LifeArc

Geriatric syndromes (GS) are complex conditions that affect older adults and often require multidisciplinary assessment. Natural language processing (NLP) has emerged as a promising tool for extracting relevant clinical information from unstructured text in electronic health records (EHRs). However, the application of NLP in detecting and monitoring GS remains an evolving area of research. This systematic review explores the role of NLP in the identification and analysis of GS, examining its applications, methodologies, and effectiveness. Furthermore, this review discusses the existing challenges, limitations, and future directions to advance NLP applications in the GS research. We conducted a systematic literature search across ten databases to identify studies that applied NLP to GS detection. Articles were screened using predefined inclusion and exclusion criteria, and relevant studies were evaluated for quality using PROBAST. Data were extracted on study characteristics, datasets, annotation processes, NLP approaches, performance metrics, population demographics, and clinical applications. A PRISMA flow diagram was used to illustrate the study selection process. A total of 65 studies were included, where the majority of the studies used traditional rule-based and machine learning approaches. Publicly available datasets were scarce, and most studies used their private dataset, leading to significant variability in data sources and formats. Annotation methodologies differed across studies, with minimal shared guidelines or standards, making direct comparisons challenging. Performance metrics varied across syndromes, with F1-score, precision, and recall as the most commonly reported. Key challenges included the lack of dataset uniformity, differences in annotation practices, and the absence of external validation. NLP has shown potential in GS analysis, particularly for the detection of syndromes and epidemiological research. However, the majority of studies only focused on one syndrome, and variability in dataset availability, annotation processes, and model performance present challenges to broader implementation. Future research should focus on improving the comprehensiveness of GS identification, dataset standardisation, enhancing model generalisability, and integrating NLP approaches into clinical workflows.

<h3></h3> In 2024, Antenatal Results and Choices conducted a survey on experiences of care for termination for fetal anomaly (TOPFA) within the last 4 years. Our survey had 399 completed responses from across all regions of the UK. The survey was designed to get a thorough overview of experiences of TOPFA care in the UK. Survey questions covered parents’ experiences of diagnosis, choice of and views on method of termination, waiting times for termination, and care and support during and after termination. Overall, the majority of respondents said their care was excellent or very good. Among the aspects of care parents valued were compassionate care from healthcare professionals (HCPs); adequate pain relief; offer of memory-making; privacy; continuity of care and point of contact with HCPs; clear information; short waits for appointments; and time to ask questions and make decisions. Support after termination was rated less highly and parents wanted more proactive provision of bereavement and psychological support. Our findings highlight the need for personalised patient-centred care which gives women sufficient information and supports them to make the right decisions for themselves in difficult circumstances. Another finding is the importance of ongoing support after TOPFA.

Abstract Two-pore domain potassium (K2P) channels are novel analgesic drug targets with existing in vitro and in vivo validation, however genetic associations in large scale populations have not been widely reported. By examining two comprehensive genetic databases (UK Biobank &amp; FinnGen) and 136 pain-related traits, we highlight that multiple pain-associated signals are present within 500 kb of K2P gene transcripts, with particularly strong evidence for KCNK5 (TASK-2) and headache-related traits. This data benchmarks remarkably well against gene targets already considered to be well validated pain targets (voltage-gated sodium and transient receptor potential channels) and is enhanced when examining populations regularly consuming analgesics who also report pain. This data supports a rationale for developing therapeutic strategies to modulate K2P function in patient populations experiencing pain.

Drug discovery requires understanding disease mechanisms, making the integration of multi-modal data essential. These data types, including omics, disease-associated, and pathway information, must be combined to uncover therapeutic insights. We developed iPANDDA, a computational pipeline that integrates these data through a network-based approach to predict candidate drug targets for specific diseases. We applied iPANDDA to lung squamous cell carcinoma (LUSC), a subtype of non-small cell lung cancer representing ~25% of global cases. Despite advances in cancer therapeutics, targeted treatments for LUSC remain limited, partly due to a lack of robust models to study carcinogenesis and therapeutic response. The SOX2 gene, amplified in ~50% of patients, plays a critical role in sustaining the cancer phenotype. Using iPANDDA, we identified and validated SOX2-dependent therapeutic targets. In vitro inhibition studies confirmed AKT and mTOR complexes as key monotherapy and combination therapy targets and revealed pathways for SOX2-targeted combination therapies.

<h3></h3> One in five people in the UK will develop a lung condition in their lifetime, often facing years before diagnosis. In 2023, LifeArc and Asthma + Lung UK held a workshop to identify essential diagnostic tests needed to transform respiratory care. A key priority is developing tools for timely and accurate diagnosis in primary care or expedited triage to secondary care—a ‘Simple Lung Test.’ Landscaping was conducted to develop a patient-focused Target Product Profile (TPP) for a Simple Lung Test. The aim was to base the TPP on the current diagnostic landscape, unmet clinical needs, and innovation opportunities in respiratory diagnostics. By mapping existing technologies, this work seeks to guide innovation, avoid duplication, and highlight promising innovations for diagnosis and patient triage. For the four priority chronic respiratory diseases (asthma, chronic obstructive pulmonary disease [COPD], bronchiectasis [BE], and interstitial lung disease [ILD]), 138 approved tests were identified, about half being lung function tests, primarily spirometers. Also approved are several breath analysis tests, such as FeNO and capnography tests, alongside in-vitro tests for measuring patient biomarkers, and lung imaging software. 48 tests specifically aiming to provide diagnosis are in development, covering a broad range of modalities, and mostly for providing diagnosis of COPD or asthma. The pipeline has moved away from traditional lung function tests, focusing instead on novel biomarkers, reflecting the limitations of lung function tests. Key areas of innovation include novel breath analysis tests and acoustic measurement tests, both showing active pipelines in clinical and preclinical stages. Artificial intelligence is a recurring theme for enhancing data analysis and interpretation for novel acoustic tests, blood biomarker tests, and breathomic approaches. These promising technologies offer putative advantages over current diagnostic tests, such as effort independence, rapid results, and improved accessibility, aligning with clinical priorities for novel tests.

Many protein bioconjugation strategies focus on the modification of lysine residues owing to the nucleophilicity of their amine side-chain, the generally high abundance of lysine residues on a protein's surface and the ability to form robustly stable amide-based bioconjugates. However, the plethora of solvent accessible lysine residues, which often have similar reactivity, is a key inherent issue when searching for regioselectivity and/or controlled loading of an entity. A relevant example is the modification of antibodies and/or antibody fragments, whose conjugates offer potential for a wide variety of applications. Thus, research in this area for the controlled loading of an entity via reaction with lysine residues is of high importance. In this article, we present an approach to achieve this by exploiting the quantitative and reversible site-selective modification of disulfides using pyridazinediones, which facilitates near-quantitative proximity-induced reactions with lysines to enable controlled loading of an entity. The strategy was appraised on several clinically relevant antibody fragments and enabled the formation of mono-labelled lysine-modified antibody fragment conjugates via the formation of stable amide bonds and the use of click chemistry for modular modification. Furthermore, through the use of multiple cycles of this novel strategy, an orthogonally bis-labelled lysine-modified antibody fragment conjugate was also furnished.

Introdução: A depressão é um transtorno de humor de sintomatologia abrangente, caracterizada principalmente por humor deprimido e anedonia. Por seu quadro incapacitante, necessita de tratamento multidisciplinar, através de psicoterapia e uso de fármacos antidepressivos. Objetivos: Descrever um relato de caso de bruxismo como efeito adverso ao uso de antidepressivo. Relato de caso: Paciente, 43 anos, diagnosticada com depressão, apresenta quadro de distúrbio do movimento funcional oral associado ao apertar e ranger de dentes inconsciente durante o sono, associado à hipertrofia de músculos mastigatórios, contraturas e espasmos musculares bem como fortes dores de cabeça, diagnosticado posteriormente como bruxismo do sono. Mesmo após o início do tratamento do bruxismo, o quadro mantinha-se sem remissão, pois não houve afastamento imediato do fator desencadeante. Devido a falta de correlação entre o quadro clínico e o uso de antidepressivos descritos na literatura, houve dificuldade do afastamento da causa. Somente após de avaliação clínica e laboratoriais, afastando-se fatores primários, cerca de 04 anos após o início dos sintomas, notou-se relação temporal entre o início do uso do fármaco Escitalopram, um Inibidor Seletivo da Recaptação de Serotonina, e o surgimento da disfunção motora. O quadro foi amenizado pela retirada da medicação e pelo uso de tratamentos não farmacológicos como órteses dentárias, no entanto, jamais houve remissão completa, apresentando ainda quadro ameno de apertar e ranger de dentes noturno, necessitando de acompanhamento clínico contínuo. Conclusão: O uso de fármacos antidepressivos para o tratamento de transtornos de humor é muito comum, entretanto nem todos os efeitos colaterais são bem elucidados, provocando um atraso no reconhecimento e intervenção, como ocorre no bruxismo desencadeado por fármacos antidepressivos como fator adverso.

Several rare genetic variations of human XDH have been shown to alter xanthine oxidoreductase (XOR) activity leading to impaired purine catabolism. However, XOR is a multi-functional enzyme that depending upon the environmental conditions also expresses oxidase activity leading to both O2·- and H2O2 and nitrite (NO2−) reductase activity leading to nitric oxide (·NO). Since these products express important, and often diametrically opposite, biological activity, consideration of the impact of XOR mutations in the context of each aspect of the biochemical activity of the enzyme is needed to determine the potential full impact of these variants. Herein, we show that known naturally occurring hXDH mutations do not have a uniform impact upon the biochemical activity of the enzyme in terms of uric acid (UA), reactive oxygen species (ROS) and nitric oxide ·NO formation. We show that the His1221Arg mutant, in the presence of xanthine, increases UA, O2·- and NO generation compared to the WT, whilst the Ile703Val increases UA and ·NO formation, but not O2·-. We speculate that this change in the balance of activity of the enzyme is likely to endow those carrying these mutations with a harmful or protective influence over health that may explain the current equipoise underlying the perceived importance of XDH mutations. We also show that, in presence of inorganic NO2−, XOR-driven O2·- production is substantially reduced. We suggest that targeting enzyme activity to enhance the NO2−-reductase profile in those carrying such mutations may provide novel therapeutic options, particularly in cardiovascular disease.