MiR-218 Inhibits Invasion and Metastasis of Gastric Cancer by Targeting the Robo1 Receptor

MicroRNAs play key roles in tumor metastasis. Here, we describe the regulation and function of miR-218 in gastric cancer (GC) metastasis. miR-218 expression is decreased along with the expression of one of its host genes, Slit3 in metastatic GC. However, Robo1, one of several Slit receptors, is negatively regulated by miR-218, thus establishing a negative feedback loop. Decreased miR-218 levels eliminate Robo1 repression, which activates the Slit-Robo1 pathway through the interaction between Robo1 and Slit2, thus triggering tumor metastasis. The restoration of miR-218 suppresses Robo1 expression and inhibits tumor cell invasion and metastasis in vitro and in vivo. Taken together, our results describe a Slit-miR-218-Robo1 regulatory circuit whose disruption may contribute to GC metastasis. Targeting miR-218 may provide a strategy for blocking tumor metastasis

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Advances in endoscopic retrograde cholangiopancreatography

Endoscopic retrograde cholangiopancreatography (ERCP) is a well-established advanced endoscopic technique for the diagnosis and treatment of pancreatobiliary diseases. New advances have been made in the treatment concept and techniques of ERCP in recent years. This article elaborates on the recent advances in ERCP, including the application of pancreatic duct stent, non-steroidal anti-inflammatory drugs, and aggressive hydration to prevent postoperative pancreatitis, covered metal stent for the treatment of benign bile duct stenosis, intraluminal radiofrequency ablation for malignant bile duct stenosis, extracorporeal shockwave lithotripsy and covered metal stent for the treatment of chronic pancreatitis, peroral choledochoscopy for qualitative diagnosis of bile duct stenosis and huge refractory stones, definition of difficult intubation, timing of pre-cut technique, and ERCP after gastrointestinal reconstruction

Source and Evolution of Subduction–Related Hot Springs Discharged in Tengchong Geothermal Field, Southwest China: Constrained by Stable H, O, and Mg Isotopes

The hydrothermal system plays a crucial role in material and energy cycling between the lithosphere and hydrosphere. In general, seafloor hydrothermal systems are one of important Mg sinks, but the situation may not be the same as it is in terrestrial hydrothermal systems. In addition, the behavior of Mg isotopes during hydrothermal circulation is still unclear. Thus, in this study, we determined the Mg isotopic compositions of the hydrothermal fluids discharged in the Tengchong region to understand better the fate of Mg in the continental hydrothermal system. The δ2H and δ18O values of the Tengchong hydrothermal fluids indicate that the recharge water sources are primary from meteoric water and influenced by the evaporation process. In contrast, the subduction–related volcanic water input is limited, except in for the Rehai area. The Mg in most of the samples is contributed by percolated meteoric water. The measured δ26Mg values range from –0.969 to 0.173‰, which are enriched in light Mg compared to the volcanic rocks of Tengchong. Combined with the precipitation dissolution of carbonate, we calculated the δ26Mg value for the endmember fluid before precipitation, which shows that the process of carbonate precipitation changes the Mg isotope of the fluid, substantially. The Shiqiang (SQ) vent is unique among all of the samples, characterized by an extremely a high δ26Mg value and Mg concentration, and it is estimated that it could have been mixed with an upper crustal material. This also reveals the diversity of the hydrothermal fluid material sources in the subduction zone

Numerical simulations on active shielding methods comparison and wrapped angle optimization for gradient coil design in MRI with enhanced shielding effect

The switching of a gradient coil current in magnetic resonance imaging will induce an eddy current in the surrounding conducting structures while the secondary magnetic field produced by the eddy current is harmful for the imaging. To minimize the eddy current effects, the stray field shielding in the gradient coil design is usually realized by minimizing the magnetic fields on the cryostat surface or the secondary magnetic fields over the imaging region. In this work, we explicitly compared these two active shielding design methods. Both the stray field and eddy current on the cryostat inner surface were quantitatively discussed by setting the stray field constraint with an ultra-low maximum intensity of 2 G and setting the secondary field constraint with an extreme small shielding ratio of 0.000 001. The investigation revealed that the secondary magnetic field control strategy can produce coils with a better performance. However, the former (minimizing the magnetic fields) is preferable when designing a gradient coil with an ultra-low eddy current that can also strictly control the stray field leakage at the edge of the cryostat inner surface. A wrapped-edge gradient coil design scheme was then optimized for a more effective control of the stray fields. The numerical simulation on the wrapped-edge coil design shows that the optimized wrapping angles for the x and z coils in terms of our coil dimensions are 40° and 90°, respectively