Predicting streamflow with LSTM networks using global datasets

Streamflow predictions remain a challenge for poorly gauged and ungauged catchments. Recent research has shown that deep learning methods based on Long Short-Term Memory (LSTM) cells outperform process-based hydrological models for rainfall-runoff modeling, opening new possibilities for prediction in ungauged basins (PUB). These studies usually feature local datasets for model development, while predictions in ungauged basins at a global scale require training on global datasets. In this study, we develop LSTM models for over 500 catchments from the CAMELS-US data base using global ERA5 meteorological forcing and global catchment characteristics retrieved with the HydroMT tool. Comparison against an LSTM trained with local datasets shows that, while the latter generally yields superior performances due to the higher spatial resolution meteorological forcing (overall median daily NSE 0.54 vs. 0.71), training with ERA5 results in higher NSE in most catchments of Western and North-Western US (median daily NSE of 0.83 vs. 0.78). No significant changes in performance occur when substituting local with global data sources for deriving the catchment characteristics. These results encourage further research to develop LSTM models for worldwide predictions of streamflow in ungauged basins using available global datasets. Promising directions include training the models with streamflow data from different regions of the world and with higher quality meteorological forcing

Validation of Novel Molecular Imaging Targets Identified by Functional Genomic mRNA Profiling to Detect Dysplasia in Barrett’s Esophagus

SIMPLE SUMMARY: Barrett’s esophagus (BE) is the precursor of esophageal adenocarcinoma (EAC). Dysplastic BE (DBE), including low-grade dysplasia (LGD) and high-grade dysplasia (HGD), shows a higher progression risk to EAC compared to non-dysplastic BE (NDBE). If LGD or HGD is detected, more intensive endoscopic surveillance or endoscopic treatment is recommended. This results in a significantly improved prognosis compared to EACs treated by surgery and/or chemoradiotherapy. However, the miss rates for detecting DBE by endoscopy remain high. Fluorescence molecular endoscopy (FME) can fill this gap by targeting the tumor-specific expression of proteins. This study aimed to identify target proteins suitable for FME. We identified SPARC, SULF1, PKCι, and DDR1 as promising imaging targets for FME to differentiate DBE from NDBE tissue. We are also the first to develop near-infrared fluorescent tracers, SULF1-800CW and SPARC-800CW, for the endoscopic imaging of DBE tissue. ABSTRACT: Barrett’s esophagus (BE) is the precursor of esophageal adenocarcinoma (EAC). Dysplastic BE (DBE) has a higher progression risk to EAC compared to non-dysplastic BE (NDBE). However, the miss rates for the endoscopic detection of DBE remain high. Fluorescence molecular endoscopy (FME) can detect DBE and mucosal EAC by highlighting the tumor-specific expression of proteins. This study aimed to identify target proteins suitable for FME. Publicly available RNA expression profiles of EAC and NDBE were corrected by functional genomic mRNA (FGmRNA) profiling. Following a class comparison between FGmRNA profiles of EAC and NDBE, predicted, significantly upregulated genes in EAC were prioritized by a literature search. Protein expression of prioritized genes was validated by immunohistochemistry (IHC) on DBE and NDBE tissues. Near-infrared fluorescent tracers targeting the proteins were developed and evaluated ex vivo on fresh human specimens. In total, 1976 overexpressed genes were identified in EAC (n = 64) compared to NDBE (n = 66) at RNA level. Prioritization and IHC validation revealed SPARC, SULF1, PKCι, and DDR1 (all p < 0.0001) as the most attractive imaging protein targets for DBE detection. Newly developed tracers SULF1-800CW and SPARC-800CW both showed higher fluorescence intensity in DBE tissue compared to paired non-dysplastic tissue. This study identified SPARC, SULF1, PKCι, and DDR1 as promising targets for FME to differentiate DBE from NDBE tissue, for which SULF1-800CW and SPARC-800CW were successfully ex vivo evaluated. Clinical studies should further validate these findings

Indirect measurement of pinch and pull forces at the shaft of laparoscopic graspers

The grasping instruments used in minimally invasive surgery reduce the ability of the surgeon to feel the forces applied on the tissue, thereby complicating the handling of the tissue and increasing the risk of tissue damage. Force sensors implemented in the forceps of the instruments enable accurate measurements of applied forces, but also complicate the design of the instrument. Alternatively, indirect estimations of tissue interaction forces from measurements of the forces applied on the handle are prone to errors due to friction in the linkages. Further, the force transmission from handle to forceps exhibits large nonlinearities, so that extensive calibration procedures are needed. The kinematic analysis of the grasping mechanism and experimental results presented in this paper show that an intermediate solution, force measurements at the shaft and rod of the grasper, enables accurate measurements of the pinch and pull forces on tissue with only a limited number of calibration measurements. We further show that the force propagation from the shaft and rod to the forceps can be approximated by a linear two-dimensional function of the opening angle of the grasper and the force on the rod

Sex Differences in Prehospital Identification of Large Vessel Occlusion in Patients with Suspected Stroke

BACKGROUND: Differences in clinical presentation of acute ischemic stroke between men and women may affect prehospital identification of anterior circulation large vessel occlusion (aLVO). We assessed sex differences in diagnostic performance of 8 prehospital scales to detect aLVO. METHODS: We analyzed pooled individual patient data from 2 prospective cohort studies (LPSS [Leiden Prehospital Stroke Study] and PRESTO [Prehospital Triage of Patients With Suspected Stroke Study]) conducted in the Netherlands between 2018 and 2019, including consecutive patients ≥18 years suspected of acute stroke who presented within 6 hours after symptom onset. Ambulance paramedics assessed clinical items from 8 prehospital aLVO detection scales: Los Angeles Motor Scale, Rapid Arterial Occlusion Evaluation, Cincinnati Stroke Triage Assessment Tool, Cincinnati Prehospital Stroke Scale, Prehospital Acute Stroke Severity, gaze-face-arm-speech-time, Conveniently Grasped Field Assessment Stroke Triage, and Face-Arm-Speech-Time Plus Severe Arm or Leg Motor Deficit. We assessed the diagnostic performance of these scales for identifying aLVO at prespecified cut points for men and women.RESULTS: Of 2358 patients with suspected stroke (median age, 73 years; 47% women), 231 (10%) had aLVO (100/1114 [9%] women and 131/1244 [11%] men). The area under the curve of the scales ranged from 0.70 (95% CI, 0.65-0.75) to 0.77 (95% CI, 0.73-0.82) in women versus 0.69 (95% CI, 0.64-0.73) to 0.75 (95% CI, 0.71-0.79) in men. Positive predictive values ranged from 0.23 (95% CI, 0.20-0.27) to 0.29 (95% CI, 0.26-0.31) in women versus 0.29 (95% CI, 0.24-0.33) to 0.37 (95% CI, 0.32-0.43) in men. Negative predictive values were similar (0.95 [95% CI, 0.94-0.96] to 0.98 [95% CI, 0.97-0.98] in women versus 0.94 [95% CI, 0.93-0.95] to 0.96 [95% CI, 0.94-0.97] in men). Sensitivity of the scales was slightly higher in women than in men (0.53 [95% CI, 0.43-0.63] to 0.76 [95% CI, 0.68-0.84] versus 0.49 [95% CI, 0.40-0.57] to 0.63 [95% CI, 0.55-0.73]), whereas specificity was lower (0.79 [95% CI, 0.76-0.81] to 0.87 [95% CI, 0.84-0.89] versus 0.82 [95% CI, 0.79-0.84] to 0.90 [95% CI, 0.88-0.91]). Rapid arterial occlusion evaluation showed the highest positive predictive values in both sexes (0.29 in women and 0.37 in men), reflecting the different event rates. CONCLUSIONS: aLVO scales show similar diagnostic performance in both sexes. The rapid arterial occlusion evaluation scale may help optimize prehospital transport decision-making in men as well as in women with suspected stroke.</p

Fine-tuning of seasonal timing of breeding is regulated downstream in the underlying neuro-endocrine system in a small songbird

The timing of breeding is under selection in wild populations as a result of climate change, and understanding the underlying physiological processes mediating this timing provides insight into the potential rate of adaptation. Current knowledge on this variation in physiology is, however, mostly limited to males. We assessed whether individual differences in the timing of breeding in females are reflected in differences in candidate gene expression and, if so, whether these differences occur in the upstream (hypothalamus) or downstream (ovary and liver) parts of the neuroendocrine system. We used 72 female great tits from two generations of lines artificially selected for early and late egg laying, which were housed in climate-controlled aviaries and went through two breeding cycles within 1 year. In the first breeding season we obtained individual egg-laying dates, while in the second breeding season, using the same individuals, we sampled several tissues at three time points based on the timing of the first breeding attempt. For each tissue, mRNA expression levels were measured using qPCR for a set of candidate genes associated with the timing of reproduction and subsequently analysed for differences between generations, time points and individual timing of breeding. We found differences in gene expression between generations in all tissues, with the most pronounced differences in the hypothalamus. Differences between time points, and early- and late-laying females, were found exclusively in the ovary and liver. Altogether, we show that fine-tuning of the seasonal timing of breeding, and thereby the opportunity for adaptation in the neuroendocrine system, is regulated mostly downstream in the neuro-endocrine system.Peer reviewe

ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

Correction to: Putting genome-wide sequencing in neonates into perspective

The original version of this Article contained an error in the spelling of the author Pleuntje J. van der Sluijs, which was incorrectly given as Eline (P. J.) van der Sluijs. This has now been corrected in both the PDF and HTML versions of the Article

Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model

Summary Background Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive, fatal motor neuron disease with a variable natural history. There are no accurate models that predict the disease course and outcomes, which complicates risk assessment and counselling for individual patients, stratification of patients for trials, and timing of interventions. We therefore aimed to develop and validate a model for predicting a composite survival endpoint for individual patients with ALS. Methods We obtained data for patients from 14 specialised ALS centres (each one designated as a cohort) in Belgium, France, the Netherlands, Germany, Ireland, Italy, Portugal, Switzerland, and the UK. All patients were diagnosed in the centres after excluding other diagnoses and classified according to revised El Escorial criteria. We assessed 16 patient characteristics as potential predictors of a composite survival outcome (time between onset of symptoms and non-invasive ventilation for more than 23 h per day, tracheostomy, or death) and applied backward elimination with bootstrapping in the largest population-based dataset for predictor selection. Data were gathered on the day of diagnosis or as soon as possible thereafter. Predictors that were selected in more than 70% of the bootstrap resamples were used to develop a multivariable Royston-Parmar model for predicting the composite survival outcome in individual patients. We assessed the generalisability of the model by estimating heterogeneity of predictive accuracy across external populations (ie, populations not used to develop the model) using internal–external cross-validation, and quantified the discrimination using the concordance (c) statistic (area under the receiver operator characteristic curve) and calibration using a calibration slope. Findings Data were collected between Jan 1, 1992, and Sept 22, 2016 (the largest data-set included data from 1936 patients). The median follow-up time was 97·5 months (IQR 52·9–168·5). Eight candidate predictors entered the prediction model: bulbar versus non-bulbar onset (univariable hazard ratio [HR] 1·71, 95% CI 1·63–1·79), age at onset (1·03, 1·03–1·03), definite versus probable or possible ALS (1·47, 1·39–1·55), diagnostic delay (0·52, 0·51–0·53), forced vital capacity (HR 0·99, 0·99–0·99), progression rate (6·33, 5·92–6·76), frontotemporal dementia (1·34, 1·20–1·50), and presence of a C9orf72 repeat expansion (1·45, 1·31–1·61), all p<0·0001. The c statistic for external predictive accuracy of the model was 0·78 (95% CI 0·77–0·80; 95% prediction interval [PI] 0·74–0·82) and the calibration slope was 1·01 (95% CI 0·95–1·07; 95% PI 0·83–1·18). The model was used to define five groups with distinct median predicted (SE) and observed (SE) times in months from symptom onset to the composite survival outcome: very short 17·7 (0·20), 16·5 (0·23); short 25·3 (0·06), 25·2 (0·35); intermediate 32·2 (0·09), 32·8 (0·46); long 43·7 (0·21), 44·6 (0·74); and very long 91·0 (1·84), 85·6 (1·96). Interpretation We have developed an externally validated model to predict survival without tracheostomy and non-invasive ventilation for more than 23 h per day in European patients with ALS. This model could be applied to individualised patient management, counselling, and future trial design, but to maximise the benefit and prevent harm it is intended to be used by medical doctors only. Funding Netherlands ALS Foundation