This paper presents a practical solution to a problem facing high-fan-in, high-bandwidth synchronized TCP workloads in datacenter Ethernets-the TCP incast problem. In these networks, receivers can experience a drastic reduction in application throughput when simultaneously requesting data from many servers using TCP. Inbound data overfills small switch buffers, leading to TCP timeouts lasting hundreds of milliseconds. For many datacenter workloads that have a barrier synchronization requirement (e.g., filesystem reads and parallel data-intensive queries), throughput is reduced by up to 90%. For latency-sensitive applications, TCP timeouts in the datacenter impose delays of hundreds of milliseconds in networks with round-trip-times in microseconds.Our practical solution uses high-resolution timers to enable microsecond-granularity TCP timeouts. We demonstrate that this technique is effective in avoiding TCP incast collapse in simulation and in real-world experiments. We show that eliminating the minimum retransmission timeout bound is safe for all environments, including the wide-area.

This paper presents a practical solution to a problem facing high-fan-in, high-bandwidth synchronized TCP workloads in datacenter Ethernets-the TCP incast problem. In these networks, receivers can experience a drastic reduction in application throughput when simultaneously requesting data from many servers using TCP. Inbound data overfills small switch buffers, leading to TCP timeouts lasting hundreds of milliseconds. For many datacenter workloads that have a barrier synchronization requirement (e.g., filesystem reads and parallel data-intensive queries), throughput is reduced by up to 90%. For latency-sensitive applications, TCP timeouts in the datacenter impose delays of hundreds of milliseconds in networks with round-trip-times in microseconds.Our practical solution uses high-resolution timers to enable microsecond-granularity TCP timeouts. We demonstrate that this technique is effective in avoiding TCP incast collapse in simulation and in real-world experiments. We show that eliminating the minimum retransmission timeout bound is safe for all environments, including the wide-area.

Cell migration is essential to embryonic development, wound healing, and cancer cell dissemination. Cells move via leading-edge protrusion, substrate adhesion, and retraction of the cell's rear. The molecular mechanisms by which extracellular cues signal to the actomyosin cytoskeleton to control these motility mechanics are poorly understood. The growth factor-responsive and oncogenically activated protein extracellular signal-regulated kinase (ERK) promotes motility by signaling in actin polymerization-mediated edge protrusion. Using a combination of immunoblotting, co-immunoprecipitation, and myosin-binding experiments and cell migration assays, we show here that ERK also signals to the contractile machinery through its substrate, p90 ribosomal S6 kinase (RSK). We probed the signaling and migration dynamics of multiple mammalian cell lines and found that RSK phosphorylates myosin phosphatase–targeting subunit 1 (MYPT1) at Ser-507, which promotes an interaction of Rho kinase (ROCK) with MYPT1 and inhibits myosin targeting. We find that by inhibiting the myosin phosphatase, ERK and RSK promote myosin II–mediated tension for lamella expansion and optimal edge dynamics for cell migration. These findings suggest that ERK activity can coordinately amplify both protrusive and contractile forces for optimal cell motility.

Laboratory mice are used to identify causes of urinary dysfunction including prostate-related mechanisms of lower urinary tract symptoms. Effective use of mice for this purpose requires a clear understanding of molecular, cellular, anatomic, and endocrine contributions to voiding function. Whether the prostate influences baseline voiding function has not been specifically evaluated, in part because most methods that alter prostate mass also change circulating testosterone concentrations. We performed void spot assay and cystometry to establish a multiparameter “baseline” of voiding function in intact male and female 9-wk-old (adult) C57BL/6J mice. We then compared voiding function in intact male mice to that of castrated male mice, male (and female) mice treated with the steroid 5α-reductase inhibitor finasteride, or male mice harboring alleles ( Pbsn4cre/+; R26RDta/+) that significantly reduce prostate lobe mass by depleting prostatic luminal epithelial cells. We evaluated aging-related changes in male urinary voiding. We also treated intact male, castrate male, and female mice with exogenous testosterone to determine the influence of androgen on voiding function. The three methods used to reduce prostate mass (castration, finasteride, and Pbsn4cre/+; R26RDta/+) changed voiding function from baseline but in a nonuniform manner. Castration feminized some aspects of male urinary physiology (making them more like intact female mice) while exogenous testosterone masculinized some aspects of female urinary physiology (making them more like intact male mice). Our results provide evidence that circulating testosterone is responsible in part for baseline sex differences in C57BL/6J mouse voiding function while prostate lobe mass in young, healthy adult mice has a lesser influence.

Sclerotinia stem rot (SSR) epidemics in soybean, caused by Sclerotinia sclerotiorum, are currently responsible for annual yield reductions in the United States of up to 1 million metric tons. In-season disease management is largely dependent on chemical control but its efficiency and cost-effectiveness depends on both the chemistry used and the risk of apothecia formation, germination, and further dispersal of ascospores during susceptible soybean growth stages. Hence, accurate prediction of the S. sclerotiorum apothecial risk during the soybean flowering period could enable farmers to improve in-season SSR management. From 2014 to 2016, apothecial presence or absence was monitored in three irrigated (n = 1,505 plot-level observations) and six nonirrigated (n = 2,361 plot-level observations) field trials located in Iowa (n = 156), Michigan (n = 1,400), and Wisconsin (n = 2,310), for a total of 3,866 plot-level observations. Hourly air temperature, relative humidity, dew point, wind speed, leaf wetness, and rainfall were also monitored continuously, throughout the season, at each location using high-resolution gridded weather data. Logistic regression models were developed for irrigated and nonirrigated conditions using apothecial presence as a binary response variable. Agronomic variables (row width) and weather-related variables (defined as 30-day moving averages, prior to apothecial presence) were tested for their predictive ability. In irrigated soybean fields, apothecial presence was best explained by row width (r = −0.41, P < 0.0001), 30-day moving averages of daily maximum air temperature (r = 0.27, P < 0.0001), and daily maximum relative humidity (r = 0.16, P < 0.05). In nonirrigated fields, apothecial presence was best explained by using moving averages of daily maximum air temperature (r = –0.30, P < 0.0001) and wind speed (r = –0.27, P < 0.0001). These models correctly predicted (overall accuracy of 67 to 70%) apothecial presence during the soybean flowering period for four independent datasets (n = 1,102 plot-level observations or 30 daily mean observations).

Bacterial infection is one known etiology of prostatic inflammation. Prostatic inflammation is associated with prostatic collagen accumulation and both are linked to progressive lower urinary tract symptoms in men. We characterized a model of prostatic inflammation utilizing transurethral instillations of E. coli UTI89 in C57BL/6J male mice with the goal of determining the optimal instillation conditions, understanding the impact of instillation conditions on urinary physiology, and identifying ideal prostatic lobes and collagen 1a1 prostatic cell types for further analysis. The smallest instillation volume tested (50 µL) distributes exclusively to bladder, 100 and 200 µL volumes distributes to bladder and prostate, and a 500 µL volume distributes to bladder, prostate and ureter. A threshold optical density (OD) of 0.4 E. coli UTI89 in the instillation fluid is necessary for significant (p < 0.05) prostate colonization. E. coli UTI89 infection results in a low frequency, high volume spontaneous voiding pattern. This phenotype is due to exposure to E. coli UTI89, not catheterization alone, and is minimally altered by a 50 µL increase in instillation volume and doubling of E. coli concentration. Prostate inflammation is isolated to the dorsal prostate and is accompanied by increased collagen density. This is partnered with increased density of PTPRC+, ProCOL1A1+ co-positive cells and decreased density of ACTA2+, ProCOL1A1+ co-positive cells. Overall, we determined that this model is effective in altering urinary phenotype and producing prostatic inflammation and collagen accumulation in mice.

In soybean, Sclerotinia sclerotiorum apothecia are the sources of primary inoculum (ascospores) critical for Sclerotinia stem rot (SSR) development. We recently developed logistic regression models to predict the presence of apothecia in irrigated and nonirrigated soybean fields. In 2017, small-plot trials were established to validate two weather-based models (one for irrigated fields and one for nonirrigated fields) to predict SSR development. Additionally, apothecial scouting and disease monitoring were conducted in 60 commercial fields in three states between 2016 and 2017 to evaluate model accuracy across the growing region. Site-specific air temperature, relative humidity, and wind speed data were obtained through the Integrated Pest Information Platform for Extension and Education (iPiPE) and Dark Sky weather networks. Across all locations, iPiPE-driven model predictions during the soybean flowering period (R1 to R4 growth stages) explained end-of-season disease observations with an accuracy of 81.8% using a probability action threshold of 35%. Dark Sky data, incorporating bias corrections for weather variables, explained end-of-season disease observations with 87.9% accuracy (in 2017 commercial locations in Wisconsin) using a 40% probability threshold. Overall, these validations indicate that these two weather-based apothecial models, using either weather data source, provide disease risk predictions that both reduce unnecessary chemical application and accurately advise applications at critical times.

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