In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Ex Input:
Scorpions are well known for their dangerous stings that can result in severe consequences for human beings, including death. Neurotoxins present in their venoms are responsible for their toxicity. Due to their medical relevance, toxins have been the driving force in the scorpion natural compounds research field. On the other hand, for thousands of years, scorpions and their venoms have been applied in traditional medicine, mainly in Asia and Africa. With the remarkable growth in the number of characterized scorpion venom components, several drug candidates have been found with the potential to tackle many of the emerging global medical threats. Scorpions have become a valuable source of biologically active molecules, from novel antibiotics to potential anticancer therapeutics. Other venom components have drawn attention as useful scaffolds for the development of drugs. This review summarizes the most promising candidates for drug development that have been isolated from scorpion venoms.

Ex Output:
Scorpion venom components as potential candidates for drug development

Ex Input:
Background: Nurses leaving their jobs and the profession are an issue of international concern, with supplydemand gaps for nurses reported to be widening. There is a large body of existing literature, much of which is already in review form. In order to advance the usefulness of the literature for nurse and human resource managers, we undertook an overview (review of systematic reviews). The aim of the overview was to identify high quality evidence of the determinants and consequences of turnover in adult nursing. Methods: Reviews were identified which were published between 1990 and January 2015 in English using electronic databases (the Cochrane Database of Systematic Reviews, MEDLINE, EMBASE, Applied Social Sciences Index and Abstracts, CINAHL plus and SCOPUS) and forward searching. All stages of the review were conducted in parallel by two reviewers. Reviews were quality appraised using the Assessment of Multiple Systematic Reviews and their findings narratively synthesised. Results: Nine reviews were included. We found that the current evidence is incomplete and has a number of important limitations. However, a body of moderate quality review evidence does exist giving a picture of multiple determinants of turnover in adult nursing, with -at the individual level -nurse stress and dissatisfaction being important factors and -at the organisational level -managerial style and supervisory support factors holding most weight. The consequences of turnover are only described in economic terms, but are considered significant. In making a quality assessment of the review as well as considering the quality of the included primary studies and specificity in the outcomes they measure, the overview found that the evidence is not as definitive as previously presented from individual reviews. Further research is required, of rigorous research design, whether quantitative or qualitative, particularly against the outcome of actual turnover as opposed to intention to leave.

Ex Output:
The determinants and consequences of adult nursing staff turnover: a systematic review of systematic reviews

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Ecological niche modeling (ENM) is widely employed in ecology to predict species' potential geographic distributions in relation to their environmental constraints and is rapidly becoming the gold-standard method for disease risk mapping. However, given the biological complexity of disease systems, the traditional ENM framework requires reevaluation. We provide an overview of the application of ENM to disease systems and propose a theoretical framework based on the biological properties of both hosts and parasites to produce reliable outputs resembling disease system distributions. Additionally, we discuss the differences between biological considerations when implementing ENM for distributional ecology and epidemiology. This new framework will help the field of disease ecology and applications of biogeography in the epidemiology of infectious diseases. The recent rise of emerging infectious diseases (EIDs) (see Glossary) [1] has increased the burden of infectious diseases and negatively impacted the global economy [2][3][4] [5] . Approximately 60% of emerging human diseases are caused by pathogenic parasites of animal origin (zoonoses), particularly wildlife [6] . As human activities intensify, contact with wildlife and exposure to novel parasites increase, potentially driving zoonotic disease emergence [1, 7] . Given the threat that EIDs pose to human populations, understanding the underlying drivers of parasite geographic distribution and their spillover to humans is particularly relevant for epidemiologists, public-health practitioners, and policy makers [9] . Ecological niche modeling (ENM) has proven useful to forecast the distribution of a vast number of organisms [10-13] and is increasingly employed to predict parasite distributions locally and globally [14] [15] [16] [17] . Despite great strides made in the implementation of ENM to forecast complex biological phenomena such as disease systems [18], traditional frameworks may render biologically unrealistic predictions and thus must be revised, as we show in this review. We provide an overview of the current state of disease ENM and propose a framework based on the biological properties of both parasites and hosts to produce reliable outputs resembling disease systems distributions. Specifically, our theoretical framework: (i) addresses the selection of an appropriate modeling approach and highlights the importance of including biologically sound predictor variables; (ii) proposes the concept of a microscale parasitic niche defined by host traits to identify relevant parasite-host associations; and (iii) integrates traditional parasite ENM with the proposed microscale niche to better understand geographic distributions and improve fine-scale predictions of disease transmission risk. ENM estimates the distributions of species by linking their geographic occurrence with their environmental constraints, often utilizing correlative approaches (detailed explanations in [18] ). Highlights

Ex Output:
An Ecological Framework for Modeling the Geography of Disease Transmission