Novel genetic variant in hereditary spastic paraparesis.

A man in his 30s was referred to neurology with right-sided paraesthesia, tremors, chest pain and lower urinary tract and erectile dysfunction. He had a medical history of left acetabular dysplasia, and subjective memory impairment, the latter being in the context of depression and chronic pain with opioid use. There was no notable family history. On examination, he had a spastic paraparesis. Imaging revealed atrophy of the thoracic spine. Lumbar puncture demonstrated a raised protein but other constituents were normal, including no presence of oligoclonal bands. Genetic testing revealed a novel heterozygous likely pathogenic SPAST variant c. 1643A>T p.(Asp548Val), confirming the diagnosis of hereditary spastic paraparesis. Symptomatic treatment with physiotherapy and antispasmodic therapy was initiated. This is the first study reporting a patient with this SPAST variant. Ensembl variant effect predictor was used, with the application of computational variant prediction tools providing support that the variant we have identified is likely deleterious and damaging. Our variant CADD score was high, indicating that our identified variant was a highly deleterious substitution.

Question-answering system extracts information on injection drug use from clinical notes.

BACKGROUND: Injection drug use (IDU) can increase mortality and morbidity. Therefore, identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients' electronic health records (EHR) is difficult because there is no other structured data available, such as International Classification of Disease (ICD) codes, and IDU is most often documented in unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. METHODS: To address this gap in clinical information, we design a question-answering (QA) framework to extract information on IDU from clinical notes for use in clinical operations. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We use 2323 clinical notes of 1145 patients curated from the US Department of Veterans Affairs (VA) Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model's ability to extract IDU-related information from temporally out-of-distribution data. RESULTS: Here, we show that for a strict match between gold-standard and predicted answers, the QA model achieves a 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains a 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. CONCLUSIONS: Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care.

There are many health risks associated with injection drug use (IDU). Identifying people who inject drugs early can reduce the likelihood of these issues arising. However, extracting information about any possible IDU from a person's electronic health records can be difficult because the information is often in text-based general clinical notes rather than provided in a particular section of the record or as numerical data. Manually extracting information from these notes is time-consuming and inefficient. We used a computational method to train computer software to be able to extract IDU details. Potentially, this approach could be used by healthcare providers to more efficiently and accurately identify people who inject drugs, and therefore provide better advice and medical care.

A snapshot of 100 years of discovery.

With a century of literature behind Journal of Experimental Biology (JEB) in 2023, I look at some of the extraordinary papers contained within its archive. From publishing Nobel Prize-inspiring discoveries to founding fields and solving long-standing mysteries, the journal has been at the hub of experimental biology for 10 decades, leading the way and shining a light on the physiology of many remarkable animal species. In this Perspective, I highlight some of the key players in the field, summarise their seminal works and consider their long-term impact as JEB embarks on its next 100 years.

Journey through the history of Journal of Experimental Biology: a timeline.

In the cut-throat industry of academic publishing, some journals barely survive a decade, let alone a century, but in October 2023, Journal of Experimental Biology is celebrating 100 years at the forefront of comparative physiology, neuroethology and biomechanics. In this Commentary article and the accompanying poster, I explore the journal's history from its inception, through the guidance of nine Editors-in-Chief, to achieving its aims of championing the comparative approach, disseminating and promoting high-quality research and supporting our community of researchers. I discuss technological developments in publishing and classic articles that have cemented the journal in its position at the forefront of comparative physiology.

Behavioral and Neural Signatures of Visual Imagery Vividness Extremes: Aphantasia versus Hyperphantasia.

Although Galton recognized in the 1880s that some individuals lack visual imagery, this phenomenon was mostly neglected over the following century. We recently coined the terms "aphantasia" and "hyperphantasia" to describe visual imagery vividness extremes, unlocking a sustained surge of public interest. Aphantasia is associated with subjective impairment of face recognition and autobiographical memory. Here we report the first systematic, wide-ranging neuropsychological and brain imaging study of people with aphantasia (n = 24), hyperphantasia (n = 25), and midrange imagery vividness (n = 20). Despite equivalent performance on standard memory tests, marked group differences were measured in autobiographical memory and imagination, participants with hyperphantasia outperforming controls who outperformed participants with aphantasia. Face recognition difficulties and autistic spectrum traits were reported more commonly in aphantasia. The Revised NEO Personality Inventory highlighted reduced extraversion in the aphantasia group and increased openness in the hyperphantasia group. Resting state fMRI revealed stronger connectivity between prefrontal cortices and the visual network among hyperphantasic than aphantasic participants. In an active fMRI paradigm, there was greater anterior parietal activation among hyperphantasic and control than aphantasic participants when comparing visualization of famous faces and places with perception. These behavioral and neural signatures of visual imagery vividness extremes validate and illuminate this significant but neglected dimension of individual difference.

Standardized Architecture for a Mega-Biobank Phenomic Library: The Million Veteran Program (MVP).

Electronic health records (EHRs) provide a wealth of data for phenotype development in population health studies, and researchers invest considerable time to curate data elements and validate disease definitions. The ability to reproduce well-defined phenotypes increases data quality, comparability of results and expedites research. In this paper, we present a standardized approach to organize and capture phenotype definitions, resulting in the creation of an open, online repository of phenotypes. This resource captures phenotype development, provenance and process from the Million Veteran Program, a national mega-biobank embedded in the Veterans Health Administration (VHA). To ensure that the repository is searchable, extendable, and sustainable, it is necessary to develop both a proper digital catalog architecture and underlying metadata infrastructure to enable effective management of the data fields required to define each phenotype. Our methods provide a resource for VHA investigators and a roadmap for researchers interested in standardizing their phenotype definitions to increase portability.

Progressive multifocal leukoencephalopathy following five lines of therapy and three autologous bone marrow transplants for multiple myeloma.

A 59-year-old man, with a background of multiply relapsed myeloma, presented with a 3-week history of confusion, short-term memory impairment and behavioural changes. CT head showed bilateral white matter changes and numerous, large lytic lesions of the skull vault. MRI brain revealed multiple areas of hyperintensity on T2-weighted sequences which did not enhance (many of which showed diffusion restriction) unexpectedly bringing progressive multifocal leukoencephalopathy (PML) into the differential. Initial cerebrospinal fluid studies were largely unremarkable, aside from a mildly elevated protein; cultures were negative. PCR for the John Cunningham (JC) virus was positive. Considering the patient's medical history and rapidily progressive symptoms, a palliative approach was adopted, with the patient dying 14 days later. We present this case as an example of PML in a patient with multiple myeloma, highlighting the need to consider this diagnosis in an enlarging population of heavily treated, severely immunocompromised, patients.