During the past 30 yr an impasse has developed in the discovery and commercialization of synthetic herbicides with new molecular targets and novel chemistries. Similarly, there has been little success with bioherbicides, both microbial and chemical. These bioherbicides are needed to combat fast-growing herbicide resistance and to fulfill the need for more environmentally and toxicologically safe herbicides. In response to this substantial and growing opportunity, numerous start-up companies are utilizing novel approaches to provide new tools for weed management. These diverse new tools broaden the scope of discovery, encompassing advanced computational, bioinformatic, and imaging platforms; plant genome–editing and targeted protein degradation technologies; and machine learning and artificial intelligence (AI)-based strategies. This review contains summaries of the presentations of 10 such companies that took part in a symposium held at the WSSA annual meeting in 2024. Four of the companies are developing microbial bioherbicides or natural product–based herbicides, and the other six are using advanced technologies, such as AI, to accelerate the discovery of herbicides with novel molecular target sites or to develop non-GMO, herbicide-resistant crops.

We present a re-analysis of the results obtained from a series of measurements on freshwater and saline ice beams under various centrifugal accelerations. The data show a strong influence of beam size, brine volume and centrifugal acceleration on the elastic modulus of ice. The data suggest a transition brine volume at around 9%, which might occur close to the melting point, at which the elastic modulus of ice drops rapidly due to a possible change of brine-pocket structure. Furthermore, for brine volumes less than 9%, there is a negligible increase in the elastic modulus measured under high centrifugal acceleration, but for brine volumes more than 9% the increase is considerable, approaching that measured with freshwater ice. This may be due to necking of brine drainage channels just above the ice/water interface at high centrifugal acceleration. A model of sea ice was constructed based on existing theories of brine inclusions in sea ice, which satisfactorily predicts the observed trends.

Crop yield loss–weed density relationships critically influence calculation of economic thresholds and the resulting management recommendations made by a bioeconomic model. To examine site-to-site and year-to-year variation in winter Triticum aestivum L. (winter wheat)–Aegilops cylindrica Host. (jointed goatgrass) interference relationships, the rectangular hyperbolic yield loss function was fit to data sets from multiyear field experiments conducted at Colorado, Idaho, Kansas, Montana, Nebraska, Utah, Washington, and Wyoming. The model was fit to three measures of A. cylindrica density: fall seedling, spring seedling, and reproductive tiller densities. Two parameters: i, the slope of the yield loss curve as A. cylindrica density approaches zero, and a, the maximum percentage yield loss as A. cylindrica density becomes very large, were estimated for each data set using nonlinear regression. Fit of the model to the data was better using spring seedling densities than fall seedling densities, but it was similar for spring seedling and reproductive tiller densities based on the residual mean square (RMS) values. Yield loss functions were less variable among years within a site than among sites for all measures of weed density. For the one site where year-to-year variation was observed (Archer, WY), parameter a varied significantly among years, but parameter i did not. Yield loss functions differed significantly among sites for 7 of 10 comparisons. Site-to-site statistical differences were generally due to variation in estimates of parameter i. Site-to-site and year-to-year variation in winter T. aestivum–A. cylindrica yield loss parameter estimates indicated that management recommendations made by a bioeconomic model cannot be based on a single yield loss function with the same parameter values for the winter T. aestivum-producing region. The predictive ability of a bioeconomic model is likely to be improved when yield loss functions incorporating time of emergence and crop density are built into the model's structure.

Field studies were conducted in Colorado, Kansas, and Wyoming to compare the use of quinclorac plus 2,4-D with picloram plus 2,4-D, dicamba plus 2,4-D, a glyphosate plus 2,4-D premix, and 2,4-D alone for control of field bindweed (Convolvulus arvensis) in a winter wheat (Triticum aestivum)-fallow rotation. Treatments were applied in late summer or fall each year for two, three, or four consecutive years at the beginning and end of each fallow period. Evaluations were taken 10 to 12 mo after treatment each year. Quinclorac plus 2,4-D and picloram plus 2,4-D consistently performed as well as or better than 2,4-D, dicamba plus 2,4-D, and glyphosate plus 2,4-D. Wheat yields increased when field bindweed was controlled during the fallow period. Strong correlations (r > −0.85) were obtained among visual field bindweed evaluation, biomass, and stand count data.

Jointed goatgrass is a problem weed in winter wheat production areas of the Great Plains. Winter wheat seeding rates are easily adjusted by the growers and influence competition by some weeds. Field experiments were initiated in Kansas, Nebraska, and Wyoming using winter wheat cultivars selected from leading adapted cultivars from each region to determine the effect of wheat plant density in the fall on jointed goatgrass competitiveness. Three winter wheat seeding rates (50, 67, and 84 kg seeds/ha) were used at Hays, KS, and Sidney, NE, and four seeding rates (33, 50, 67, and 101 kg seeds/ha) were used at Torrington and Archer, WY. An analysis of covariance model was fit with winter wheat fall plant density as the covariate. In 1996, winter wheat grain contamination (dockage) was reduced at the rate of about 6% for every 10 additional wheat plants/m2 above the threshold density of 70 plants/m2 at Archer, WY, and at the rate of about 0.5% for every 10 additional wheat plants/m2 above the threshold density of 110 plants/m2 at Hays, KS. At Hays the reduction occurred only with the semidwarf cultivar ‘Vista’. Increased wheat density reduced jointed goatgrass reproductive tillers in four out of six location–year combinations and biomass in two out of four location–year combinations. Despite the lack of a consistent reduction in jointed goatgrass competitiveness as the result of increased wheat density, increased seeding rates may be a good, low-cost, long-term investment as part of an integrated jointed goatgrass control program in winter wheat.

Secale cereale is a serious weed problem in winter Triticum aestivum–producing regions. The interference relationships and economic thresholds of S. cereale in winter T. aestivum in Colorado, Kansas, Nebraska, and Wyoming were determined over 4 yr. Winter T. aestivum density was held constant at recommended planting densities for each site. Target S. cereale densities were 0, 5, 10, 25, 50, or 100 plants m−2. Secale cereale–winter T. aestivum interference relationships across locations and years were determined using a negative hyperbolic yield loss function. Two parameters—I, which represents the percent yield loss as S. cereale density approaches zero, and A, the maximum percent yield loss as S. cereale density increases—were estimated for each data set using nonlinear regression. Parameter I was more stable among years within locations than among locations within years, whereas maximum percentage yield loss was more stable across locations and years. Environmental conditions appeared to have a role in the stability of these relationships. Parameter estimates for I and A were incorporated into a second model to determine economic thresholds. On average, threshold values were between 4 and 5 S. cereale plants m−2; however, the large variation in these threshold values signifies considerable risk in making economic weed management decisions based upon these values.

Variation in crop–weed interference relationships has been shown for a number of crop–weed mixtures and may have an important influence on weed management decision-making. Field experiments were conducted at seven locations over 2 yr to evaluate variation in common lambsquarters interference in field corn and whether a single set of model parameters could be used to estimate corn grain yield loss throughout the northcentral United States. Two coefficients (I and A) of a rectangular hyperbola were estimated for each data set using nonlinear regression analysis. The I coefficient represents corn yield loss as weed density approaches zero, and A represents maximum percent yield loss. Estimates of both coefficients varied between years at Wisconsin, and I varied between years at Michigan. When locations with similar sample variances were combined, estimates of both I and A varied. Common lambsquarters interference caused the greatest corn yield reduction in Michigan (100%) and had the least effect in Minnesota, Nebraska, and Indiana (0% yield loss). Variation in I and A parameters resulted in variation in estimates of a single-year economic threshold (0.32 to 4.17 plants m−1 of row). Results of this study fail to support the use of a common yield loss–weed density function for all locations.

Three models that empirically predict crop yield from crop and weed density were evaluated for their fit to 30 data sets from multistate, multiyear winter wheat–jointed goatgrass interference experiments. The purpose of the evaluation was to identify which model would generally perform best for the prediction of yield (damage function) in a bioeconomic model and which model would best fulfill criteria for hypothesis testing with limited amounts of data. Seven criteria were used to assess the fit of the models to the data. Overall, Model 2 provided the best statistical description of the data. Model 2 regressions were most often statistically significant, as indicated by approximate F tests, explained the largest proportion of total variation about the mean, gave the smallest residual sum of squares, and returned residuals with random distribution more often than Models 1 and 3. Model 2 performed less well based on the remaining criteria. Model 3 outperformed Models 1 and 2 in the number of parameters estimated that were statistically significant. Model 1 outperformed Models 2 and 3 in the proportion of regressions that converged on a solution and more readily exhibited an asymptotic relationship between winter wheat yield and both winter wheat and jointed goatgrass density under the constraint of limited data. In contrast, Model 2 exhibited a relatively linear relationship between yield and crop density and little effect of increasing jointed goatgrass density on yield, thus overpredicting yield at high weed densities when data were scarce. Model 2 had statistical properties that made it superior for hypothesis testing; however, Model 1's properties were determined superior for the damage function in the winter wheat–jointed goatgrass bioeconomic model because it was less likely to cause bias in yield predictions based on data sets of minimum size.

Field experiments were conducted at five locations in Kansas, Nebraska, and Wyoming to determine the effects of imazamox rate and application timing on winter annual grass control and crop response in imidazolinone-tolerant winter wheat. Imazamox at 35, 44, or 53 g ai/ha applied early-fall postemergence (EFP), late-fall postemergence, early-spring postemergence (ESP), or late-spring postemergence (LSP) controlled jointed goatgrass at least 95% in all experiments. Feral rye control with imazamox was 95 to 99%, regardless of rate or application timing at Hays, KS, in 2001. Feral rye control at Sidney, NE, and Torrington, WY, was highest (78 to 85%) with imazamox at 44 or 53 g/ha. At Sidney and Torrington, feral rye control was greatest when imazamox was applied EFP. Imazamox stunted wheat <10% in two experiments at Torrington, but EFP or LSP herbicide treatments in the Sidney experiment and ESP or LSP treatments in two Hays experiments caused moderate (12 to 34%) wheat injury. Wheat injury increased as imazamox rate increased. Wheat receiving imazamox LSP yielded less grain than wheat treated at other application timings in each Hays experiment and at Sidney in 2001. No yield differences occurred in one Torrington experiment. However, yields generally decreased as imazamox application timing was delayed in the other Torrington experiment. Generally, imazamox applied in the fall provided the greatest weed control, caused the least wheat injury, and maximized wheat yield.

This paper reports two children who had mental retardation as the predominant manifestation of vein of Galen malformations. C.T. scans demonstrated extensive intracerebral calcification. Surgery reversed the progressive downhill course in one patient and may have arrested further deterioration in the other. The pathophysiological mechanisms underlying the clinical and radiographic features are discussed.

That non-rheumatic atrial fibrillation is an independent risk factor for cerebral infarction has not been established with certainty. The rationale underlying contemporary clinical trials of warfarin therapy for the prevention of stroke in patients who have non-rheumatic atrial fibrillation is that the majority of strokes in such patients are due to cardiogenic cerebral embolism. However, there is evidence to suggest that the increased probability of stroke attributed to this arrhythmia is due to its association with other risk factors such as hypertension, diabetes mellitus, and atherosclerosis. The question of who should be anticoagulated is a major public health issue since atrial fibrillation is present in approximately ten per cent of the general population aged 65 or more years.

A 39-year-old man presented with a pure motor stroke 9 days after cervical chiropractic manipulation. Computerised tomographic scanning showed a pontine infarct. Cerebral angiography showed changes consistent with the diagnosis of bilateral vertebral artery dissection. It is postulated that the infarct resulted from artery-to-artery embolism.