Identifying encephalopathy in patients admitted to an intensive care unit: Going beyond structured information using natural language processing

BackgroundEncephalopathy is a severe co-morbid condition in critically ill patients that includes different clinical constellation of neurological symptoms. However, even for the most recognised form, delirium, this medical condition is rarely recorded in structured fields of electronic health records precluding large and unbiased retrospective studies. We aimed to identify patients with encephalopathy using a machine learning-based approach over clinical notes in electronic health records.MethodsWe used a list of ICD-9 codes and clinical concepts related to encephalopathy to define a cohort of patients from the MIMIC-III dataset. Clinical notes were annotated with MedCAT and vectorized with a bag-of-word approach or word embedding using clinical concepts normalised to standard nomenclatures as features. Machine learning algorithms (support vector machines and random forest) trained with clinical notes from patients who had a diagnosis of encephalopathy (defined by ICD-9 codes) were used to classify patients with clinical concepts related to encephalopathy in their clinical notes but without any ICD-9 relevant code. A random selection of 50 patients were reviewed by a clinical expert for model validation.ResultsAmong 46,520 different patients, 7.5% had encephalopathy related ICD-9 codes in all their admissions (group 1, definite encephalopathy), 45% clinical concepts related to encephalopathy only in their clinical notes (group 2, possible encephalopathy) and 38% did not have encephalopathy related concepts neither in structured nor in clinical notes (group 3, non-encephalopathy). Length of stay, mortality rate or number of co-morbid conditions were higher in groups 1 and 2 compared to group 3. The best model to classify patients from group 2 as patients with encephalopathy (SVM using embeddings) had F1 of 85% and predicted 31% patients from group 2 as having encephalopathy with a probability >90%. Validation on new cases found a precision ranging from 92% to 98% depending on the criteria considered.ConclusionsNatural language processing techniques can leverage relevant clinical information that might help to identify patients with under-recognised clinical disorders such as encephalopathy. In the MIMIC dataset, this approach identifies with high probability thousands of patients that did not have a formal diagnosis in the structured information of the EHR

Widespread extrahepatic expression of acute-phase proteins in chicken (Gallus gallus) tissues

Acute Phase Proteins (APP) are plasma proteins that can modify their expression in response toinflammation caused by tissue injury, infections, immunological disorders, or stress. Although APP areproduced mainly in liver, extrahepatic production has been described (Marques et al., 2016; Lecchi etal., 2012). The aim of this work was to study the extrahepatic gene expression of five APP, namely α1-acid glycoprotein (AGP), Serum amyloid A (SAA), Haptoglobin-like protein (PIT54), C-rective protein(CRP) and Ovotransferrin (OVT) (O'Reilly and Eckersall, 2014) in different healthy chicken (Gallus gallus)tissues by quantitative real time PCR (qPCR) and immunohistochemistry to detect the precise locationof the proteins.APP gene expression was higher in liver compared with other tissues. mRNA coding for CRP, OVT andSAA was detected in all tissues involved in this study with a higher expression in gastrointestinal tract,respiratory system and lymphatic system. SAA expression was particularly high in cecal tonsil, lung,spleen and meckel’s diverticulum, whereas OVT showed a high expression in lung, bursa of Fabricius,pancreas, brain and adipose tissue. AGP and PIT54 was also detected in pericardial adipose tissue,spleen, kidney, lung, mucosa of proventriculus, mucosa of gizzard and pancreas but, oppositely to SAA,their mRNA was not detected in meckel’s diverticulum, cecal tonsil and bursa of Fabricius. These resultssuggest that each tissue is able to express different amount of APP even in healthy conditions andmount a local acute phase reaction. Immunohistochemistry to detect the precise location for AGP, OVTand SAA using available antibodies is ongoing

Near Isotropic D4d Spin Qubits as Nodes of a Gd(III)-Based Metal-Organic Framework

Embedding coherent spin motifs in reproducible molecular building blocks is a promising pathway for the realization of quantum technologies. Three-dimensional (3D) MOFs are a versatile platform for the rational design of extended structures employing coordination chemistry. Here, we report the synthesis and characterization of a gadolinium(III)-based MOF, [Gd(bipyNO)4](TfO)3·xMeOH (bipyNO = bipyridine,N,N′-dioxide; TfO = triflate; and MeOH = methanol) (quMOF-1), which presents a unique coordination geometry that leads to a tiny magnetic anisotropy (in terms of D, an equivalent zero-field splitting would be achieved by D = 0.006 cm-1) even compared with regular Gd(III) complexes. Pulsed electron paramagnetic resonance experiments on its magnetically diluted samples confirm the preservation of quantum coherence of single Gd(III) qubit units in this 3D extended molecular architecture (T2 = 612 ns and T1 = 66 μs at 3.5 K), which allows for the detection of Rabi oscillations at 40 K

Peptides as Versatile Platforms for Quantum Computing

The pursuit of novel functional building blocks for the emerging field of quantum computing is one of the most appealing topics in the context of quantum technologies. Herein we showcase the urgency of introducing peptides as versatile platforms for quantum computing. In particular, we focus on lanthanide-binding tags, originally developed for the study of protein structure. We use pulsed electronic paramagnetic resonance to demonstrate quantum coherent oscillations in both neodymium and gadolinium peptidic qubits. Calculations based on density functional theory followed by a ligand field analysis indicate the possibility of influencing the nature of the spin qubit states by means of controlled changes in the peptidic sequence. We conclude with an overview of the challenges and opportunities opened by this interdisciplinary field

Reduced serial dependence suggests deficits in synaptic potentiation in anti-NMDAR encephalitis and schizophrenia

A mechanistic understanding of core cognitive processes, such as working memory, is crucial to addressing psychiatric symptoms in brain disorders. We propose a combined psychophysical and biophysical account of two symptomatologically related diseases, both linked to hypofunctional NMDARs: schizophrenia and autoimmune anti-NMDAR encephalitis. We first quantified shared working memory alterations in a delayed-response task. In both patient groups, we report a markedly reduced influence of previous stimuli on working memory contents, despite preserved memory precision. We then simulated this finding with NMDAR-dependent synaptic alterations in a microcircuit model of prefrontal cortex. Changes in cortical excitation destabilized within-trial memory maintenance and could not account for disrupted serial dependence in working memory. Rather, a quantitative fit between data and simulations supports alterations of an NMDAR-dependent memory mechanism operating on longer timescales, such as short-term potentiation

Placental transfer of NMDAR antibodies causes reversible alterations in mice

Objective: To determine whether maternofetal transfer of NMDA receptor (NMDAR) antibodies has pathogenic effects on the fetus and offspring, we developed a model of placental transfer of antibodies. Methods: Pregnant C57BL/6J mice were administered via tail vein patients' or controls' immunoglobulin G (IgG) on days 14-16 of gestation, when the placenta is able to transport IgG and the immature fetal blood-brain barrier is less restrictive to IgG crossing. Immunohistochemical and DiOlistic (gene gun delivery of fluorescent dye) staining, confocal microscopy, standardized developmental and behavioral tasks, and hippocampal long-term potentiation were used to determine the antibody effects. Results: In brains of fetuses, patients' IgG, but not controls' IgG, bound to NMDAR, causing a decrease in NMDAR clusters and cortical plate thickness. No increase in neonatal mortality was observed, but offspring exposed in utero to patients' IgG had reduced levels of cell-surface and synaptic NMDAR, increased dendritic arborization, decreased density of mature (mushroom-shaped) spines, microglial activation, and thinning of brain cortical layers II-IV with cellular compaction. These animals also had a delay in innate reflexes and eye opening and during follow-up showed depressive-like behavior, deficits in nest building, poor motor coordination, and impaired social-spatial memory and hippocampal plasticity. Remarkably, all these paradigms progressively improved (becoming similar to those of controls) during follow-up until adulthood. Conclusions: In this model, placental transfer of patients' NMDAR antibodies caused severe but reversible synaptic and neurodevelopmental alterations. Reversible antibody effects may contribute to the infrequent and limited number of complications described in children of patients who develop anti-NMDAR encephalitis during pregnancy

Binding Sites, Vibrations and Spin-Lattice Relaxation Times in Europium(II)-Based Metallofullerene Spin Qubits

To design molecular spin qubits with enhanced quantum coherence, a control of the coupling between the local vibrations and the spin states is crucial, which could be realized in principle by engineering molecular structures via coordination chemistry. To this end, understanding the underlying structural factors that govern the spin relaxation is a central topic. Here, we report the investigation of the spin dynamics in a series of chemically designed europium(II)-based endohedral metallofullerenes (EMFs). By introducing a unique structural difference, i. e. metal-cage binding site, while keeping other molecular parameters constant between different complexes, these manifest the key role of the three low-energy metal-displacing vibrations in mediating the spin-lattice relaxation times (T1). The temperature dependence of T1 can thus be normalized by the frequencies of these low energy vibrations to show an unprecedentedly universal behavior for EMFs in frozen CS2 solution. Our theoretical analysis indicates that this structural difference determines not only the vibrational rigidity but also spin-vibration coupling in these EMF-based qubit candidates