The pathway to diagnosis of type 1 diabetes in children: a questionnaire study.

OBJECTIVE: To explore the pathway to diagnosis of type 1 diabetes (T1D) in children. DESIGN: Questionnaire completed by parents. PARTICIPANTS: Parents of children aged 1 month to 16 years diagnosed with T1D within the previous 3 months. SETTING: Children and parents from 11 hospitals within the East of England. RESULTS: 88/164 (54%) invited families returned the questionnaire. Children had mean±SD age of 9.41±4.5 years. 35 (39.8%) presented with diabetic ketoacidosis at diagnosis. The most common symptoms were polydipsia (97.7%), polyuria (83.9%), tiredness (75.9%), nocturia (73.6%) and weight loss (64.4%) and all children presented with at least one of those symptoms. The time from symptom onset to diagnosis ranged from 2 to 315 days (median 25 days). Most of this was the appraisal interval from symptom onset until perceiving the need to seek medical advice. Access to healthcare was good but one in five children presenting to primary care were not diagnosed at first encounter, most commonly due to waiting for fasting blood tests or alternative diagnoses. Children diagnosed at first consultation had a shorter duration of symptoms (p=0.022) and children whose parents suspected the diagnosis were 1.3 times more likely (relative risk (RR) 1.3, 95% CI 1.02 to 1.67) to be diagnosed at first consultation. CONCLUSIONS: Children present with the known symptoms of T1D but there is considerable scope to improve the diagnostic pathway. Future interventions targeted at parents need to address the tendency of parents to find alternative explanations for symptoms and the perceived barriers to access, in addition to symptom awareness.The study was funded by the Royal College of General Practitioners Scientific Foundation Board (SFB-2011-15). JUS was supported by a National Institute of Health Research (NIHR) Academic Clinical Fellowship and subsequently Clinical Lectureship, and FMW by an NIHR Clinician Scientist award. SJS was supported by the Medical Research Council www.mrc.ac.uk [Unit Programme number MC_UU_12015/1]. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.This is the final version of the article. It was first published by BMJ Group at http://bmjopen.bmj.com/content/5/3/e006470.ful

Temporal discrimination is altered in patients with isolated asymmetric and jerky upper limb tremor

Background: Unilateral or very asymmetric upper limb tremors with a jerky appearance are poorly investigated. Their clinical classification is an unsolved problem because their classification as essential tremor versus dystonic tremor is uncertain. To avoid misclassification as essential tremor or premature classification as dystonic tremor, the term indeterminate tremor was suggested. Objectives: The aim of this study was to characterize this tremor subgroup electrophysiologically and evaluate whether diagnostically meaningful electrophysiological differences exist compared to patients with essential tremor and dystonic tremor. Methods: We enrolled 29 healthy subjects and 64 patients with tremor: 26 with dystonic tremor, 23 with essential tremor, and 15 patients with upper limb tremor resembling essential tremor but was unusually asymmetric and jerky (indeterminate tremor). We investigated the somatosensory temporal discrimination threshold, the short-interval intracortical inhibition, and the cortical plasticity by paired associative stimulation. Results: Somatosensory temporal discrimination threshold was significantly increased in patients with dystonic tremor and indeterminate tremor, but it was normal in the essential tremor patients and healthy controls. Significant differences in short-interval intracortical inhibition and paired associative stimulation were not found among the three patient groups and controls. Conclusion: These results indicate that indeterminate tremor, as defined in this study, shares electrophysiological similarities with dystonic tremor rather than essential tremor. Therefore, we propose that indeterminate tremor should be considered as a separate clinical entity from essential tremor and that it might be dystonic in nature. Somatosensory temporal discrimination appears to be a useful tool in tremor classification

GA-NIFS: Black hole and host galaxy properties of two z≃\simeq6.8 quasars from the NIRSpec IFU

Integral Field Spectroscopy (IFS) with JWST NIRSpec will significantly improve our understanding of the first quasars, by providing spatially resolved, infrared spectroscopic capabilities which cover key rest-frame optical emission lines that have been previously unobservable. Here we present our results from the first two z>6 quasars observed as a part of the Galaxy Assembly with NIRSpec IFS (GA-NIFS) GTO program, DELS J0411-0907 at z=6.82 and VDES J0020-3653 at z=6.86. By observing the H$\beta$, [OIII], and H$\alpha$ emission lines in these high-z quasars for the first time, we measure accurate black hole masses, $M_{\rm{BH}}=1.85e9$ and $2.9e9$M$_\odot$, corresponding to Eddington ratios of $\lambda_{\rm{Edd}}=0.8$ and 0.4 for DELS J0411-0907 and VDES J0020-3653 respectively. These provide a key comparison for existing estimates from the more uncertain MgII line. We perform quasar-host decomposition using models of the quasars' broad lines to measure the underlying host galaxies. We also discover multiple emission line regions surrounding each of the host galaxies, which are likely companion galaxies undergoing mergers with these hosts. We measure the star formation rates, excitation mechanisms, and dynamical masses of the hosts and companions, measuring the $M_{\rm{BH}}/M_{\rm{dyn}}$ ratios at high-z using these estimators for the first time. DELS J0411-0907 and VDES J0020-3653 both lie above the local black hole--host mass relation, and are consistent with the existing observations of $z\gtrsim6$ quasar host galaxies with ALMA. We detect ionized outflows in [OIII] and H$\beta$ from both quasars, with mass outflow rates of 58 and 525 M$_{\odot}$/yr for DELS J0411-0907 and VDES J0020-3653, much larger than their host star formation rates of <33 and <54 M$_\odot$/yr. This work highlights the exceptional capabilities of the JWST NIRSpec IFU for observing quasars in the early Universe.Comment: 27 pages, 10 figures. Resubmitted to A&A after significant revisions. If you have cited values from our first version, please check this version and update accordingly, as many values have changed slightly thanks to improvements in our analysi

A massive black hole in a low-metallicity AGN at z∼5.55z\sim5.55 revealed by JWST/NIRSpec IFS

We present JWST/NIRSpec Integral Field Spectrograph rest-frame optical data of the compact $z=5.55$ galaxy GS_3073. Its prominent broad components in several hydrogen and helium lines (while absent in the forbidden lines), and the detection of a large equivalent width of He II $\lambda4686$, EW(He II) $\sim20$ Angstrom, unambiguously identify it as an active galactic nucleus (AGN). We measure a gas-phase metallicity of $Z_{\rm gas}/Z_\odot\sim0.21^{+0.08}_{-0.04}$, lower than what has been inferred for both more luminous AGN at similar redshift and lower redshift AGN. We empirically show that classical emission line ratio diagnostic diagrams cannot be used to distinguish between the primary ionisation source (AGN or star formation) for such low-metallicity systems, whereas different diagnostic diagrams involving He II$\lambda4686$ prove very useful, independent of metallicity. We measure the central black hole mass to be $\log(M_{\rm BH}/M_\odot)\sim8.20^{+0.11}_{-0.16}$. While this places GS_3073 at the lower end of known high-redshift black hole masses, it still appears to be over-massive compared to its host galaxy properties. We detect an outflow with projected velocity $\gtrsim700$~km/s and an ionised gas mass outflow rate of about $100\ M_\odot/$yr, suggesting that GS_3073 is able to enrich the intergalactic medium with metals one billion years after the Big Bang.Comment: 15 pages, 10 figures; comments are welcome. Submitted to A&

Interventions targeting glucocorticoid-Krüppel-like factor 15-branched-chain amino acid signaling improve disease phenotypes in spinal muscular atrophy mice

The circadian glucocorticoid-Krüppel-like factor 15-branched-chain amino acid (GC-KLF15-BCAA) signaling pathway is a key regulatory axis in muscle, whose imbalance has wide-reaching effects on metabolic homeostasis. Spinal muscular atrophy (SMA) is a neuromuscular disorder also characterized by intrinsic muscle pathologies, metabolic abnormalities and disrupted sleep patterns, which can influence or be influenced by circadian regulatory networks that control behavioral and metabolic rhythms. We therefore set out to investigate the contribution of the GC-KLF15-BCAA pathway in SMA pathophysiology of Taiwanese Smn−/−;SMN2 and Smn2B/− mouse models. We thus uncover substantial dysregulation of GC-KLF15-BCAA diurnal rhythmicity in serum, skeletal muscle and metabolic tissues of SMA mice. Importantly, modulating the components of the GC-KLF15-BCAA pathway via pharmacological (prednisolone), genetic (muscle-specific Klf15 overexpression) and dietary (BCAA supplementation) interventions significantly improves disease phenotypes in SMA mice. Our study highlights the GC-KLF15-BCAA pathway as a contributor to SMA pathogenesis and provides several treatment avenues to alleviate peripheral manifestations of the disease. The therapeutic potential of targeting metabolic perturbations by diet and commercially available drugs could have a broader implementation across other neuromuscular and metabolic disorders characterized by altered GC-KLF15-BCAA signaling

Experience of, awareness of and help-seeking for potential cancer symptoms in smokers and non-smokers: A cross-sectional study

Background Presenting to primary care with potential cancer symptoms is contingent on one’s ability to recognize potentially serious symptoms. We investigated differences between smokers and non-smokers in symptoms experienced, awareness and consulting of potential respiratory, head and neck cancer symptoms. Methods Smokers and non-smokers aged over 50 from Yorkshire general practice lists were sent a postal questionnaire asking about symptoms, consulting and awareness of cancer symptoms. Data were analysed using STATA14. Results Response rate after one reminder was 30.5% (1205/3954). Smoking status was associated with experience of cough (p<0.001), breathlessness (p = 0.002) and tiredness (p = 0.004) with smokers (25.8% of population) more likely than never-smokers (53.6% of population) to experience all three symptoms (cough OR = 2.56;95%CI[1.75–3.75], breathlessness OR = 2.39;95%CI[1.43–4.00], tiredness OR = 1.57;95%CI[1.12–2.19]). Smoking status was associated with awareness of breathlessness as a potential cancer symptom (p = 0.035) and consulting for cough (p = 0.011) with smokers less likely to consult than never-smokers (OR = 0.37;95% CI[0.17–0.80]). Conclusion Our findings suggest that current smokers are more likely to experience cough, breathlessness and tiredness, but are less likely to consult for cough than never-smokers. To increase cancer awareness and promote consulting among smokers, innovative interventions improving symptom recognition and empowering smokers to seek help are required

JADES: Detecting [OIII]λ4363λ4363 Emitters and Testing Strong Line Calibrations in the High-zz Universe with Ultra-deep JWST/NIRSpec Spectroscopy up to z∼9.5z \sim 9.5

© 2024 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/We present ten novel [OIII]λ4363 auroral line detections up to z ∼ 9.5 measured from ultra-deep JWST/NIRSpec MSA spectroscopy from the JWST Advanced Deep Extragalactic Survey (JADES). We leverage the deepest spectroscopic observations taken thus far with NIRSpec to determine electron temperatures and oxygen abundances using the direct Te method. We directly compare these results against a suite of locally calibrated strong-line diagnostics and recent high-z calibrations. We find the calibrations fail to simultaneously match our JADES sample, thus warranting a self-consistent revision of these calibrations for the high-z Universe. We find a weak dependence between R2 and O3O2 with metallicity, thus suggesting these line ratios are inefficient in the high-z Universe as metallicity diagnostics and degeneracy breakers. We find R3 and R23 are still correlated with metallicity, but we find a tentative flattening of these diagnostics, thus suggesting future difficulties when applying these strong line ratios as metallicity indicators in the high-z Universe. We also propose and test an alternative diagnostic based on a different combination of R3 and R2 with a higher dynamic range. We find a reasonably good agreement (median offset of 0.002 dex, median absolute offset of 0.13 dex) with the JWST sample at low metallicity, but future investigations are required on larger samples to probe past the turnover point. At a given metallicity, our sample demonstrates higher ionization and excitation ratios than local galaxies with rest-frame EWs(Hβ) ≈200 − 300 Å. However, we find the median rest-frame EWs(Hβ) of our sample to be ∼2× less than the galaxies used for the local calibrations. This EW discrepancy combined with the high ionization of our galaxies does not offer a clear description of [OIII]λ4363 production in the high-z Universe, thus warranting a much deeper examination into the factors influencing these processes.Peer reviewe

Deep learning models for predicting RNA degradation via dual crowdsourcing

Medicines based on messenger RNA (mRNA) hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition (‘Stanford OpenVaccine’) on Kaggle, involving single-nucleotide resolution measurements on 6,043 diverse 102–130-nucleotide RNA constructs that were themselves solicited through crowdsourcing on the RNA design platform Eterna. The entire experiment was completed in less than 6 months, and 41% of nucleotide-level predictions from the winning model were within experimental error of the ground truth measurement. Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504–1,588 nucleotides) with improved accuracy compared with previously published models. These results indicate that such models can represent in-line hydrolysis with excellent accuracy, supporting their use for designing stabilized messenger RNAs. The integration of two crowdsourcing platforms, one for dataset creation and another for machine learning, may be fruitful for other urgent problems that demand scientific discovery on rapid timescales