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Time to lithium: a case register study of lithium initiation in bipolar disorder
No full textBackground: Lithium monotherapy has been recommended as first-line maintenance or long term pharmacological therapy for bipolar disorder (BD). Previous research has linked early
lithium use with better outcomes for people with BD. Despite extensive evidence as an
effective treatment for BD, lithium prescribing continues to decline.
Aims: Our primary aim was to determine time between initial assessment by mental health
services and lithium initiation in people with BD who initiated lithium. Secondary objectives
included determining time between first assessment and recorded BD diagnosis, number of
prior mood episodes, polarity when lithium was prescribed and number of antipsychotics
before lithium initiation.
Methods: Free-text clinical notes were extracted from a de-identified electronic health record
database. Eligible records comprised adults with BD diagnosis who were concordant with
lithium treatment.
Results: 88 people were identified, based on inclusion and exclusion criteria. Median time
between first assessment and lithium initiation was 659 days. Median time between first
assessment and BD diagnosis was 220 days, with a median of 2.5 mood episodes and 2
antipsychotics prescribed prior to lithium. Around 30% of people presented with manic
symptoms at time of lithium prescription. There is significant delay between first contact with
services and initiation of lithium in people with BD.
Conclusions: This highlights the potential for earlier intervention with lithium, which could
improve of outcomes for people with BD
Oncogenic KRAS/ERK/JUNB signaling suppresses differentiation regulator GATA6 in pancreatic cancer.
No full textGATA6 is a master regulator of differentiation in the pancreas, and its expression levels determine the 2 main molecular subtypes of pancreatic cancer. High GATA6 levels contribute to the classical pancreatic cancer subtype, which is associated with a higher degree of tumor differentiation and better disease prognosis. However, why GATA6 expression varies across pancreatic cancers and what regulates GATA6 expression remain elusive. Here, we report that oncogenic KRAS-activated ERK signaling suppresses GATA6 transcription in pancreatic cancers. GATA6 mRNA levels inversely correlated with KRAS/ERK activity in pancreatic tumors. A genome-wide CRISPR screen in a GATA6-EGFP reporter knockin cell line identified JUNB as the ERK-regulated transcriptional repressor for GATA6. Active ERK stabilized JUNB protein, while KRAS/ERK inhibition led to ubiquitin-independent proteasomal degradation of JUNB and increased transcription of GATA6. Upregulation of GATA6 enhanced chemosensitivity of pancreatic cancer cells, and KRAS/ERK inhibitors synergized with chemotherapy in a GATA6-dependent manner. Our study identifies how oncogenic KRAS/ERK signaling suppresses GATA6 to cause dedifferentiation in pancreatic cancer. Combining KRAS/ERK inhibitors with standard-of-care chemotherapies could be a promising therapeutic strategy for treating pancreatic cancers
Rubrik’s Cube: Testing a New Rubric for Evaluating Explanations on the CUBE dataset
Get PDFThe performance and usability of Large-Language Models (LLMs) are driving their use in explanation generation tasks. However, despite their widespread adoption, LLM explanations have been found to be unreliable, making it difficult for users to distinguish good from bad explanations. To address this issue, we present Rubrik's CUBE-an education-inspired rubric and a dataset of 26k explanations, written and later quality-annotated using the rubric by both humans and six open- and closed-source LLMs. The CUBE dataset focuses on two reasoning and two language tasks, providing the necessary diversity for us to effectively test our proposed rubric. Using Rubrik, we find that explanations are influenced by both task and perceived difficulty. Low quality stems primarily from a lack of conciseness in LLM-generated explanations, rather than cohesion and word choice. The full dataset, rubric, and code are available at https://github.com/RubriksCube/rubriks_cube
Deep learning of temporal renewable energy patterns for optimizing Power-to-X processes
No full textThe inherently intermittent nature of renewable energy and its geographic variations make the optimisation of Power-to-X processes dependent on the local temporal characteristics of solar and wind energy generation profiles. By using green ammonia production as a case study, this paper demonstrates that deep convolutional and recurrent neural networks can successfully learn key characteristics of renewable power profiles (capacity production, peak supply and intermittency) and accordingly determine the capacity of the solar panels/wind turbines, electrolysers and hydrogen storage to minimise the cost of green ammonia production. By learning implicit cost relationships, deep neural networks can also predict the economically optimal process design with an error of 5-15%. As a result, neural networks can be implemented for rapid screening of locations for initial economic feasibility of Power-to-X processes, providing the foundations for more challenging optimizations such as those considering decades of weather-based renewable power profiles and complex energy system models
The Relationship Between Demographic and Medical Characteristics and the Development of Posttraumatic Stress Disorder in Children Following Emergency Department Attendance: A Prospective Study.
Get PDFOBJECTIVES: This study adopted a prospective longitudinal design to assess the utility of demographic and medical characteristics routinely available to emergency medicine clinicians to predict the development of posttraumatic stress disorder (PTSD) in children exposed to death or serious injury 2 months following emergency department (ED) attendance. METHODS: A sample of children (8-17 years; N = 231) were recruited from 4 EDs in the East of England between 2010 and 2013. Within 2 weeks of attendance, research nurses screened records for appropriate cases and recorded information on relevant variables from ED attendance notes. At 2 months, a research assistant carried out a structured clinical interview to assess their Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) PTSD symptoms. Univariate analyses were conducted to compare ED characteristics between children who developed PTSD and those who did not. Logistic regression models were used to identify variables associated with increased risk of PTSD. RESULTS: Ten percent of children met the criteria for PTSD at 2 months. Systolic blood pressure, pulse, number of injuries, being subjected to interpersonal violence, and having a head injury were variables that distinguished PTSD and non-PTSD groups. Logistic regression models showed that being assaulted was predictive of PTSD (Odds ratio = 5.07, 95% CI [1.51, 17.00]); although these models had excellent specificity (0.96), the sensitivity was poor (0.30)-that is, there were a number of cases who developed PTSD but were not assaulted. CONCLUSION: PTSD is a complication of exposure to death or injury that occurs in a significant minority of children. Children who are victims of interpersonal violence are more likely to develop the disorder
Comparing the effect of multi-gradient echo and multi-band fMRI during a semantic task
Get PDFAbstract The blood oxygenation level dependent (BOLD) signal, as measured using functional magnetic resonance imaging (fMRI), is known to vary in sensitivity across the brain due to magnetic susceptibility artefacts. For example, the ventral anterior temporal lobes have been implicated with semantic cognition using convergent methods (i.e., neuropsychology, PET, MEG, brain stimulation) but less so with fMRI using conventional gradient-echo protocols. Of the methods to alleviate this signal loss, “multi-echo” fMRI has gained popularity. Here, additional volumes are collected with a range of echo times (TEs), subsequent combination of which can improve BOLD contrast-to-noise. However, these additional volumes normally require compromising other MR sequence parameters (e.g., longer repetition times, higher in-plane acceleration). One solution is to combine multi-echo with “multi-band” imaging, in which simultaneous acquisition of multiple slices reduces repetition time again. However, it remains unclear how these two modifications independently or interactively affect fMRI sensitivity across the brain, for univariate or multi-variate analyses. In the current study, we used a factorial design in which the number of echoes and/or bands was manipulated to assess how well semantically related activation/multi-voxel patterns can be detected. When comparing the precision with which activations were detected (i.e., average T-statistics), we found that multi-band protocols were beneficial, with no evidence of signal leakage artefacts. When comparing the magnitude of activations, multi-echo protocols increased activations in regions prone to susceptibility artefacts (particularly in the temporal lobes). Both multi-banding and independent component analysis (ICA)-denoising of multi-echo data tended to improve multi-voxel decoding of conditions. However, multi-echo protocols reduced activation magnitude in more central regions, such as the medial temporal lobes, possibly due to the higher in-plane acceleration entailed. Nonetheless, the multi-echo, multi-band protocol is a promising default option for fMRI on most regions, particularly those that suffer from susceptibility artefacts, as well as offering the potential to apply advanced post-processing methods to take advantage of the increased temporal (or spatial) resolution of multi-band protocols and more principled ICA-denoising based on TE dependence of BOLD signals
Deciphering Delphic guidance: The Bank of England and geopolitical uncertainty
Get PDFThe effective transmission of monetary policy can be hampered by geopolitical uncertainty, at times necessitating central banks to adapt their tools and communication strategy in order to anchor market expectations. The UK 2016 referendum on EU membership is a prominent example of geopolitical uncertainty, manifested as a historic event. Accordingly, this paper examines how the Bank of England (BoE) adjusted their response, including through conventional, unconventional monetary policy measures and communications. We use text-based analysis of Monetary Policy Committee (MPC) summaries and minutes to measure the stance of policy, QE-related news and geopolitical uncertainty. To investigate the impact of central bank communication, we then decompose long-dated yields into a risk-neutral and term premium component and analyse the dynamic response to MPC communication. We show that the Bank’s communication strategy acted to complement the stance of monetary policy, which had responded to the result of the referendum by lowering Bank Rate and expanding QE, and helped lower the term premium that might otherwise have risen in response to this example of geopolitical uncertainty
Persistent immune, coagulation and cardiac dysregulation are correlated with later post-discharge mortality in children with severe malnutrition.
Get PDFBACKGROUND: Children with complicated severe malnutrition (CSM) face high mortality after hospital discharge, yet the underlying mechanisms remain poorly understood. While early post-discharge mortality (< 2 months) has been linked to a sepsis-like inflammatory profile measured at discharge, it is unclear whether this relationship persists (later mortality; 2-6 months post-discharge). This study investigated whether immune, inflammatory, and endothelial dysfunction at 2 months post-discharge are associated with later mortality in children recovering from CSM. METHODS: We conducted a case-control study nested within a randomised placebo-controlled trial of daily co-trimoxazole in HIV-negative children aged 2-59 months with CSM in four Kenyan hospitals. Cases were children who died between 2 and 6 months post-discharge; controls were survivors frequency-matched by sex, site, and trial arm. Plasma cytokines, chemokines, endothelial markers, and untargeted proteomics were measured at discharge and 2 months post-discharge. Conditional Cox regression, adjusted for age, sex, site, mid-upper arm circumference (MUAC), and randomisation arm, was used to identify biomarkers associated with later mortality. RESULTS: Cases were younger (had a median of 7 vs. 11 months), had longer hospital stays (14 vs. 10 days), and showed lower anthropometry (MUAC = 10.7 vs. 12.0 cm) and lower haemoglobin (9.7 vs. 10.6 g/dL) at 2 months post-discharge (all p < 0.05). Mortality 2-6 months post-discharge was associated with elevated inflammatory mediators (e.g. IL-10 [hazard ratio, HR: 1.47, 95% confidence interval, CI: 1.00-2.14], IL-15 [1.65, 95% CI: 1.08-2.51], IFN-α2 [1.51, 95% CI: 1.02-2.23]), acute phase proteins, apolipoproteins and coagulation markers, including fibrinogen, histidine-rich glycoprotein (1.40, 95% CI: 1.01-1.94), protein C inhibitor (SERPINA5, 1.50, 95% CI: 1.07-2.08), SERPINA10 (1.42, 95% CI: 1.02-1.99), and ADAMTS13 (0.41, 95% CI: 0.24-0.70). Additionally, cardiovascular and muscle-related proteins such as angiotensinogen (1.46, 95% CI: 1.03-2.08), α- and β-tropomyosin (0.68, 95% CI: 0.48-0.98), PI16 (0.72, 95% CI:0.54-0.97), and zyxin (0.61, 95% CI: 0.40-0.92) were elevated in cases. CONCLUSIONS: Later mortality in children recovering from CSM is associated with persistent immune activation, a sepsis-like phenotype involving multiple systems. These findings suggest that children at risk of later mortality may benefit from biomarker-guided interventions initiated at discharge
