Genetic Algorithms and the Satisfiability of Large-Scale Boolean Expressions.

The two new genetic methods overpopulation and bitwise expected value are introduced. In overpopulation a temporary population of size Mn (M $\u3e$ 1) is created using genetic operators and the n children with the highest estimated fitness values are selected as the next generation. The rest are discarded. Bitwise expected value (bev) is the fitness estimation function used. Overpopulation and bitwise expected value are applied to the NP-complete problem 3SAT (a special form of Satisfiability in which the boolean expression consists of the conjunction of an arbitrary number of clauses where each clause consists of the disjunction of 3 boolean variables) with excellent empirical results when compared to the performance of the standard genetic algorithm. Overpopulation increases the cost of producing each generation due to the overhead required to maintain the larger temporary population but results in many fewer generations to solution. Using bitwise expected value as a fitness estimator causes the algorithm to take slightly more generations to solution but is much faster to calculate than the fitness function, leading to a decrease in wall-clock time to solution. Theoretical justification for the success of overpopulation is seen as a result of the generalization of the schema growth equation. Bitwise expected value is viewed as an analogy to the Building Block Hypothesis. Empirical evidence of high correlation between bev and the fitness function is presented. We also introduce the target problem concept, in which a difficult problem is transformed into a well-known problem for which a good genetic method of solution is known. As an example of the target problem concept a transformation from the Traveling Salesman Problem to Satisfiability is demonstrated. Overpopulation and bitwise expected value are applied to the resulting boolean expression, with good results. An interesting convergence property is observed

Large Language Models to Identify Social Determinants of Health in Electronic Health Records

Social determinants of health (SDoH) have an important impact on patient outcomes but are incompletely collected from the electronic health records (EHR). This study researched the ability of large language models to extract SDoH from free text in EHRs, where they are most commonly documented, and explored the role of synthetic clinical text for improving the extraction of these scarcely documented, yet extremely valuable, clinical data. 800 patient notes were annotated for SDoH categories, and several transformer-based models were evaluated. The study also experimented with synthetic data generation and assessed for algorithmic bias. Our best-performing models were fine-tuned Flan-T5 XL (macro-F1 0.71) for any SDoH, and Flan-T5 XXL (macro-F1 0.70). The benefit of augmenting fine-tuning with synthetic data varied across model architecture and size, with smaller Flan-T5 models (base and large) showing the greatest improvements in performance (delta F1 +0.12 to +0.23). Model performance was similar on the in-hospital system dataset but worse on the MIMIC-III dataset. Our best-performing fine-tuned models outperformed zero- and few-shot performance of ChatGPT-family models for both tasks. These fine-tuned models were less likely than ChatGPT to change their prediction when race/ethnicity and gender descriptors were added to the text, suggesting less algorithmic bias (p<0.05). At the patient-level, our models identified 93.8% of patients with adverse SDoH, while ICD-10 codes captured 2.0%. Our method can effectively extracted SDoH information from clinic notes, performing better compare to GPT zero- and few-shot settings. These models could enhance real-world evidence on SDoH and aid in identifying patients needing social support.Comment: 38 pages, 5 figures, 5 tables in main, submitted for revie

Familial Interstitial Lung Disease in Two Young Korean Sisters

Most of the interstitial lung diseases are rare, chronic, progressive and fatal disorders, especially in familial form. The etiology of the majority of interstitial lung disease is still unknown. Host susceptibility, genetic and environmental factors may influence clinical expression of each disease. With familial interstitial lung diseases, mutations of surfactant protein B and surfactant protein C or other additional genetic mechanisms (e.g. mutation of the gene for ATP-binding cassette transporter A3) could be associated. We found a 21 month-old girl with respiratory symptoms, abnormal radiographic findings and abnormal open lung biopsy findings compatible with nonspecific interstitial pneumonitis that is similar to those of her older sister died from this disease. We performed genetic studies of the patient and her parents, but we could not find any mutation in our case. High-dose intravenous methylprednisolone and oral hydroxychloroquine were administered and she is still alive without progression during 21 months of follow-up

Lateralization in the Invertebrate Brain: Left-Right Asymmetry of Olfaction in Bumble Bee, Bombus terrestris

Brain and behavioural lateralization at the population level has been recently hypothesized to have evolved under social selective pressures as a strategy to optimize coordination among asymmetrical individuals. Evidence for this hypothesis have been collected in Hymenoptera: eusocial honey bees showed olfactory lateralization at the population level, whereas solitary mason bees only showed individual-level olfactory lateralization. Here we investigated lateralization of odour detection and learning in the bumble bee, Bombus terrestris L., an annual eusocial species of Hymenoptera. By training bumble bees on the proboscis extension reflex paradigm with only one antenna in use, we provided the very first evidence of asymmetrical performance favouring the right antenna in responding to learned odours in this species. Electroantennographic responses did not reveal significant antennal asymmetries in odour detection, whereas morphological counting of olfactory sensilla showed a predominance in the number of olfactory sensilla trichodea type A in the right antenna. The occurrence of a population level asymmetry in olfactory learning of bumble bee provides new information on the relationship between social behaviour and the evolution of population-level asymmetries in animals

A call for new approaches to quantifying biases in observations of sea-surface temperature

Global surface-temperature changes are a fundamental expression of climate change. Recent, much-debated, variations in the observed rate of surface-temperature change have highlighted the importance of uncertainty in adjustments applied to sea-surface temperature (SST) measurements. These adjustments are applied to compensate for systematic biases and changes in observing protocol. Better quantification of the adjustments and their uncertainties would increase confidence in estimated surface-temperature change and provide higher- quality gridded SST fields for use in many applications. Bias adjustments have been based either on physical models of the observing processes or on the assumption of an unchanging relationship between SST and a reference data set such as night marine air temperature. These approaches produce similar estimates of SST bias on the largest space and timescales, but regional differences can exceed the estimated uncertainty. We describe challenges to improving our understanding of SST biases. Overcoming these will require clarification of past observational methods, improved modeling of biases associated with each observing method, and the development of statistical bias estimates that are less sensitive to the absence of metadata regarding the observing method. New approaches are required that embed bias models, specific to each type of observation, within a robust statistical framework. Mobile platforms and rapid changes in observation type require biases to be assessed for individual historic and present-day platforms (i.e., ships or buoys) or groups of platforms. Lack of observational metadata and of high-quality observations for validation and bias model development are likely to remain major challenges

Sirt1 Regulates Insulin Secretion by Repressing UCP2 in Pancreatic β Cells

Sir2 and insulin/IGF-1 are the major pathways that impinge upon aging in lower organisms. In Caenorhabditis elegans a possible genetic link between Sir2 and the insulin/IGF-1 pathway has been reported. Here we investigate such a link in mammals. We show that Sirt1 positively regulates insulin secretion in pancreatic β cells. Sirt1 represses the uncoupling protein (UCP) gene UCP2 by binding directly to the UCP2 promoter. In β cell lines in which Sirt1 is reduced by SiRNA, UCP2 levels are elevated and insulin secretion is blunted. The up-regulation of UCP2 is associated with a failure of cells to increase ATP levels after glucose stimulation. Knockdown of UCP2 restores the ability to secrete insulin in cells with reduced Sirt1, showing that UCP2 causes the defect in glucose-stimulated insulin secretion. Food deprivation induces UCP2 in mouse pancreas, which may occur via a reduction in NAD (a derivative of niacin) levels in the pancreas and down-regulation of Sirt1. Sirt1 knockout mice display constitutively high UCP2 expression. Our findings show that Sirt1 regulates UCP2 in β cells to affect insulin secretion

The Current State of Cephalopod Science and Perspectives on the Most Critical Challenges Ahead From Three Early-Career Researchers

International audienceHere, three researchers who have recently embarked on careers in cephalopod biology discuss the current state of the field and offer their hopes for the future. Seven major topics are explored genetics, aquaculture, climate change, welfare, behavior, cognition, and neurobiology. Recent developments in each of these fields are reviewed and the potential of emerging technologies to address specific gaps in knowledge about cephalopods are discussed. Throughout, the authors highlight specific challenges that merit particular focus in the near-term. This review and prospectus is also intended to suggest some concrete near-term goals to cephalopod researchers and inspire those working outside the field to consider the revelatory potential of these remarkable creatures