimated using Expedia.com, Hotels.com, Uber, and Lyft. We aggregated these data and calculated median and interquartile ranges (IQRs) for applicant GHGE and cost savings, and assumed no cost or GHGE from virtual interviews. We used Wilcoxon signed rank sum tests to compare in-person 2019-2020 and virtual 2020-2021 GME program interview budgets. Results: The survey response rate was 565, or 40% of applicants; 543 remained after the exclusion criteria were applied. Reduction in applicant travel due to virtual interviews led to median estimated GHGE savings of 0.47 (IQR 0.30-0.61) MTCO2e and $490 (IQR $392-$544) per applicant, per interview. Programs savings ranged from $7,615 to $33,670 for the interview season. Conclusions: Virtual interviews in 8 GME programs were associated with lower estimated GHGE and costs, for applicants and programs, compared with in-person interviews.

Effectiveness of Virtual Residency Interviews: Interviewer Perspectives.

BACKGROUND AND OBJECTIVES: Virtual residency interviews were widely utilized during the COVID-19 pandemic. Little is known about the effectiveness, advantages, barriers, and acceptability of virtual interviews, casting uncertainty about how interviews should be conducted after the pandemic. We conducted a survey of interviewers to inform future decisions. METHODS: We developed and implemented an online postinterview survey of interviewers representing seven residency programs and two clinical psychology programs at one midsized academic medical center. We analyzed results using descriptive statistics. RESULTS: Of 312 interviewers, 136 completed the survey (44% response rate). A majority rated virtual interviews as very or extremely effective in creating a comfortable setting (79%), answering interviewee questions (86%), establishing a sense of connection (59%), evaluating interviewee strengths (64%), and communicating program culture (51%). About half felt virtual interviews were not effective at all or only slightly effective for evaluating interviewee strengths via informal interactions (51%). A similar portion agreed or strongly agreed that virtual tours (44%) and social environment (50%) information were adequate. The most frequent advantages were time efficiency (81%), reduced carbon footprint (61%) and cost savings (56%). Frequent disadvantages included technological issues (21%) and caregiving duties (18%). Most interviewers (91%) thought some form of virtual interviews should be incorporated postpandemic. CONCLUSIONS: Interviewers found virtual interviews to be effective in most aspects, and identified more advantages than barriers. The vast majority preferred incorporation of virtual interviews in the future. Virtual tours and social activities were areas for improvement.

Information Theory as an Experimental Tool for Integrating Disparate Biophysical Signaling Modules.

There is a growing appreciation in the fields of cell biology and developmental biology that cells collectively process information in time and space. While many powerful molecular tools exist to observe biophysical dynamics, biologists must find ways to quantitatively understand these phenomena at the systems level. Here, we present a guide for the application of well-established information theory metrics to biological datasets and explain these metrics using examples from cell, developmental and regenerative biology. We introduce a novel computational tool named after its intended purpose, calcium imaging, (CAIM) for simple, rigorous application of these metrics to time series datasets. Finally, we use CAIM to study calcium and cytoskeletal actin information flow patterns between Xenopus laevis embryonic animal cap stem cells. The tools that we present here should enable biologists to apply information theory to develop a systems-level understanding of information processing across a diverse array of experimental systems.

Formalising the Pathways to Life Using Assembly Spaces.

Assembly theory (referred to in prior works as pathway assembly) has been developed to explore the extrinsic information required to distinguish a given object from a random ensemble. In prior work, we explored the key concepts relating to deconstructing an object into its irreducible parts and then evaluating the minimum number of steps required to rebuild it, allowing for the reuse of constructed sub-objects. We have also explored the application of this approach to molecules, as molecular assembly, and how molecular assembly can be inferred experimentally and used for life detection. In this article, we formalise the core assembly concepts mathematically in terms of assembly spaces and related concepts and determine bounds on the assembly index. We explore examples of constructing assembly spaces for mathematical and physical objects and propose that objects with a high assembly index can be uniquely identified as those that must have been produced using directed biological or technological processes rather than purely random processes, thereby defining a new scale of aliveness. We think this approach is needed to help identify the new physical and chemical laws needed to understand what life is, by quantifying what life does.

Virtual Residency Interviews: Applicant Perceptions Regarding Virtual Interview Effectiveness, Advantages, and Barriers.

Background: Studies of the virtual interview format are needed to inform medical residency program leaders as they plan for future virtual interview seasons. Objective: In the current study, completed in 2021, we sought to assess applicant perspectives of virtual interview effectiveness, advantages, and barriers, including factors that might impact equity and inclusion. Methods: Interviewees applying to 7 residency programs and 2 clinical psychology programs at an academic medical center in the Pacific Northwest completed a post-interview survey. Results: A total of 565 of 1429 interviewees (40%) completed the survey. A vast majority (83%-96%) agreed virtual interviews were effective in each measured domain, except for learning institutional culture (352 of 565, 62%). Many also found information regarding social/living environments inadequate. Participants selected advantages to virtual interviews more frequently than disadvantages. Commonly selected advantages included cost savings, time efficiency, reduced burden of travel, and reduced carbon footprint. Disadvantages included time zone differences, access to an appropriate interview setting, and reliable access to internet. The majority of interviewees (84%, 456 of 542) desired to keep a component of virtual interviews in the future. There were no significant disparities in results based on gender, rural/suburban/urban location, race, or underrepresented minority status. Conclusions: Virtual interviews were perceived as effective, more advantageous than burdensome, and widely acceptable, with no disparities in these findings by included demographic characteristics.

Scaling laws in enzyme function reveal a new kind of biochemical universality.

All life on Earth is unified by its use of a shared set of component chemical compounds and reactions, providing a detailed model for universal biochemistry. However, this notion of universality is specific to known biochemistry and does not allow quantitative predictions about examples not yet observed. Here, we introduce a more generalizable concept of biochemical universality that is more akin to the kind of universality found in physics. Using annotated genomic datasets including an ensemble of 11,955 metagenomes, 1,282 archaea, 11,759 bacteria, and 200 eukaryotic taxa, we show how enzyme functions form universality classes with common scaling behavior in their relative abundances across the datasets. We verify that these scaling laws are not explained by the presence of compounds, reactions, and enzyme functions shared across known examples of life. We demonstrate how these scaling laws can be used as a tool for inferring properties of ancient life by comparing their predictions with a consensus model for the last universal common ancestor (LUCA). We also illustrate how network analyses shed light on the functional principles underlying the observed scaling behaviors. Together, our results establish the existence of a new kind of biochemical universality, independent of the details of life on Earth's component chemistry, with implications for guiding our search for missing biochemical diversity on Earth or for biochemistries that might deviate from the exact chemical makeup of life as we know it, such as at the origins of life, in alien environments, or in the design of synthetic life.

Naïve individuals promote collective exploration in homing pigeons.

Group-living animals that rely on stable foraging or migratory routes can develop behavioural traditions to pass route information down to inexperienced individuals. Striking a balance between exploitation of social information and exploration for better alternatives is essential to prevent the spread of maladaptive traditions. We investigated this balance during cumulative route development in the homing pigeon Columba livia. We quantified information transfer within pairs of birds in a transmission-chain experiment and determined how birds with different levels of experience contributed to the exploration-exploitation trade-off. Newly introduced naïve individuals were initially more likely to initiate exploration than experienced birds, but the pair soon settled into a pattern of alternating leadership with both birds contributing equally. Experimental pairs showed an oscillating pattern of exploration over generations that might facilitate the discovery of more efficient routes. Our results introduce a new perspective on the roles of leadership and information pooling in the context of collective learning.

Improving Timeliness of Insulin Administration by Using an Insulin Dose Calculator.

OBJECTIVES: Insulin is a high-risk medication, and its dosing depends on the individualized clinical and nutritional needs of each patient. Our hospital implemented an insulin dose calculator (IDC) imbedded in the electronic medical record with the goal of decreasing average wait times in inpatient insulin ordering and administration. In this study, we evaluated whether implementation of an IDC decreased the average wait time for insulin administration for hospitalized pediatric patients. METHODS: This pre- and postintervention cohort study measured wait times between point-of-care glucose testing and insulin administration. Patients admitted to the inpatient pediatric services who were treated with subcutaneous insulin during the study period were included. Additionally, nurses completed satisfaction surveys on the insulin administration process at our hospital pre- and post-IDC implementation. Descriptive statistics, χ2, Fisher's exact test, and Student t tests were used to compare groups. Statistical process control charts were used to analyze data trends. RESULTS: The preintervention cohort included 79 insulin doses for admitted pediatric patients. The postimplementation cohort included 128 insulin doses ordered via the IDC. Post-IDC implementation, the average wait time between point-of-care glucose testing and insulin administration decreased from 37 to 25 minutes (P < .05). The statistical process control chart revealed a 5-month run below the established mean after implementation of the IDC. Before IDC implementation, 15.6% of nurses expressed satisfaction in the insulin-dosing process compared with 69.2% postimplementation (P < .05). CONCLUSIONS: Implementation of an IDC reduced the average wait time in ordering and administration of rapid-acting insulin and improved nursing satisfaction with the process.

Be Responsible?

The bystander effect reveals that people are less likely to help a person in need when others are present. We examined the impact of priming the concept of responsibility on the bystander effect in a field study. Lone pedestrians (N = 259) were randomly assigned to a two (Bystanders: none and three nonresponsive bystanders) by two (Shirt: blank shirt and shirt with "Be Responsible" written on the front) design. A researcher dropped eight pens approximately 15 ft from a lone pedestrian, while wearing one of the two shirts in the presence/absence of bystanders (confederates). The bystander effect was found: Pedestrians helped pick up pens more frequently in the no bystanders condition (59.05% helped) compared to the nonresponsive bystanders condition (41.67% helped). The responsibility prime tended to boost helping rates, but it did not significantly increase helping rates either as a main effect or as part of an interaction term. The bystander effect was replicated in a field setting, but priming the concept of responsibility did not appear to reduce it.

Formalizing falsification for theories of consciousness across computational hierarchies.

The scientific study of consciousness is currently undergoing a critical transition in the form of a rapidly evolving scientific debate regarding whether or not currently proposed theories can be assessed for their scientific validity. At the forefront of this debate is Integrated Information Theory (IIT), widely regarded as the preeminent theory of consciousness because it quantified subjective experience in a scalar mathematical measure called Φ that is in principle measurable. Epistemological issues in the form of the "unfolding argument" have provided a concrete refutation of IIT by demonstrating how it permits functionally identical systems to have differences in their predicted consciousness. The implication is that IIT and any other proposed theory based on a physical system's causal structure may already be falsified even in the absence of experimental refutation. However, so far many of these arguments surrounding the epistemological foundations of falsification arguments, such as the unfolding argument, are too abstract to determine the full scope of their implications. Here, we make these abstract arguments concrete, by providing a simple example of functionally equivalent machines realizable with table-top electronics that take the form of isomorphic digital circuits with and without feedback. This allows us to explicitly demonstrate the different levels of abstraction at which a theory of consciousness can be assessed. Within this computational hierarchy, we show how IIT is simultaneously falsified at the finite-state automaton level and unfalsifiable at the combinatorial-state automaton level. We use this example to illustrate a more general set of falsification criteria for theories of consciousness: to avoid being already falsified, or conversely unfalsifiable, scientific theories of consciousness must be invariant with respect to changes that leave the inference procedure fixed at a particular level in a computational hierarchy.

Identifying molecules as biosignatures with assembly theory and mass spectrometry.

The search for alien life is hard because we do not know what signatures are unique to life. We show why complex molecules found in high abundance are universal biosignatures and demonstrate the first intrinsic experimentally tractable measure of molecular complexity, called the molecular assembly index (MA). To do this we calculate the complexity of several million molecules and validate that their complexity can be experimentally determined by mass spectrometry. This approach allows us to identify molecular biosignatures from a set of diverse samples from around the world, outer space, and the laboratory, demonstrating it is possible to build a life detection experiment based on MA that could be deployed to extraterrestrial locations, and used as a complexity scale to quantify constraints needed to direct prebiotically plausible processes in the laboratory. Such an approach is vital for finding life elsewhere in the universe or creating de-novo life in the lab.

Scarcity of scale-free topology is universal across biochemical networks.

Biochemical reactions underlie the functioning of all life. Like many examples of biology or technology, the complex set of interactions among molecules within cells and ecosystems poses a challenge for quantification within simple mathematical objects. A large body of research has indicated many real-world biological and technological systems, including biochemistry, can be described by power-law relationships between the numbers of nodes and edges, often described as "scale-free". Recently, new statistical analyses have revealed true scale-free networks are rare. We provide a first application of these methods to data sampled from across two distinct levels of biological organization: individuals and ecosystems. We analyze a large ensemble of biochemical networks including networks generated from data of 785 metagenomes and 1082 genomes (sampled from the three domains of life). The results confirm no more than a few biochemical networks are any more than super-weakly scale-free. Additionally, we test the distinguishability of individual and ecosystem-level biochemical networks and show there is no sharp transition in the structure of biochemical networks across these levels of organization moving from individuals to ecosystems. This result holds across different network projections. Our results indicate that while biochemical networks are not scale-free, they nonetheless exhibit common structure across different levels of organization, independent of the projection chosen, suggestive of shared organizing principles across all biochemical networks.

Informational architecture across non-living and living collectives.

Collective behavior is widely regarded as a hallmark property of living and intelligent systems. Yet, many examples are known of simple physical systems that are not alive, which nonetheless display collective behavior too, prompting simple physical models to often be adopted to explain living collective behaviors. To understand collective behavior as it occurs in living examples, it is important to determine whether or not there exist fundamental differences in how non-living and living systems act collectively, as well as the limits of the intuition that can be built from simpler, physical examples in explaining biological phenomenon. Here, we propose a framework for comparing non-living and living collectives as a continuum based on their information architecture: that is, how information is stored and processed across different degrees of freedom. We review diverse examples of collective phenomena, characterized from an information-theoretic perspective, and offer views on future directions for quantifying living collective behaviors based on their informational structure.

Seeding Biochemistry on Other Worlds: Enceladus as a Case Study.

The Solar System is becoming increasingly accessible to exploration by robotic missions to search for life. However, astrobiologists currently lack well-defined frameworks to quantitatively assess the chemical space accessible to life in these alien environments. Such frameworks will be critical for developing concrete predictions needed for future mission planning, both to determine the potential viability of life on other worlds and to anticipate the molecular biosignatures that life could produce. Here, we describe how uniting existing methods provides a framework to study the accessibility of biochemical space across diverse planetary environments. Our approach combines observational data from planetary missions with genomic data catalogued from across Earth and analyzed using computational methods from network theory. To demonstrate this, we use 307 biochemical networks generated from genomic data collected across Earth and "seed" these networks with molecules confirmed to be present on Saturn's moon Enceladus. By expanding through known biochemical reaction space starting from these seed compounds, we are able to determine which products of Earth's biochemistry are, in principle, reachable from compounds available in the environment on Enceladus, and how this varies across different examples of life from Earth (organisms, ecosystems, planetary-scale biochemistry). While we find that none of the 307 prokaryotes analyzed meet the threshold for viability, the reaction space covered by this process can provide a map of possible targets for detection of Earth-like life on Enceladus, as well as targets for synthetic biology approaches to seed life on Enceladus. In cases where biochemistry is not viable because key compounds are missing, we identify the environmental precursors required to make it viable, thus providing a set of compounds to prioritize for detection in future planetary exploration missions aimed at assessing the ability of Enceladus to sustain Earth-like life or directed panspermia.