A multi-stage machine learning model on diagnosis of esophageal manometry

High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its interpretation and classification includes an initial evaluation of swallow-level outcomes and then derivation of a study-level diagnosis based on Chicago Classification (CC), using a tree-like algorithm. This diagnostic approach on motility disordered using HRM was mirrored using a multi-stage modeling framework developed using a combination of various machine learning approaches. Specifically, the framework includes deep-learning models at the swallow-level stage and feature-based machine learning models at the study-level stage. In the swallow-level stage, three models based on convolutional neural networks (CNNs) were developed to predict swallow type, swallow pressurization, and integrated relaxation pressure (IRP). At the study-level stage, model selection from families of the expert-knowledge-based rule models, xgboost models and artificial neural network(ANN) models were conducted, with the latter two model designed and augmented with motivation from the export knowledge. A simple model-agnostic strategy of model balancing motivated by Bayesian principles was utilized, which gave rise to model averaging weighted by precision scores. The averaged (blended) models and individual models were compared and evaluated, of which the best performance on test dataset is 0.81 in top-1 prediction, 0.92 in top-2 predictions. This is the first artificial-intelligence-style model to automatically predict CC diagnosis of HRM study from raw multi-swallow data. Moreover, the proposed modeling framework could be easily extended to multi-modal tasks, such as diagnosis of esophageal patients based on clinical data from both HRM and functional luminal imaging probe panometry (FLIP)

Single-molecule visualization of Saccharomyces cerevisiae leading-strand synthesis reveals dynamic interaction between MTC and the replisome

The replisome, the multiprotein system responsible for genome duplication, is a highly dynamic complex displaying a large number of different enzyme activities. Recently, the Saccharomyces cerevisiae minimal replication reaction has been successfully reconstituted in vitro. This provided an opportunity to uncover the enzymatic activities of many of the components in a eukaryotic system. Their dynamic behavior and interactions in the context of the replisome, however, remain unclear. We use a tethered-bead assay to provide real-time visualization of leading-strand synthesis by the S. cerevisiae replisome at the single-molecule level. The minimal reconstituted leading-strand replisome requires 24 proteins, forming the CMG helicase, the Pol e DNA polymerase, the RFC clamp loader, the PCNA sliding clamp, and the RPA single-stranded DNA binding protein. We observe rates and product lengths similar to those obtained from ensemble biochemical experiments. At the single-molecule level, we probe the behavior of two components of the replication progression complex and characterize their interaction with active leading-strand replisomes. The Minichromosome maintenance protein 10 (Mcm10), an important player in CMG activation, increases the number of productive replication events in our assay. Furthermore, we show that the fork protection complex Mrc1-Tof1-Csm3 (MTC) enhances the rate of the leading-strand replisome threefold. The introduction of periods of fast replication by MTC leads to an average rate enhancement of a factor of 2, similar to observations in cellular studies. We observe that the MTC complex acts in a dynamic fashion with the moving replisome, leading to alternating phases of slow and fast replication

Nuclease dead Cas9 is a programmable roadblock for DNA replication

Limited experimental tools are available to study the consequences of collisions between DNA-bound molecular machines. Here, we repurpose a catalytically inactivated Cas9 (dCas9) construct as a generic, novel, targetable protein-DNA roadblock for studying mechanisms underlying enzymatic activities on DNA substrates in vitro. We illustrate the broad utility of this tool by demonstrating replication fork arrest by the specifically bound dCas9-guideRNA complex to arrest viral, bacterial and eukaryotic replication forks in vitro

Gas-Particle Partitioning of Atmospheric Hg(II) and Its Effect on Global Mercury Deposition

Atmospheric deposition of Hg(II) represents a major input of mercury to surface environments. The phase of Hg(II) (gas or particle) has important implications for deposition. We use long-term observations of reactive gaseous mercury (RGM, the gaseous component of Hg(II)), particle-bound mercury (PBM, the particulate component of Hg(II)), fine particulate matter (PM2.5), and temperature (T) at five sites in North America to derive an empirical gas-particle partitioning relationship log10(K−1) = (10±1)–(2500±300)/T where K = (PBM/PM2.5)/RGM with PBM and RGM in common mixing ratio units, PM2.5 in μg m−3, and T in K. This relationship is within the range of previous work but is based on far more extensive data from multiple sites. We implement this empirical relationship in the GEOS-Chem global 3-D Hg model to partition Hg(II) between the gas and particle phases. The resulting gas-phase fraction of Hg(II) ranges from over 90 % in warm air with little aerosol to less than 10 % in cold air with high aerosol. Hg deposition to high latitudes increases because of more efficient scavenging of particulate Hg(II) by precipitating snow. Model comparison to Hg observations at the North American surface sites suggests that subsidence from the free troposphere (warm air, low aerosol) is a major factor driving the seasonality of RGM, while elevated PBM is mostly associated with high aerosol loads. Simulation of RGM and PBM at these sites is improved by including fast in-plume reduction of Hg(II) emitted from coal combustion and by assuming that anthropogenic particulate Hg(p) behaves as semi-volatile Hg(II) rather than as a refractory particulate component. We improve the simulation of Hg wet deposition fluxes in the US relative to a previous version of GEOS-Chem; this largely reflects independent improvement of the washout algorithm. The observed wintertime minimum in wet deposition fluxes is attributed to inefficient snow scavenging of gas-phase Hg(II).Earth and Planetary SciencesEngineering and Applied Science

The Process of Replication Target Selection in Psychology: What to Consider?

Increased execution of replication studies contributes to the effort to restore credibility of empirical research. However, a second generation of problems arises: the number of potential replication targets is at a serious mismatch with available resources. Given limited resources, replication target selection should be well justified, systematic, and transparently communicated. At present the discussion on what to consider when selecting a replication target is limited to theoretical discussion, self-reported justifications, and a few formalized suggestions. In this Registered Report, we proposed a study involving the scientific community to create a list of considerations for consultation when selecting a replication target in psychology. We employed a modified Delphi approach. First, we constructed a preliminary list of considerations. Second, we surveyed psychologists who previously selected a replication target with regards to their considerations. Third, we incorporated the results into the preliminary list of considerations and sent the updated list to a group of individuals knowledgeable about concerns regarding replication target selection. Over the course of several rounds, we established consensus regarding what to consider when selecting a replication target

Family violence, war, and natural disasters: A study of the effect of extreme stress on children's mental health in Sri Lanka

Catani C, Jacob N, Schauer E, Kohila M, Neuner F. Family violence, war, and natural disasters: a study of the effect of extreme stress on children's mental health in Sri Lanka. BMC Psychiatry. 2008;8(1): 33.BACKGROUND: The consequences of war violence and natural disasters on the mental health of children as well as on family dynamics remain poorly understood. Aim of the present investigation was to establish the prevalence and predictors of traumatic stress related to war, family violence and the recent Tsunami experience in children living in a region affected by a long-lasting violent conflict. In addition, the study looked at whether higher levels of war violence would be related to higher levels of violence within the family and whether this would result in higher rates of psychological problems in the affected children. METHODS: 296 Tamil school children in Sri Lanka's North-Eastern provinces were randomly selected for the survey. Diagnostic interviews were carried out by extensively trained local Master level counselors. PTSD symptoms were established by means of a validated Tamil version of the UCLA PTSD Index. Additionally, participants completed a detailed checklist of event types related to organized and family violence. RESULTS: 82.4% of the children had experienced at least one war-related event. 95.6% reported at least one aversive experience out of the family violence spectrum. The consequences are reflected in a 30.4% PTSD and a 19.6% Major Depression prevalence. Linear regression analyses showed that fathers' alcohol intake and previous exposure to war were significantly linked to the amount of maltreatment reported by the child. A clear dose-effect relationship between exposure to various stressful experiences and PTSD was found in the examined children. CONCLUSION: Data argue for a relationship between war violence and violent behavior inflicted on children in their families. Both of these factors, together with the experience of the recent Tsunami, resulted as significant predictors of PTSD in children, thus highlighting the detrimental effect that the experience of cumulative stress can have on children's mental health

Interleukin-8 Is Activated in Patients with Chronic Liver Diseases and Associated with Hepatic Macrophage Accumulation in Human Liver Fibrosis

BACKGROUND: Interleukin-8 (IL-8, CXCL8) is a potent chemoattractant for neutrophils and contributes to acute liver inflammation. Much less is known about IL-8 in chronic liver diseases (CLD), but elevated levels were reported from alcoholic and hepatitis C-related CLD. We investigated the regulation of IL-8, its receptors CXCR1 and CXCR2 and possible IL-8 responding cells in CLD patients. METHODOLOGY: Serum IL-8 levels were measured in CLD patients (n = 200) and healthy controls (n = 141). Intrahepatic IL-8, CXCR1 and CXCR2 gene expression was quantified from liver samples (n = 41), alongside immunohistochemical neutrophil (MPO) and macrophage (CD68) stainings. CXCR1 and CXCR2 expression was analyzed on purified monocytes from patients (n = 111) and controls (n = 31). In vitro analyses explored IL-8 secretion by different leukocyte subsets. PRINCIPAL FINDINGS: IL-8 serum levels were significantly increased in CLD patients, especially in end-stage cirrhosis. Interestingly, patients with cholestatic diseases exhibited highest IL-8 serum concentrations. IL-8 correlated with liver function, inflammatory cytokines and non-invasive fibrosis markers. Intrahepatically, IL-8 and CXCR1 expression were strongly up-regulated. However, intrahepatic IL-8 could only be associated to neutrophil infiltration in patients with primary biliary cirrhosis (PBC). In non-cholestatic cirrhosis, increased IL-8 and CXCR1 levels were associated with hepatic macrophage accumulation. In line, CXCR1, but not CXCR2 or CXCR3, expression was increased on circulating monocytes from cirrhotic patients. Moreover, monocyte-derived macrophages from CLD patients, especially the non-classical CD16⁺ subtype, displayed enhanced IL-8 secretion in vitro. CONCLUSIONS: IL-8 is strongly activated in CLD, thus likely contributing to hepatic inflammation. Our study suggests a novel role of IL-8 for recruitment and activation of hepatic macrophages via CXCR1 in human liver cirrhosis

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO

Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO