Are current dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

Catchment-scale water quality models are becoming increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we have developed a parsimonious P model, SimplyP, incorporating a coupled rainfall-runoff model and a biogeochemical model able to simulate streamflow, suspended sediment, particulate and dissolved P dynamics. The model’s complexity is compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP model parameters must be determined through calibration alone, the rest may be based on measurements; INCA-P has around 40 unmeasurable parameters. Despite simpler process-representation, SimplyP produced a slightly better dissolved P simulation during both calibration and validation, and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate amongst the water quality modelling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated

Precise Regulation of Gene Expression Dynamics Favors Complex Promoter Architectures

Promoters process signals through recruitment of transcription factors and RNA polymerase, and dynamic changes in promoter activity constitute a major noise source in gene expression. However, it is barely understood how complex promoter architectures determine key features of promoter dynamics. Here, we employ prototypical promoters of yeast ribosomal protein genes as well as simplified versions thereof to analyze the relations among promoter design, complexity, and function. These promoters combine the action of a general regulatory factor with that of specific transcription factors, a common motif of many eukaryotic promoters. By comprehensively analyzing stationary and dynamic promoter properties, this model-based approach enables us to pinpoint the structural characteristics underlying the observed behavior. Functional tradeoffs impose constraints on the promoter architecture of ribosomal protein genes. We find that a stable scaffold in the natural design results in low transcriptional noise and strong co-regulation of target genes in the presence of gene silencing. This configuration also exhibits superior shut-off properties, and it can serve as a tunable switch in living cells. Model validation with independent experimental data suggests that the models are sufficiently realistic. When combined, our results offer a mechanistic explanation for why specific factors are associated with low protein noise in vivo. Many of these findings hold for a broad range of model parameters and likely apply to other eukaryotic promoters of similar structure

Multisensory visual–tactile object related network in humans: insights gained using a novel crossmodal adaptation approach

Neuroimaging techniques have provided ample evidence for multisensory integration in humans. However, it is not clear whether this integration occurs at the neuronal level or whether it reflects areal convergence without such integration. To examine this issue as regards visuo-tactile object integration we used the repetition suppression effect, also known as the fMRI-based adaptation paradigm (fMR-A). Under some assumptions, fMR-A can tag specific neuronal populations within an area and investigate their characteristics. This technique has been used extensively in unisensory studies. Here we applied it for the first time to study multisensory integration and identified a network of occipital (LOtv and calcarine sulcus), parietal (aIPS), and prefrontal (precentral sulcus and the insula) areas all showing a clear crossmodal repetition suppression effect. These results provide a crucial first insight into the neuronal basis of visuo-haptic integration of objects in humans and highlight the power of using fMR-A to study multisensory integration using non-invasinve neuroimaging techniques

The Effects of Context and Presentation Rate on the First 200 msec of Word Recognition

We used Electroencephalography (EEG) to investigate whether context‐modulated lexical access occurs within the first 200 msec of stimulus onset. We employed two different presentation rates to investigate whether earlier effects (P130 and N170) as well as later effects (N400 and P600) are modulated by the rate of presentation of stimuli. Subjects read contextually supported controls, contextually supported pseudowords, contextually unsupported pseudowords, and nonwords (e.g., She measured the flour so she could bake a cake/ceke/fash/srdt), which were presented between subjects at either a fast rate (word appeared on screen for 200 msec followed by a 175 msec blank screen) or a slow rate (word appeared on screen for 200 msec followed by a 350 msec blank screen). We predicted that the supported pseudoword would have the earliest and largest effect, followed by the nonword and unsupported pseudoword. Our predictions were supported numerically but not statistically. We observed that presentation rate clearly modulated the N400 effect. Subjects who saw the fast presentation rate had a more negative N400 for nonwords compared to subjects who saw the slow presentation rate; however, this effect was nonsignificant as well. Although we found no significant effects, numerically our results support our hypothesis that context modulates lexical access prior to 200 msec and presentation rate can modulate word recognition effects

Tailored Treatment Options for Cerebral Cavernous Malformations

The diagnosis and treatment of cerebral cavernous malformations (CCMs), or cavernomas, continues to evolve as more data and treatment modalities become available. Intervention is necessary when a lesion causes symptomatic neurologic deficits, seizures, or has high risk of continued hemorrhage. Future medical treatment directions may specifically target the pathogenesis of these lesions. This review highlights the importance of individualized treatment plans based on specific CCM characteristics

Untangling the Modern Treatment Paradigm for Unruptured Brain Arteriovenous Malformations

Brain arteriovenous malformations (AVMs) often present treatment challenges. Patients with unruptured AVMs must consider not only whether they want to be treated, but what treatment modality they would prefer. Vascular neurosurgeons, neurointerventional surgeons, and stereotactic radiosurgeons must in turn guide their patients through the most appropriate treatment course considering the risk of AVM rupture, an individual AVM’s characteristics, and patient preferences. In this review we will look at how the clinical trial “A Randomized Trial of Unruptured Brain Arteriovenous Malformations (ARUBA)” has influenced the approach to unruptured brain AVMs and the treatment modalities available to clinicians to deal with these formidable lesions