Triggers and maintenance of multiple shifts in the state of a natural community

Ecological communities can undergo sudden and dramatic shifts between alternative persistent community states. Both ecological prediction and natural resource management rely on understanding the mechanisms that trigger such shifts and maintain each state. Differentiating between potential mechanisms is difficult, however, because shifts are often recognized only in hindsight and many occur on such large spatial scales that manipulative experiments to test their causes are difficult or impossible. Here we use an approach that focuses first on identifying changes in environmental factors that could have triggered a given state change, and second on examining whether these changes were sustained (and thus potentially maintained the new state) or transitory (explaining the shift but not its persistence). We use this approach to evaluate a community shift in which a benthic marine species of filter feeding sea cucumber (Pachythyone rubra) suddenly came to dominate subtidal rocky reefs that had previously supported high abundances of macroalgae, persisted for more than a decade, then abruptly declined. We found that a sustained period without large wave events coincided with the shift to sea cucumber dominance, but that the sea cucumbers persisted even after the end of this low wave period, indicating that different mechanisms maintained the new community. Additionally, the period of sea cucumber dominance occurred when their predators were rare, and increases in the abundance of these predators coincided with the end of sea cucumber dominance. These results underscore the complex nature of regime shifts and illustrate that focusing separately on the causes and maintenance of state change can be a productive first step for analyzing these shifts in a range of systems

Current state of laparoscopic and robotic surgery

Minimally invasive surgical innovation has exploded in recent times. Currently, conventional laparoscopy is most widely adopted as the costs are relatively low. However, robotics and single port surgery are leading a revolution in surgery for wealthy health-care systems. We explore the historical and contemporary areas of this evolution

Approach to endoscopic extraperitoneal radical prostatectomy (EERPE): the impact of previous laparoscopic experience on the learning curve

BACKGROUND: We report our approach regarding the technique of endoscopic extraperitoneal radical prostatectomy (EERPE) and analyze the learning curve of two surgeons after thorough technical training under expert monitoring. The purpose of this study was to investigate the influence of expert monitoring on the surgical outcome and whether previous laparoscopic experience influences the surgeon's learning curve. METHODS: EERPE was performed on 120 consecutive patients by two surgeons with different experience in laparoscopy. An analysis and comparison of their learning curve was made. RESULTS: Median operation time: 200 (110-415) minutes. Complications: no conversion, blood transfusion (1.7%), rectal injury (3.3%). Median catheterisation time: 6 (5-45) days. Histopathological data: 55% pT2, 45% pT3 with a positive surgical margin rate of 6.1% and 46%, respectively. After 12 months, 78% of the patients were continent, 22% used 1 or more pad. Potency rate with or without PDE-5-inhibitors was 66% with bilateral and 31% with unilateral nerve-sparing, respectively. Operation time was the only parameter to differ significantly between the two surgeons. CONCLUSION: EERPE can be learned within a short teaching phase. Previous laparoscopic experience is reflected by shorter operation times, not by lower complication rates or superior early oncological data

Shifts in Attack Behavior of an Important Kelp Forest Predator Within Marine Reserves

Marine reserves have become increasingly valuable tools with which to manage ecosystems. These reserves consistently restore populations of top predators, often reducing availability of their favored prey. We hypothesized that such prey reduction in reserves causes protected predators to alter their attack behavior to include less palatable prey, potentially amplifying top-down effects on community structure. To test this hypothesis, we presented the relatively unpalatable sea hare Aplysia californica to freely foraging spiny lobsters Panulirus interruptus in 4 marine no-take reserves, each paired with an adjacent fished area. We found that lobsters only attacked sea hares inside reserves, where lobster density was significantly greater than that of the adjacent fished areas. Attacks on otherwise unpalatable prey exclusively in no-take reserves was likely caused by increased hunger, since in the laboratory only food-deprived lobsters attacked sea hares. These findings are the first to suggest that management involving no-take reserves may have unintended consequences on community structure that result from behavioral changes in key predators in the face of increased competition for food. We suspect that these effects may become more widely detected as reserves across the globe grow older and are researched further

Evidence for a general species time arearelationship

The species-area relationship (SAR) plays a central role in biodiversity research, and recent work has increased awareness of its temporal analog, the species-time relationship (STR). Here we provide evidence for a general species-time-area-relationship (STAR), in which species number is a function of the area and time span of sampling, as well as their interaction. For eight assemblages ranging from lake zooplankton to desert rodents, this model outperformed a sampling-based model and two simpler models in which area and time had independent effects. In every case the interaction term was negative, meaning that rates of species accumulation in space decreased with the time span of sampling, while species accumulation rates in time decreased with area sampled. Although questions remain about its precise functional form, the STAR provides a tool for scaling species richness across time and space, for comparing the relative rates of species turnover in space and time at different scales of sampling, and for rigorous testing of mechanisms proposed to drive community dynamics. Our results show that the SAR and STR are not separate relationships but two dimensions of one unified pattern. Keywords: community dynamics, spatiotemporal scaling, species diversity, turnover, speciesarea relationship, species-time relationshi

Analysis of Abrupt Transitions in Ecological Systems

The occurrence and causes of abrupt transitions, thresholds, or regime shifts between ecosystem states are of great concern and the likelihood of such transitions is increasing for many ecological systems. General understanding of abrupt transitions has been advanced by theory, but hindered by the lack of a common, accessible, and data-driven approach to characterizing them. We apply such an approach to 30–60 years of data on environmental drivers, biological responses, and associated evidence from pelagic ocean, coastal benthic, polar marine, and semi-arid grassland ecosystems. Our analyses revealed one case in which the response (krill abundance) linearly tracked abrupt changes in the driver (Pacific Decadal Oscillation), but abrupt transitions detected in the three other cases (sea cucumber abundance, penguin abundance, and black grama grass production) exhibited hysteretic relationships with drivers (wave intensity, sea-ice duration, and amounts of monsoonal rainfall, respectively) through a variety of response mechanisms. The use of a common approach across these case studies illustrates that: the utility of leading indicators is often limited and can depend on the abruptness of a transition relative to the lifespan of responsive organisms and observation intervals; information on spatiotemporal context is useful for comparing transitions; and ancillary information from associated experiments and observations aids interpretation of response-driver relationships. The understanding of abrupt transitions offered by this approach provides information that can be used to manage state changes and underscores the utility of long-term observations in multiple sentinel sites across a variety of ecosystems.Organismic and Evolutionary Biolog

Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management-Current Trends and Future Perspectives

Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention