The digital Balint: using AI in reflective practice.

Reflective practice is fundamental to postgraduate general practitioner (GP) training and ongoing professional development. However, real-world challenges like time constraints and professional isolation often limit meaningful engagement with this critical skill. This article proposes that large language models (LLMs), sophisticated artificial intelligence systems, may have potential for enhancing reflective practice. We present three case studies, in which we explore the ability of LLMs to generate thought-provoking questions, which could prompt GPs to consider new angles, address underlying factors, and bridge the gap between theory and practice. Our findings suggest that LLMs could help reframe experiences and foster deeper self reflection, particularly for isolated practitioners. While ethical concerns regarding privacy, over reliance, and potential biases exist, we consider the possibility of responsibly integrating LLMs into reflective practice. For trainees, AI-generated questions might complement personal reflection under guidance. For GPs working in isolation, LLMs present an opportunity to enhance reflective practice, challenging us to consider a place for this technological innovation without diminishing the human aspects essential to medical practice.

Efficient and flexible representation of higher-dimensional cognitive variables with grid cells.

We shed light on the potential of entorhinal grid cells to efficiently encode variables of dimension greater than two, while remaining faithful to empirical data on their low-dimensional structure. Our model constructs representations of high-dimensional inputs through a combination of low-dimensional random projections and "classical" low-dimensional hexagonal grid cell responses. Without reconfiguration of the recurrent circuit, the same system can flexibly encode multiple variables of different dimensions while maximizing the coding range (per dimension) by automatically trading-off dimension with an exponentially large coding range. It achieves high efficiency and flexibility by combining two powerful concepts, modularity and mixed selectivity, in what we call "mixed modular coding". In contrast to previously proposed schemes, the model does not require the formation of higher-dimensional grid responses, a cell-inefficient and rigid mechanism. The firing fields observed in flying bats or climbing rats can be generated by neurons that combine activity from multiple grid modules, each representing higher-dimensional spaces according to our model. The idea expands our understanding of grid cells, suggesting that they could implement a general circuit that generates on-demand coding and memory states for variables in high-dimensional vector spaces.

Locations in the Neocortex: A Theory of Sensorimotor Object Recognition Using Cortical Grid Cells.

The neocortex is capable of anticipating the sensory results of movement but the neural mechanisms are poorly understood. In the entorhinal cortex, grid cells represent the location of an animal in its environment, and this location is updated through movement and path integration. In this paper, we propose that sensory neocortex incorporates movement using grid cell-like neurons that represent the location of sensors on an object. We describe a two-layer neural network model that uses cortical grid cells and path integration to robustly learn and recognize objects through movement and predict sensory stimuli after movement. A layer of cells consisting of several grid cell-like modules represents a location in the reference frame of a specific object. Another layer of cells which processes sensory input receives this location input as context and uses it to encode the sensory input in the object's reference frame. Sensory input causes the network to invoke previously learned locations that are consistent with the input, and motor input causes the network to update those locations. Simulations show that the model can learn hundreds of objects even when object features alone are insufficient for disambiguation. We discuss the relationship of the model to cortical circuitry and suggest that the reciprocal connections between layers 4 and 6 fit the requirements of the model. We propose that the subgranular layers of cortical columns employ grid cell-like mechanisms to represent object specific locations that are updated through movement.

Targeted Single Primer Enrichment Sequencing with Single End Duplex-UMI.

For specific detection of somatic variants at very low levels, artifacts from the NGS workflow have to be eliminated. Various approaches using unique molecular identifiers (UMI) to analytically remove NGS artifacts have been described. Among them, Duplex-seq was shown to be highly effective, by leveraging the sequence complementarity of two DNA strands. However, all of the published Duplex-seq implementations so far required pair-end sequencing and in the case of combining duplex sequencing with target enrichment, lengthy hybridization enrichment was required. We developed a simple protocol, which enabled the retrieval of duplex UMI in multiplex PCR based enrichment and sequencing. Using this protocol and reference materials, we demonstrated the accurate detection of known SNVs at 0.1-0.2% allele fractions, aided by duplex UMI. We also observed that low level base substitution artifacts could be introduced when preparing in vitro DNA reference materials, which could limit their utility as a benchmarking tool for variant detection at very low levels. Our new targeted sequencing method offers the benefit of using duplex UMI to remove NGS artifacts in a much more simplified workflow than existing targeted duplex sequencing methods.

A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex.

How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework.

Reducing amplification artifacts in high multiplex amplicon sequencing by using molecular barcodes.

BACKGROUND: PCR amplicon sequencing has been widely used as a targeted approach for both DNA and RNA sequence analysis. High multiplex PCR has further enabled the enrichment of hundreds of amplicons in one simple reaction. At the same time, the performance of PCR amplicon sequencing can be negatively affected by issues such as high duplicate reads, polymerase artifacts and PCR amplification bias. Recently researchers have made some good progress in addressing these shortcomings by incorporating molecular barcodes into PCR primer design. So far, most work has been demonstrated using one to a few pairs of primers, which limits the size of the region one can analyze. RESULTS: We developed a simple protocol, which enables the use of molecular barcodes in high multiplex PCR with hundreds of amplicons. Using this protocol and reference materials, we demonstrated the applications in accurate variant calling at very low fraction over a large region and in targeted RNA quantification. We also evaluated the protocol's utility in profiling FFPE samples. CONCLUSIONS: We demonstrated the successful implementation of molecular barcodes in high multiplex PCR, with multiplex scale many times higher than earlier work. We showed that the new protocol combines the benefits of both high multiplex PCR and molecular barcodes, i.e. the analysis of a very large region, low DNA input requirement, very good reproducibility and the ability to detect as low as 1% mutations with minimal false positives (FP).

Eukaryotic polyribosome profile analysis.

Protein synthesis is a complex cellular process that is regulated at many levels. For example, global translation can be inhibited at the initiation phase or the elongation phase by a variety of cellular stresses such as amino acid starvation or growth factor withdrawal. Alternatively, translation of individual mRNAs can be regulated by mRNA localization or the presence of cognate microRNAs. Studies of protein synthesis frequently utilize polyribosome analysis to shed light on the mechanisms of translation regulation or defects in protein synthesis. In this assay, mRNA/ribosome complexes are isolated from eukaryotic cells. A sucrose density gradient separates mRNAs bound to multiple ribosomes known as polyribosomes from mRNAs bound to a single ribosome or monosome. Fractionation of the gradients allows isolation and quantification of the different ribosomal populations and their associated mRNAs or proteins. Differences in the ratio of polyribosomes to monosomes under defined conditions can be indicative of defects in either translation initiation or elongation/termination. Examination of the mRNAs present in the polyribosome fractions can reveal whether the cohort of individual mRNAs being translated changes with experimental conditions. In addition, ribosome assembly can be monitored by analysis of the small and large ribosomal subunit peaks which are also separated by the gradient. In this video, we present a method for the preparation of crude ribosomal extracts from yeast cells, separation of the extract by sucrose gradient and interpretation of the results. This procedure is readily adaptable to mammalian cells.

Coordination of eukaryotic translation elongation factor 1A (eEF1A) function in actin organization and translation elongation by the guanine nucleotide exchange factor eEF1Balpha.

Eukaryotic translation elongation factor 1A (eEF1A) both shuttles aminoacyl-tRNA (aa-tRNA) to the ribosome and binds and bundles actin. A single domain of eEF1A is proposed to bind actin, aa-tRNA and the guanine nucleotide exchange factor eEF1Balpha. We show that eEF1Balpha has the ability to disrupt eEF1A-induced actin organization. Mutational analysis of eEF1Balpha F163, which binds in this domain, demonstrates effects on growth, eEF1A binding, nucleotide exchange activity, and cell morphology. These phenotypes can be partially restored by an intragenic W130A mutation. Furthermore, the combination of F163A with the lethal K205A mutation restores viability by drastically reducing eEF1Balpha affinity for eEF1A. This also results in a consistent increase in actin bundling and partially corrected morphology. The consequences of the overlapping functions in this eEF1A domain and its unique differences from the bacterial homologs provide a novel function for eEF1Balpha to balance the dual roles in actin bundling and protein synthesis.