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Non-steroidal anti-inflammatory drugs (NSAIDs), intravenous fluid, pancreatic stents, or combinations of these have been evaluated in randomised controlled trials (RCTs) for the prevention of post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis, but the comparative efficacy of these treatments remains unclear. Our aim was to do an exploratory network meta-analysis of previous RCTs to systematically compare the direct and indirect evidence and rank NSAIDs, intravenous fluids, pancreatic stents, or combinations of these to determine the most efficacious method of prophylaxis for post-ERCP pancreatitis.

We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a machine learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to 7615 samples from 5178 individuals, 2073 with solid cancer and the remainder without cancer. Samples from patients with cancer and controls were prespecified into four cohorts used for model training, analyte integration, and threshold determination, validation, and reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the validation cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and eight common protein biomarkers detected 51% of the cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature—the global reduction of AluS subfamily elements in the circulating DNA of patients with solid cancer. We confirmed this reduction through the analysis of another independent dataset obtained with a different approach (whole-genome sequencing). The evaluation of Alu elements may therefore have the potential to enhance the performance of several methods designed for the earlier detection of cancer.

A three-dimensional numerical model is used to investigate the mechanisms that contribute to the formation of the turbidity maxima in the York River, Virginia (U.S.). The model reproduces the basic features in both salinity and total suspended sediments (TSS) fields for three different patterns. Both the prominent estuary turbidity maximum (ETM) and the newly discovered secondary turbidity maximum (STM) are simulated when river discharge is relatively low. At higher river inflow, the two turbidity maxima move closer to each other. During very high river discharge event, only the prominent turbidity maximum is simulated. Diagnostic model studies also suggest that bottom resuspension is an important source of TSS in both the ETM and the STM, and confirm the observed association between the turbidity maxima and the stratification patterns in the York River estuary. The ETM is usually located near the head of salt intrusion and the STM is often associated with a transition zone between upriver well mixed and downriver more stratified water columns. Analysis of the model results from the diagnostic studies indicates that the location of the ETM is well associated with the null point of bottom residual flow. Convergent bottom residual flow, as well as tidal asymmetry, is the most important mechanisms that contribute to the formation of the STM. the STM often exists in a region with landward decrease of bottom residual flow and net landward sediment flux due to tidal asymmetry. The channel depth of this region usually decreases sharply upriver. As channel depth decreases, vertical mixing increases and hence the water column is better mixed landward of the STM.

Abstract: Data from a two-year period of monthly slackwater surveys reveal that in addition to the classical estuary turbidity maximum (ETM), another peak of bottom total suspended sediment (TSS) concentration, or a so-called secondary turbidity maximum (STM), often exists in the middle part of the York River estuary, Virginia. This STM, observed in most (but not all) of the slackwater surveys, moves back and forth in the region of about 20 to 40 km from the York River mouth where the mud percentage of bottom sediment is very high. The distribution of the potential energy anomaly, which was calculated using salinity data, indicates that the STM usually resides in the transition zone between the upstream well mixed and the downstream more stratified water columns. An analysis using the conservation equation of suspended sediment concentration in the water column reveals that four processes may contribute to the formation of the STM: convergence of bottom residual flow, tidal asymmetry, inhibition of turbulent diffusion by stratification, and bottom resuspension. The along-channel variations of the strength of bottom residual flow, the effect of tidal asymmetry, and the stratification patterns are probably due to the geometric features of the York River estuary.

Abstract: A simple computational framework is developed to include shoals and shallow embayments (SSE) and their interaction with main channels in estuarine modeling. The scheme, treating SSE as temporary storage areas, accounts for the water and material exchanges between SSE and main channels as the tide rises and falls, and for the biogeochemical processes affecting nonconservative substances such as water-quality parameters in SSE. The scheme, because of its simple nature, can be easily incorporated into one-, two- or three-dimensional models of estuaries with substantial SSE. The concept and the model implementation of the scheme are explained using a vertical two-dimensional model of estuarine hydrodynamics and water quality. The model application to the tidal Rappahannock River, a western shore tributary of Chesapeake Bay, demonstrates the scheme is simple and physically reasonable, and the importance of SSE in estuarine modeling. The inclusion of SSE in a water-quality model not only provides a framework, for computing water-quality conditions therein but also accounts for the interaction between SSE and the main channel. It is shown that significant errors may result if the effects of SSE are not properly accounted for in modeling of an estuary with extensive SSE.

A model is developed to describe the turbidity plume induced by dredging a ship channel using an hydraulic dredge. The model predicts the suspended sediment concentration within the plume and the resulting sediment deposition alongside the dredged channel. The model applies to a dredging operation in a water body in which the current is primarily along the channel axis and the channel depth is large enough that no significant suspended sediment reaches water surface. Results of field measurements are presented and compared with model. It is shown that the model describes the qualitative feature of prototype data and that the calibrated model parameters agree with independent observations by other investigators.

Abstract: Hypoxia/anoxia in bottom waters of the Rappahannock River, a tributary estuary of Chesapeake Bay, was observed to persist throughout the summer in the deep basin near the river mouth; periodic reoxygenation of bottom water occurred on the shallower sill at the river mouth. The reoxygenation events were closely related to spring tide mixing. The dissolved oxygen (DO) in surface waters was always near or at the saturation level, while that of bottom waters exhibited a characteristic spatial pattern. The bottom DO decreased upriver from river mouth, reaching a minimum upriver of the deepest point of the river and increasing as the water becaume shallower further upriver. A model was formulated to describe the longitudinal distribution of DO in bottom waters. The model is based on Lagrangian concept—following a water parcel as it travels upriver along the estuarine bottom. The model successfully describes the characteristic distribution of DO and also explains the shifting of the minimum DO location in response to spring-neap cycling. A diagnostic study with the model provided insight into relationships between the bottom DO and the competing factors that contribute to the DO budget of bottom waters. The study reveals that both oxygen demand, either benthic or water column demand, and vertical mixing have a promounced effect on the severity of hypoxia in bottom waters of an estary. However, it is the vertical mixing which controls the longitudinal location of the minimum DO. The strength of gravitational circulation is also shown to affect the occurrence of hypoxia. An estuary with stronger circulation tends to have less chance for hypoxia to occur. The initial DO deficit of bottom water entering an estuary has a strong effect on DO concentration near the river mouth, but its effect diminishes in the upriver direction.

Abstract: Hypoxia, periods of reduced dissolved oxygen concentrations, has been observed not only in the Chesapeake Bay but also in the deeper waters of the Virginia estuaries that are tributaries to the Chesapeake Bay. When water temperature exceeded 20�C, minimum oxygen concentrations were observed to be <50% of saturation concentrations in 75%, 50% and 2% of the surveys in the estuaries of the Rappahannock, York and James rivers, respectively. The observation that hypoxia rarely occurred in the James River is surprising, given the fact that it receives the greatest amount of wastewater. Analysis of the oxygen budgets in these estuaries indicates that the variations in the frequency, duration, and severity of hypoxia are related to the net movement of bottom waters. This relationship has significant implications for the management of water quality and marine fisheries.

A model based on the analytical solution of an advective‐diffusion equation is developed to describe the turbidity plume induced by the operation of a bucket dredge. The model applies to the portion of the plume beyond the initial mixing zone where the separate patches of suspended sediments have coalesced into a continuous plume. It predicts the vertical average suspended sediment concentration within the plume as a function of the source strength of suspended sediment, the characteristics of the ambient flow field and the effective particle settling velocity. Four sets of field data from previous studies are compared with the model. It is shown that the model describes the qualitative feature of prototype data and that the calibrated model parameters agree with independent observations.