Active learning-based multistage sequential decision-making model with application on common bile duct stone evaluation.

Multistage sequential decision-making occurs in many real-world applications such as healthcare diagnosis and treatment. One concrete example is when the doctors need to decide to collect which kind of information from subjects so as to make the good medical decision cost-effectively. In this paper, an active learning-based method is developed to model the doctors' decision-making process that actively collects necessary information from each subject in a sequential manner. The effectiveness of the proposed model, especially its two-stage version, is validated on both simulation studies and a case study of common bile duct stone evaluation for pediatric patients.

Creation of a Pediatric Choledocholithiasis Prediction Model.

BACKGROUND: Definitive non-invasive detection of pediatric choledocholithiasis could allow more efficient identification of those patients who are most likely to benefit from therapeutic endoscopic retrograde cholangiopancreatography (ERCP) for stone extraction. OBJECTIVE: To craft a pediatric choledocholithiasis prediction model using a combination of commonly available serum laboratory values and ultrasound results. METHODS: A retrospective review of laboratory and imaging results from 316 pediatric patients who underwent intraoperative cholangiogram or ERCP due to suspicion of choledocholithiasis were collected and compared to presence of common bile duct stones on cholangiography. Multivariate logistic regression with supervised machine learning was used to create a predictive scoring model. Monte-Carlo cross-validation was used to validate the scoring model and a score threshold that would provide at least 90% specificity for choledocholithiasis was determined in an effort to minimize non-therapeutic ERCP. RESULTS: Alanine aminotransferase (ALT), total bilirubin, alkaline phosphatase, and common bile duct diameter via ultrasound were found to be the key clinical variables to determine the likelihood of choledocholithiasis. The dictated specificity threshold of 90.3% yielded a sensitivity of 40.8% and overall accuracy of 71.5% in detecting choledocholithiasis. Positive predictive value was 71.4% and negative predictive value was 72.1%. CONCLUSION: Our novel pediatric choledocholithiasis predictive model is a highly specific tool to suggest ERCP in the setting of likely choledocholithiasis.

Ecosystem state change in the Arabian Sea fuelled by the recent loss of snow over the Himalayan-Tibetan Plateau region.

The recent trend of global warming has exerted a disproportionately strong influence on the Eurasian land surface, causing a steady decline in snow cover extent over the Himalayan-Tibetan Plateau region. Here we show that this loss of snow is undermining winter convective mixing and causing stratification of the upper layer of the Arabian Sea at a much faster rate than predicted by global climate models. Over the past four decades, the Arabian Sea has also experienced a profound loss of inorganic nitrate. In all probability, this is due to increased denitrification caused by the expansion of the permanent oxygen minimum zone and consequent changes in nutrient stoichiometries. These exceptional changes appear to be creating a niche particularly favorable to the mixotroph, Noctiluca scintillans which has recently replaced diatoms as the dominant winter, bloom forming organism. Although Noctiluca blooms are non-toxic, they can cause fish mortality by exacerbating oxygen deficiency and ammonification of seawater. As a consequence, their continued range expansion represents a significant and growing threat for regional fisheries and the welfare of coastal populations dependent on the Arabian Sea for sustenance.

Mesenchymal Stem Cells Promote the Resolution of Cardiac Inflammation After Ischemia Reperfusion Via Enhancing Efferocytosis of Neutrophils.

Background Neutrophils play a major role in inflammation after myocardial ischemia-reperfusion (I/R) injury. The effects of mesenchymal stem cells (MSCs) on neutrophils in I/R are complex and not fully understood. This study was designed to investigate the effects and mechanism of MSCs on alleviating myocardial I/R injury in rats. Methods and Results MSCs induced M2 macrophages polarization in vitro and enhanced macrophage efferocytosis of apoptotic neutrophils, measured by fluorescence-activated cell sorting analysis and immunofluorescence staining. Rats myocardial I/R were induced by transient ligation of left anterior descending coronary. Adipose-derived MSCs or vehicle were infused at initiation (immediate after reperfusion) or peak of inflammation (24 hours after I/R). Hematoxylin and eosin, 2,3,5-triphenyltetrazolium chloride/Evans Blue staining and immunofluorescence staining were applied within 72 hours after cell infusion. Cardiac function was assessed by echocardiography and left cardiac catheterization analysis at 28 days post-operation. MSCs infused immediately and 24 hours later both markedly ameliorated myocardial I/R injury, and immediate infusion had more significant outcome. These improvements were associated with neutrophils infiltration, measured by fluorescence-activated cell sorting analysis and immunofluorescence staining. When infused immediately, MSCs did not significantly change neutrophil number at 24 hours but CD11b expression was significantly higher. When infused at 24 hours, MSCs markedly decreased neutrophil number by enhanced M2 macrophage infiltration and macrophage efferocytosis of neutrophils within 72 hours. Conclusions Efferocytosis is pivotal to relieve neutrophil-mediated I/R injury and initial the immune response for healing. MSCs infusion improves cardiac function in rats after myocardial I/R via the possible mechanism of enhancing M2 macrophages-induced efferocytosis of apoptotic neutrophils.

Designing flexible 2D transition metal carbides with strain-controllable lithium storage.

Efficient flexible energy storage systems have received tremendous attention due to their enormous potential applications in self-powering portable electronic devices, including roll-up displays, electronic paper, and "smart" garments outfitted with piezoelectric patches to harvest energy from body movement. Unfortunately, the further development of these technologies faces great challenges due to a lack of ideal electrode materials with the right electrochemical behavior and mechanical properties. MXenes, which exhibit outstanding mechanical properties, hydrophilic surfaces, and high conductivities, have been identified as promising electrode material candidates. In this work, taking 2D transition metal carbides (TMCs) as representatives, we systematically explored several influencing factors, including transition metal species, layer thickness, functional group, and strain on their mechanical properties (e.g., stiffness, flexibility, and strength) and their electrochemical properties (e.g., ionic mobility, equilibrium voltage, and theoretical capacity). Considering potential charge-transfer polarization, we employed a charged electrode model to simulate ionic mobility and found that ionic mobility has a unique dependence on the surface atomic configuration influenced by bond length, valence electron number, functional groups, and strain. Under multiaxial loadings, electrical conductivity, high ionic mobility, low equilibrium voltage with good stability, excellent flexibility, and high theoretical capacity indicate that the bare 2D TMCs have potential to be ideal flexible anode materials, whereas the surface functionalization degrades the transport mobility and increases the equilibrium voltage due to bonding between the nonmetals and Li. These results provide valuable insights for experimental explorations of flexible anode candidates based on 2D TMCs.

Catalytic oxidation of Li2S on the surface of metal sulfides for Li-S batteries.

Polysulfide binding and trapping to prevent dissolution into the electrolyte by a variety of materials has been well studied in Li-S batteries. Here we discover that some of those materials can play an important role as an activation catalyst to facilitate oxidation of the discharge product, Li2S, back to the charge product, sulfur. Combining theoretical calculations and experimental design, we select a series of metal sulfides as a model system to identify the key parameters in determining the energy barrier for Li2S oxidation and polysulfide adsorption. We demonstrate that the Li2S decomposition energy barrier is associated with the binding between isolated Li ions and the sulfur in sulfides; this is the main reason that sulfide materials can induce lower overpotential compared with commonly used carbon materials. Fundamental understanding of this reaction process is a crucial step toward rational design and screening of materials to achieve high reversible capacity and long cycle life in Li-S batteries.