Evaluation of in Vitro Antioxidant Activity and L Asparaginase Enzyme Production of Four Endophytic Fungi Isolated from Acanthus Ilicifolius

The need for novel and useful bioactive secondary metabolites to help and relieve people from all aspects of human conditions is constantly expanding. Every plant tissue has a variety of endophytic fungi, which are thought to be highly effective producers of natural products. In this work, the determination of total phenolics, antioxidants, and L-asparaginase enzyme activity in four fungal endophytes associated with the mangrove plant Acanthus ilicifolius was evaluated. The study indicated that total phenolic content (1633+8.7 μg equivalent to gallic acid) and reducing power (0.96) were the highest for methanolic extracts of the isolate Aspergillus terreus while scavenging activity was highest for the isolate Colletotrichum xishuangbannaense (78.2+4.5 %). The enzyme activity of L-asparaginase was expressed predominantly by all the isolates except Colletotrichum xishuangbannaense. Maximum enzyme activities of 50.1 U/mL, 48.1 U/mL, and 47.7 U/mL were observed in Aspergillus terreus, Colletotrichum cobbiƫense, and Fusarium multiceps respectively. The current research demonstrated that mangrove-associated fungi have a high potential for producing bioactive molecules and L-asparaginase, which can be used as a possible source for the creation of anticancer drugs

From Text to MITRE Techniques: Exploring the Malicious Use of Large Language Models for Generating Cyber Attack Payloads

This research article critically examines the potential risks and implications arising from the malicious utilization of large language models(LLM), focusing specifically on ChatGPT and Google's Bard. Although these large language models have numerous beneficial applications, the misuse of this technology by cybercriminals for creating offensive payloads and tools is a significant concern. In this study, we systematically generated implementable code for the top-10 MITRE Techniques prevalent in 2022, utilizing ChatGPT, and conduct a comparative analysis of its performance with Google's Bard. Our experimentation reveals that ChatGPT has the potential to enable attackers to accelerate the operation of more targeted and sophisticated attacks. Additionally, the technology provides amateur attackers with more capabilities to perform a wide range of attacks and empowers script kiddies to develop customized tools that contribute to the acceleration of cybercrime. Furthermore, LLMs significantly benefits malware authors, particularly ransomware gangs, in generating sophisticated variants of wiper and ransomware attacks with ease. On a positive note, our study also highlights how offensive security researchers and pentesters can make use of LLMs to simulate realistic attack scenarios, identify potential vulnerabilities, and better protect organizations. Overall, we conclude by emphasizing the need for increased vigilance in mitigating the risks associated with LLMs. This includes implementing robust security measures, increasing awareness and education around the potential risks of this technology, and collaborating with security experts to stay ahead of emerging threats

The role of neuropeptides in adverse myocardial remodeling and heart failure

In addition to traditional neurotransmitters of the sympathetic and parasympathetic nervous systems, the heart also contains numerous neuropeptides. These neuropeptides not only modulate the effects of neurotransmitters, but also have independent effects on cardiac function. While in most cases the physiological actions of these neuropeptides are well defined, their contributions to cardiac pathology are less appreciated. Some neuropeptides are cardioprotective, some promote adverse cardiac remodeling and heart failure, and in the case of others their functions are unclear. Some have both cardioprotective and adverse effects depending on the specific cardiac pathology and progression of that pathology. In this review, we briefly describe the actions of several neuropeptides on normal cardiac physiology, before describing in more detail their role in adverse cardiac remodeling and heart failure. It is our goal to bring more focus toward understanding the contribution of neuropeptides to the pathogenesis of heart failure, and to consider them as potential therapeutic targets

Formal methods for analyzing the completeness of an assertion suite against a high-level fault model

One of the emerging challenges in formal property verification (FPV) technology is the problem of deciding whether sufficient properties have been written to cover the design intent. Existing literature on FPV coverage does not solve this problem adequately, since they primarily analyze the coverage of a specification against a given implementation. On the other hand, we consider the task of determining the coverage of a formal specification against a high-level fault model that is independent of any specific implementation. We show that such a coverage analysis discovers behavioral gaps in the specification and prompts the design architect to add more properties to close the behavioral gaps. Our results establish that the coverage analysis task at this level is computationally complex, but it is possible to obtain a conservative estimate of the coverage at low cost

Student understanding of the critical features of an hypothesis: variation across epistemic and heuristic dimensions

The higher education sector is now focussed on the task of creating graduates who are able to deal with the novel, complex, unstructured problems they will encounter in the 21st century workforce (Brew, 2010). Within science, the central role of hypothetico-deductive reasoning in ‘thinking like a scientist’ is well established (Dunbar and Fugelsang, 2005), and in bioscience education, understanding ‘testable hypotheses’ has become a threshold concept (Taylor and Meyer, 2010) and a key driver of curriculum transformation (Elliot et al., 2010). From a large database of responses provided by undergraduate biology students to the question “What is a hypothesis?” Taylor et al. (2011) developed a forty seven item psychometric instrument capturing variation in student understanding of this threshold concept. A version of this instrument has now been trialled with eight hundred undergraduate science students enrolled in a first year, second semester biology course. Exploratory factor analysis of their responses has revealed five factors which vary along dimensions of epistemic maturity and understanding of disciplinary heuristics. These factors are interpreted as representing the initial 'critical features' of the threshold concept as it 'comes into view'. Specifically, students were found to conceptualise hypotheses most simplistically as based on facts, or hold more advanced conceptions about the predictive utility of hypotheses (indicating an awareness of hypothetico-predictive reasoning) and to hypotheses as testable statements (indicating an awareness of hypothetico-deductive reasoning) used in the development of new scientific knowledge. Further, student conceptions varied on the role of observations, experiments and controlling variables in judging the validity of hypotheses. This snapshot characterises the conceptions about hypothesis held by early stage undergraduate science students, providing insights into the ways students are beginning to understand the heuristics used to judge the evidence that builds scientific knowledge in their discipline, as they embark on the journey toward thinking like a scientist