Differential loss of spinal interneurons in a mouse model of ALS

Amyotrophic lateral sclerosis (ALS) leads to a loss of specific motor neuron populations in the spinal cord and cortex. Emerging evidence suggests that interneurons may also be affected, but a detailed characterization of interneuron loss and its potential impacts on motor neuron loss and disease progression is lacking. To examine this issue, the fate of V1 inhibitory neurons during ALS was assessed in the ventral spinal cord using the SODG93A mouse model. The V1 population makes up ∼30% of all ventral inhibitory neurons, ∼50% of direct inhibitory synaptic contacts onto motor neuron cell bodies, and is thought to play a key role in modulating motor output, in part through recurrent and reciprocal inhibitory circuits. We find that approximately half of V1 inhibitory neurons are lost in SODG93A mice at late disease stages, but that this loss is delayed relative to the loss of motor neurons and V2a excitatory neurons. We further identify V1 subpopulations based on transcription factor expression that are differentially susceptible to degeneration in SODG93A mice. At an early disease stage, we show that V1 synaptic contacts with motor neuron cell bodies increase, suggesting an upregulation of inhibition before V1 neurons are lost in substantial numbers. These data support a model in which progressive changes in V1 synaptic contacts early in disease, and in select V1 subpopulations at later stages, represent a compensatory upregulation and then deleterious breakdown of specific interneuron circuits within the spinal cord

Introduction to "Special Issue on Social Reproduction Feminism"

The 2011 Historical Materialism Conference in London saw the launch of a Marxist-Feminist set of panels. This issue is inspired by the success of those panels, and the remarkably sustained interest in reviving and moving beyond older debates and discussions. The special issue’s focus, Social-Reproduction Feminism, reflects and contextualises the ongoing work and engagement with that thematic that has threaded through the conferences in the 2010s. This Introduction provides a summary overview of the Social-Reproduction Feminism framework, situating it within Marxist-Feminist thinking and politics more generally, and calls on readers to consider its promise and potential as an historical-materialist approach to understanding capitalist social relations in terms of an integrated totality

Transformer-based biomarker prediction from colorectal cancer histology:A large-scale multicentric study

Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem