Experimental Biological Protocols with Formal Semantics

Both experimental and computational biology is becoming increasingly automated. Laboratory experiments are now performed automatically on high-throughput machinery, while computational models are synthesized or inferred automatically from data. However, integration between automated tasks in the process of biological discovery is still lacking, largely due to incompatible or missing formal representations. While theories are expressed formally as computational models, existing languages for encoding and automating experimental protocols often lack formal semantics. This makes it challenging to extract novel understanding by identifying when theory and experimental evidence disagree due to errors in the models or the protocols used to validate them. To address this, we formalize the syntax of a core protocol language, which provides a unified description for the models of biochemical systems being experimented on, together with the discrete events representing the liquid-handling steps of biological protocols. We present both a deterministic and a stochastic semantics to this language, both defined in terms of hybrid processes. In particular, the stochastic semantics captures uncertainties in equipment tolerances, making it a suitable tool for both experimental and computational biologists. We illustrate how the proposed protocol language can be used for automated verification and synthesis of laboratory experiments on case studies from the fields of chemistry and molecular programming

Top-down social modulation of interpersonal observation-execution.

Cyclical upper limb movement can involuntarily deviate from its primary movement axis when the performer concurrently observes incongruent biological motion (i.e. interpersonal observation-execution). The current study examined the social modulation of such involuntary motor interference using a protocol that reflected everyday social interactions encountered in a naturalistic social setting. Eighteen participants executed cyclical horizontal arm movements during the observation of horizontal (congruent) or curvilinear (incongruent) biological motion. Both prior to, and during the interpersonal observation-execution task, participants also received a series of social words designed to prime a pro-social or anti-social attitude. The results showed greater orthogonal movement deviation, and thus interference, for the curvilinear compared to horizontal stimuli. Importantly, and opposite to most of the previous findings from work on automatic imitation and mimicry, there was a greater interference effect for the anti-social compared to pro-social prime condition. These findings demonstrate the importance of interpreting the context of social primes, and strongly support predictions of a comparison between the prime construct and the self-concept/-schema and the top-down response modulation of social incentives

Mimicry of Food Intake: The Dynamic Interplay between Eating Companions

Numerous studies have shown that people adjust their intake directly to that of their eating companions; they eat more when others eat more, and less when others inhibit intake. A potential explanation for this modeling effect is that both eating companions' food intake becomes synchronized through processes of behavioral mimicry. No study, however, has tested whether behavioral mimicry can partially account for this modeling effect. To capture behavioral mimicry, real-time observations of dyads of young females having an evening meal were conducted. It was assessed whether mimicry depended on the time of the interaction and on the person who took the bite. A total of 70 young female dyads took part in the study, from which the total number of bites (N = 3,888) was used as unit of analyses. For each dyad, the total number of bites and the exact time at which each person took a bite were coded. Behavioral mimicry was operationalized as a bite taken within a fixed 5-second interval after the other person had taken a bite, whereas non-mimicked bites were defined as bites taken outside the 5-second interval. It was found that both women mimicked each other's eating behavior. They were more likely to take a bite of their meal in congruence with their eating companion rather than eating at their own pace. This behavioral mimicry was found to be more prominent at the beginning than at the end of the interaction. This study suggests that behavioral mimicry may partially account for social modeling of food intake

Does the Precision of a Biological Clock Depend upon Its Period? Effects of the Duper and tau Mutations in Syrian Hamsters

Mutations which alter the feedback loops that generate circadian rhythms may provide insight into their insensitivity to perturbation robustness) and their consistency of period (precision). I examined relationships between endogenous period, activity and rest (τDD, α and ρ) in Syrian hamsters using two different mutations, duper and tau, both of which speed up the circadian clock. I generated 8 strains of hamsters that are homozygous or heterozygous for the tau, duper, and wild type alleles in all combinations. The endogenous period of activity onsets among these strains ranged from 17.94+0.04 to 24.13±0.04 h. Contrary to predictions, the variability of period was unrelated to its absolute value: all strains showed similar variability of τDD when activity onsets and acrophase were used as phase markers. The τDD of activity offsets was more variable than onsets but also differed little between genotypes. Cycle variation and precision were not correlated with τDD within any strain, and only weakly correlated when all strains are considered together. Only in animals homozygous for both mutations (super duper hamsters) were cycle variation and precision reduced. Rhythm amplitude differed between strains and was positively correlated with τDD and precision. All genotypes showed negative correlations between α and ρ. This confirms the expectation that deviations in the duration of subjective day and night should offset one another in order to conserve circadian period, even though homeostatic maintenance of energy reserves predicts that longer intervals of activity or rest would be followed by longer durations of rest or activity. Females consistently showed greater variability of the period of activity onset and acrophase, and of α, but variability of the period of offset differed between sexes only in super duper hamsters. Despite the differences between genotypes in τDD, ρ was consistently more strongly correlated with the preceding than the succeeding α

Low Fidelity Imitation of Atypical Biological Kinematics in Autism Spectrum Disorders Is Modulated by Self-Generated Selective Attention.

We examined whether adults with autism had difficulty imitating atypical biological kinematics. To reduce the impact that higher-order processes have on imitation we used a non-human agent model to control social attention, and removed end-state target goals in half of the trials to minimise goal-directed attention. Findings showed that only neurotypical adults imitated atypical biological kinematics. Adults with autism did, however, become significantly more accurate at imitating movement time. This confirmed they engaged in the task, and that sensorimotor adaptation was self-regulated. The attentional bias to movement time suggests the attenuation in imitating kinematics might be a compensatory strategy due to deficits in lower-level visuomotor processes associated with self-other mapping, or selective attention modulated the processes that represent biological kinematics

A High-Level Language for Rule-Based Modelling

Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages

Patterns of patient-reported symptoms and association with sociodemographic and systemic sclerosis disease characteristics: a scleroderma Patient-centered Intervention Network (SPIN) Cohort cross-sectional study

Background: Systemic sclerosis is a heterogenous disease in which little is known about patterns of patient-reported symptom clusters. We aimed to identify classes of individuals with similar anxiety, depression, fatigue, sleep disturbance, and pain symptoms and to evaluate associated sociodemographic and disease-related characteristics. Methods: This multi-centre cross-sectional study used baseline data from Scleroderma Patient-centered Intervention Network Cohort participants enrolled from 2014 to 2020. Eligible participants completed the PROMIS-29 v2.0 measure. Latent profile analysis was used to identify homogeneous classes of participants based on patterns of anxiety, depression, fatigue, sleep disturbance, and pain scores. Sociodemographic and disease-related characteristics were compared across classes. Findings: Among 2212 participants, we identified five classes, including four classes with “Low” (565 participants, 26%), “Normal” (651 participants, 29%), “High” (569 participants, 26%), or “Very High” (193 participants, 9%) symptom levels across all symptoms. Participants in a fifth class, “High Fatigue/Sleep/Pain and Low Anxiety/Depression” (234 participants, 11%) had similar levels of fatigue, sleep disturbance, and pain as in the “High” class but low anxiety and depression symptoms. There were significant and substantive trends in sociodemographic characteristics (age, education, race or ethnicity, marital or partner status) and increasing disease severity (diffuse disease, tendon friction rubs, joint contractures, gastrointestinal symptoms) across severity-based classes. Disease severity and sociodemographic characteristics of “High Fatigue/Sleep/Pain and Low Anxiety/Depression” class participants were similar to the “High” severity class. Interpretation: Most people with systemic sclerosis can be classified by levels of patient-reported symptoms, which are consistent across symptoms and highly associated with sociodemographic and disease-related variables, except for one group which reports low mental health symptoms despite high levels of other symptoms and substantial disease burden. Studies are needed to better understand resilience in systemic sclerosis and to identify and facilitate implementation of cognitive and behavioural strategies to improve coping and overall quality of life. Funding: National Institute of Nursing Research (F31NR019007), Canadian Institutes of Health Research, Arthritis Society Canada, the Lady Davis Institute for Medical Research, the Jewish General Hospital Foundation, McGill University, Scleroderma Society of Ontario, Scleroderma Canada, Sclérodermie Québec, Scleroderma Manitoba, Scleroderma Atlantic, Scleroderma Association of BC, Scleroderma SASK, Scleroderma Australia, Scleroderma New South Wales, Scleroderma Victoria, and Scleroderma Queensland

Syntax-Guided Optimal Synthesis for Chemical Reaction Networks

We study the problem of optimal syntax-guided synthesis of stochastic Chemical Reaction Networks (CRNs) that plays a fundamental role in design automation of molecular devices and in the construction of predictive biochemical models. We propose a sketching language for CRNs that concisely captures syntactic constraints on the network topology and allows its under-specification. Given a sketch, a correctness specification, and a cost function defined over the CRN syntax, our goal is to find a CRN that simultaneously meets the constraints, satisfies the specification and minimizes the cost function. To ensure computational feasibility of the synthesis process, we employ the Linear Noise Approximation allowing us to encode the synthesis problem as a satisfiability modulo theories problem over a set of parametric Ordinary Differential Equations (ODEs). We design and implement a novel algorithm for the optimal synthesis of CRNs that employs almost complete refutation procedure for SMT over reals and ODEs, and exploits a meta-sketching abstraction controlling the search strategy. Through relevant case studies we demonstrate that our approach significantly improves the capability of existing methods for synthesis of biochemical systems and paves the way towards their automated and provably-correct design

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability