Potential Misuse Research Articles

Investigation Into the Equine Metabolism of Phosphodiesterase‐4 Inhibitor Roflumilast for Potential Doping Control

ABSTRACTThe phosphodiesterase 4 (PDE4) inhibitors constitute a relatively modern class of medications that are known for inducing bronchodilation and exhibiting anti‐inflammatory properties within the body. Due to these properties, there is concern regarding their potential misuse as performance‐enhancing substances in competitive sports. This study delves into the metabolic conversion of roflumilast in thoroughbred horses following oral administration and in vitro experimentation using equine liver microsomes and Cunninghamella elegans. High‐performance liquid chromatography coupled with a Q Exactive Orbitrap mass spectrometer (HPLC‐HRMS) was employed for analysis. The investigation identified 10 metabolites of roflumilast, including six phase I and four phase II metabolites from in vivo studies, and 11 metabolites from in vitro studies, consisting of eight phase I and three phase II metabolites. The identified biotransformation products encompassed processes such as hydroxylation, chlorine substitution, methylation, N‐oxide formation, and even the dissociation of methylenecyclopropane and difluoromethane. Furthermore, the study identified three glucuronic acid and one sulfonic acid conjugated phase II metabolites of the investigated drug candidate. The aforementioned findings contribute to the detection and comprehension of the unauthorized utilization of roflumilast in equestrian sports.

Knowledge and perception of medical students on genetics in the genomic era.

The importance of medical genetics in modern healthcare underscores the urgent need for comprehensive genetics education for physicians. Such training should address both fundamental concepts and ethical considerations to bridge existing knowledge gaps and improve early diagnostic capabilities. In Latin America, the level of genetic knowledge among healthcare workers, particularly medical students, remains largely unexplored. This study evaluates the knowledge and attitudes toward genetic testing among final-year medical students at a public university in Monterrey, Mexico. Using a cross-sectional, observational, and anonymous survey design, the International Genetic Literacy and Attitudes Survey version 3 (iGLAS3) was administered from October 1, 2019, to August 16, 2020. This online survey collected demographic information, assessed genetic knowledge, and gauged opinions on genetic topics, focusing on items most relevant to our research objectives. Statistical analyses provided descriptive statistics and measures of central tendency. Of the 323 surveys distributed, 201 participants completed essential sections, revealing a moderate to high level of genetic knowledge, with an average score of 70 ± 11.5. The demographic profile included 58.7% women, 40.3% men, and 0.5% non-binary individuals, with an average participant age of 24years. A majority of participants expressed openness to genetic testing, primarily through private entities; however, significant concerns about the potential misuse of genetic data were noted. These findings underscore the necessity of enhancing genetic education and incorporating practical genetics training into medical curricula to meet the evolving challenges in this field effectively.

Authoritarian Surveillance and Public Support for Digital Governance Solutions

This study investigates factors influencing support for digital governance solutions and compares this support between autocracies and democracies. We conduct survey experiments in Russia, Germany, Turkey, the United States, and Estonia, and find that awareness of potential misuse of digital governance tools by the government reduces support. Importantly, while this effect has previously been documented for China, we find it irrespective of regime type for an autocracy, a hybrid regime and three democracies. Individuals relying on government-controlled information sources are more likely to endorse digital governance tools. Our study challenges prior findings by indicating that gaps in public service quality do not boost support. Instead, satisfaction with government services correlates with trust in the government’s capacity to implement digital governance solutions.

Dispensing of zolpidem and benzodiazepines in Brazilian private pharmacies: a retrospective cohort study from 2014 to 2021

ObjectiveThe study aimed to evaluate Zolpidem and Benzodiazepines prescription and dispensing data in private pharmacies in Brazil from 2014 to 2021. Methods: This retrospective cohort study was carried out with retrospective open data from the Brazilian Federal Government from January 2014 to August 2021 containing medicines registered in the National Controlled Products Management System (SNGPC).ResultsBetween January 2014 and August 2021, a total of 32,441,392 sales of thirteen drugs from the z-drug and benzodiazepine classes used to treat sleep disorders were recorded in Brazil. Throughout the entire period, clonazepam emerged as the most popular drug, accounting for 29.8% of total sales. Alprazolam followed in second place with 20.6% of sales, while zolpidem came in third with 14.4%. The normal-release form of zolpidem was consistently the highest-selling variant during the evaluation period. However, the fast-acting-release form exhibited the most significant growth, indicated by a noticeable upward trend in sales since 2020. In contrast, the extended-release form of zolpidem remained stable over the years.ConclusionThe increased sales of zolpidem in Brazilian private pharmacies raise concerns about potential misuse and dependence on this drug mainly for the treatment of insomnia. The epidemic of sleeping pills arises in a scenario of expectancy of short-term amelioration of symptoms, with no correspondence in best clinical practice. Education and counseling for both healthcare professionals and the general population are essential to address this growing health concern and ensure the safe and appropriate use of medications for sleep disorders.

Improving Organizational Performance by Creating an Instrument That Can Help Keep Misuse of Manager Power Under Control

Power misuse by managers in organizations is a wide-spread problem that has significant negative consequences for organizational performance. At the same time, published research on attempts of diagnosing power misuse is scarce. As such, organizations keep facing this problem without help from academia on handling it. The authors of this paper suggest addressing the issue by utilizing a regular survey with the purpose of diagnosing potential power misuse by supervising managers of an organization. The information collected via such a survey can be a powerful feedback instrument toward changing or continuing the state of affairs. Such a survey is developed in this paper. The survey has adequate face validity and Cronbach’s alpha reliability of 0.93. Furthermore, its criterion, convergent, external structure, and discriminant validity results indicate their good levels. Therefore, the survey may be recommended for use in the organizational setting. Utilization of this instrument can potentially lead to the increase of employee accomplishments, and the improvement of organization-wide performance.

DeepFake Image Detection: Fake Image Detection using CNNs and GANs Algorithm

Deep learning is a powerful and versatile technique that has seen extensive applications in areas such as natural language processing, machine learning, and computer vision. Among its most recent applications is the generation of deepfakes, which are high-quality, realistic altered videos or images that have garnered significant attention. While innovative uses of deepfake technology are being explored, its potential for misuse has raised serious concerns. Harmful applications, such as spreading fake news, creating celebrity pornography, financial fraud, and revenge pornography, have become increasingly prevalent in the digital age. As a result, public figures, including celebrities and politicians, face heightened risks from deepfake content. In response, substantial research has been conducted to explore the mechanics behind deepfakes, leading to the development of various deep learning-based algorithms for their detection. This study provides a comprehensive review of deepfake creation and detection techniques, focusing on different deep learning approaches. Additionally, it discusses the limitations of existing methods and the availability of datasets for research. The lack of a highly accurate and fully automated deepfake detection system presents a significant challenge as the ease of generating and distributing such content continues to grow. Nonetheless, recent efforts in deep learning have shown promising results, surpassing traditional detection methods.

Maintaining Integrity and Confidentiality of Patients’ Records Using an Enhanced Security Technique

Medical record storage on paper is currently being phased out and replaced by more sophisticated Electronic Health Record (EHR) systems. However, the ease of access to data and the digitization of medical records also come with the potential of misuse of personally identifiable information and healthcare data breaches. How technology will protect patient privacy is one of the primary concerns about EHRs. Network connectivity is another major issue, therefore keeping private health information online may expose it to major information leaks to external parties. Around the world, data management and privacy are major concerns. The main concerns that prevent businesses from using cloud computing are security and information authenticity, as they fear that data may be lost to unauthorized parties. The quantity of patient-oriented data in the healthcare system is continuously increasing, and the current medical systems are confronted with security issues such as weak access control, data breaches or unauthorized disclosure, and insufficient authorization and authentication. An Enhanced Security Model was created in this study to secure and protect Electronic Health Records. The records were encrypted for security and privacy utilizing the Advanced Encryption Standard (AES), One Time Password (OTP), and National Identity Number (NIN). The system was designed using Object Oriented Analysis and Design Methodology (OOADM). The New System improved patient record security by utilizing NIN for cloud identity management, OTP for authentication, and AES for privacy and security. While the MySQL server was used to implement the database, HTML, CSS, PHP, and JavaScript were used to program the system. Comparing the new system to the old system, the results of the performance assessment analysis based on security, user-friendliness, dependability, and privacy show that the new system has very good performance efficiency and integrity.

Multifactor Quality and Safety Analysis of Semaglutide Products Sold by Online Sellers Without a Prescription: Market Surveillance, Content Analysis, and Product Purchase Evaluation Study.

Over the past 4 decades, obesity has escalated into a global epidemic, with its worldwide prevalence nearly tripling. Pharmacological treatments have evolved with the recent development of glucagon-like peptide 1 agonists, such as semaglutide. However, off-label use of drugs such as Ozempic for cosmetic weight loss has surged in popularity, raising concerns about potential misuse and the emergence of substandard and falsified products in the unregulated supply chain. This study aims to conduct a multifactor investigation of product quality and patient safety risks associated with the unregulated online sale of semaglutide by examining product availability and vendor characteristics and assessing product quality through test purchases. We used a complex risk and quality assessment methodology combining online market surveillance, search engine results page analysis, website content assessment, domain traffic analytics, conducting targeted product test purchases, visual quality inspection of product packaging, microbiological sterility and endotoxin contamination evaluation, and quantitative sample analysis using liquid chromatography coupled with mass spectrometry. We collected and evaluated 1080 links from search engine results pages and identified 317 (29.35%) links belonging to online pharmacies, of which 183 (57.7%) led to legal pharmacies and 134 (42.3%) directed users to 59 unique illegal online pharmacy websites.Web traffic data for the period between July and September 2023 revealed that the top 30 domains directly or indirectly affiliated with illegal online pharmacies accumulated over 4.7 million visits.Test purchases were completed from6 illegal online pharmacies with the highest number of links offering semaglutide products for sale without prescription at the lowest price range. Three injection vial purchases were delivered; none of the 3 Ozempic prefilled injection pens were received due to nondelivery e-commerce scams.All purchased vials were considered probable substandard and falsified products, as visual inspection indicated noncompliance in more than half (59%-63%) of the evaluated criteria. The semaglutide content of samples substantially exceeded labeled amounts by 28.56%-38.69%, although no peptide-like impurities were identified. The lyophilized peptide samples were devoid of viable microorganisms at the time of testing; however, endotoxin was detected in all samples with levels ranging between 2.1645 EU/mg and 8.9511 EU/mg. Furthermore, the measured semaglutide purity was significantly low, ranging between 7.7% and 14.37% and deviating from the 99% claimed on product labels by manufacturers. Glucagon-like peptide 1 agonist drugs promoted for weight loss, similar to erectile dysfunction medications more than 2 decades ago, are becoming the new blockbuster lifestyle medications for the illegal online pharmacy market. Protecting the pharmaceutical supply chain from substandard and falsified weight loss products and raising awareness regarding online medication safety must be a public health priority for regulators and technology platforms alike.

The NIH Pain Common Data Elements: A Great Start but a Long Way to the Finish Line.

The NIH Pain Common Data Elements (CDEs) provide a standardized framework for pain research, but their implementation and interpretation present challenges. To review the NIH CDE Program's selected pain domains, provide best practices for implementing required questions, and offer a checklist for appropriate CDE use in clinical trials and secondary data analysis. This work analyzed the ten core pain research domains selected by the NIH CDE Program and discuss their limitations and considerations for use. The manuscript provides an overview of the ten core pain research domains, including pain intensity, interference, physical function, sleep, catastrophizing, depression, anxiety, global impression of change, substance use screening, and quality of life. It offers sample scenarios for implementing required questions and presents a checklist to guide researchers in using pain CDEs effectively for clinical trials and secondary data analysis. Key challenges identified include contextual variability, lack of validation across all pain conditions and populations, and potential misuse or misinterpretation of measures. This work proposes solutions such as supplementary measures, context-specific guidance, comprehensive training programs, and ongoing refinement of the CDE framework. While NIH Pain CDEs are valuable tools for standardizing pain assessment in research, addressing challenges in their implementation and interpretation is crucial for improving the consistency, validity, and interpretability of pain research data, ultimately advancing the field and enhancing patient care.

The Impact of Hate Speech Regulations on Freedom of Expression an Indonesian Legal Perspective

This paper explores the impact of hate speech regulation on freedom of expression in Indonesia from a juridical perspective. The study focuses on the legal framework, including the Electronic Information and Transactions Law (UU ITE) and the Indonesian Penal Code (KUHP), both of which are central to the regulation of hate speech. Through an analysis of key statutes, court rulings, and case studies, this paper highlights the tension between protecting public order and safeguarding free speech. The findings reveal that vague legal definitions and broad enforcement of hate speech laws have led to selective prosecution, often targeting political dissent and criticism. These issues raise concerns about the erosion of democratic rights and the potential misuse of hate speech laws for political purposes. Recommendations are provided to clarify legal definitions, ensure proportionality in enforcement, and prevent the misuse of these laws in a manner that balances the protection of social harmony with the preservation of freedom of expression.

Testing the capacity of Bard and ChatGPT for writing essays on ethical dilemmas: A cross-sectional study

Recent advancements in artificial intelligence (AI) have led to concerns about its potential misuse in education. As large language models (LLMs) such as ChatGPT and Bard can generate human-like text, researchers and educators noted the potential redundancy of tasking students with writing academic essays. We aimed to explore if the two LLMs could generate unstructured essays on medical students’ personal experiences of challenges and ethical dilemmas that are indistinguishable from human-written texts. We collected 47 original student-written essays from which we extracted keywords to develop prompts for the LLMs. We then used these prompts to generate an equivalent number of essays using ChatGPT and Bard. We analysed the essays using the Language Inquiry and Word Count (LIWC) 22 software, extracting the main LIWC summary measures and variables related to social and psychological processes. We also conducted sub-analyses for sixteen student essays that were presumably written entirely or in part by AI, according to two AI detectors. We found that AI-written essays used more language related to affect, authenticity, and analytical thinking compared to student-written essays after we removed AI-co-written student essays from the analysis. We observed that, despite the differences in language characteristics compared to student-written essays, both LLMs are highly effective in generating essays on students’ personal experiences and opinions regarding real-life ethical dilemmas.

Frequency and mechanism of injury for unintentional paediatric femoral fractures associated with consumer products over a 10-year period in the USA.

Femoral shaft fractures tend to be rare among children; however, these injuries are the most common major paediatric injuries treated by orthopaedic surgeons. The purpose of this study is to characterise the demographics and mechanisms of femoral injury associated with consumer products in the age group treated with spica casting, children 6 months to 6 years, to identify areas for injury prevention. Data from 2012 to 2021 were obtained from the National Electronic Injury Surveillance System maintained by the Consumer Products Safety Commission, documenting emergency department visits for unintentional injuries associated with consumer products. Narrative descriptions were analysed to identify common factors in the injury events such as location, products and mechanisms of action. From 2012 to 2021, the estimated incidence of femur fractures was 23.5 cases per 100 000 children with no significant difference in yearly frequency. The most common mechanism of injury was a fall with the most frequent fracture sources being bed/bunk beds (16.1%), floor (slips/falls, 9.7%) and trampolines (9.7%). Most fractures occurred at the patient's home (58.4%). The incidence of injury outside of the home and frequency of fractures involving play structures/trampolines increased with age. The incidence and demographic characteristics of paediatric femur fractures associated with consumer products have remained consistent over the past 10 years. As home was the most common location of fracture, prevention of femur fractures should focus on caregiver education around high-risk sources of fracture (bed, stairs and trampolines) and manufacturers should consider design alternatives that discourage potential misuse.

Review of Guidelines on Bupropion for Depression

What Is the Issue? Bupropion is a drug used in the treatment of depression. Bupropion is 1 of many treatment options available for depression and is associated with several side effects as well as the potential for misuse. Some patients continue to experience symptoms of depression despite trying multiple medications (known as treatment-resistant depression). Therefore, it is important to determine the place in therapy of bupropion for the treatment of depression. What Did We Do? To help determine the potential place in therapy for bupropion for the treatment of major depressive disorder (MDD) and treatment-resistant depression in adults, we sought to identify and summarize recommendations in evidence-based guidelines. We searched key resources, including journal citation databases, and conducted a focused internet search for relevant evidence published since 2019. One reviewer screened articles for inclusion based on predefined criteria, critically appraised the included publications, and narratively summarized the findings. What Did We Find? We identified 4 evidence-based guidelines that included recommendations on the use of bupropion for MDD. We identified 1 evidence-based guideline that included a recommendation on the use of bupropion for difficult-to-treat depression (defined as persistent depression despite several standard treatments). All 4 included guidelines recommend bupropion for the treatment of adults with MDD. Two of the guidelines recommend bupropion as a first-line treatment option. One guideline suggests bupropion as an option for initial pharmacologic treatment or for patients who have previously responded well to pharmacotherapy. One guideline suggests bupropion as an option for adjunctive treatment for patients in the acute phase of moderate to severe MDD who did not respond to treatment with a second-generation antidepressant. One guideline suggests bupropion as a second-line adjunctive option for adults with difficult-to-treat depression. What Does It Mean? The included evidence-based guidelines consistently recommend bupropion as an option for the treatment of adults with MDD. Additional factors such as the availability of other options, costs, and patient preferences may also be important to decision-making around the use of bupropion for MDD. Only 1 of the included guidelines included a recommendation on the use of bupropion for patients with difficult-to-treat depression. Future evidence-based guidelines that include recommendations on the use of bupropion for treatment-resistant depression would help fill the gaps identified in this report.

Effect of sacubitril/valsartan and dapagliflozin on athletic performance; can the popular cardiac medications of recent years be used as doping agents?

Abstract Background/Introduction Recent guidelines have highlighted the positive impacts of sacubitril/valsartan and dapagliflozin on heart failure management [1]. Given their potential misuse as doping agents in professional sports, this study evaluates their effects on athletic performance. Purpose To investigate the effects of sacubitril/valsartan and dapagliflozin on athletic performance and cardiac functions in a rodent model. Methods The study had a randomized double-blind design. 24 Sprague-Dawley male rats aged 4 months, divided into control, sacubitril/valsartan, and dapagliflozin groups. The rats were weighed at the start of the experiment. The medications (dapagliflozin 1,5 mg/kg/1 ml/once a day, sacubitril/valsartan 60 mg/kg/1 ml/once a day to their respective groups, and normal saline for control group) were administered via gastric gavage for 30 days. The rats were weighed, examined with transthoracic echocardiography and put on rotarod at the start of the experiment, and on 15th and 30th days. The rats were put on forced swimming tests for 20 days. Exhaustion, loss of coordinated movements and failure to surface for 3 seconds after submersion in the water were defined as indications for ending the test as per the guidelines regarding rat exercise testing [2]. M-mode and Doppler measurements, forced swimming test durations, rotarod durations and weight were recorded on 0th, 15th and 30th days. Results Initial performance metrics, including echocardiography, weight, and rotarod tests, showed no significant differences among the groups at baseline. The distributions in data were non-normal. Over the course of the study, median swimming times significantly differed from the 9th session, with dapagliflozin-treated rats exhibiting a substantial increase in endurance. Specifically, dapagliflozin group's swimming times increased to a median of 3580 seconds by the 20th session, compared to 2382 seconds in the control group and 2591 seconds in the sacubitril/valsartan group, indicating a pronounced improvement in exercise capacity (P<0.0001)(Figure-1). Echocardiographic assessments revealed enhanced cardiac output and ejection fraction, particularly in the sacubitril/valsartan group, suggesting increased cardiac efficiency and potential athletic performance enhancement. Conclusion(s) The study demonstrates a significant improvement in athletic performance with dapagliflozin compared to sacubitril/valsartan. These findings suggest a potential for misuse in sports doping, emphasizing the need for stringent regulation and monitoring within competitive athletics.Figure-1

An Early Snapshot of Attitudes Toward Generative Artificial Intelligence in Physical Therapy Education

Introduction. Generative artificial intelligence (AI) is rapidly gaining popularity across health care, education, and society. The purpose of this study was to assess perceptions and use of generative AI in academic physical therapy (PT). Review of Literature. Generative AI became one of the fastest-growing technologies ever after the public release of ChatGPT in November 2022. Early data indicate that attitudes toward generative AI in higher education are mixed and rapidly evolving, with significant ethical concerns around use and potential misuse. There are no published studies investigating perceptions and use of generative AI in PT education. Subjects. A total of 175 surveys were completed and analyzed. Respondents included PT educators, administrators, and students. Methods. An anonymous, online survey on use and perception of AI was distributed through email and social media. Descriptive statistics and cross-tabulations were performed to analyze respondent characteristics and responses to survey questions. Results. Most respondents (61.1%) reported they did not use generative AI during the 2022-2023 academic year, whereas 35.4% were generative AI users. More than 40% of respondents were optimistic or very optimistic toward generative AI. Users of AI were more likely to report an optimistic or very optimistic disposition toward AI compared with nonusers. AI users were more likely to agree or completely agree that generative AI has more benefits than drawbacks compared with nonusers. Discussion and Conclusion. Results of this survey suggest that, despite the rapid uptake of generative AI in society, many PT educators and students harbor reservations and uncertainties toward its use. Artificial intelligence users were less likely to hold negative perceptions toward it and were more likely to find it useful. Understanding use and perceptions of generative AI in PT education may inform strategies to promote innovation, policy-making, and ethical integration of this new and rapidly evolving technology.

Neurorights in the Constitution: from neurotechnology to ethics and politics.

Neuroimaging technologies such as brain-computer interfaces and neurofeedback have evolved rapidly as new tools for cognitive neuroscience and as potential clinical interventions. However, along with these developments, concern has grown based on the fear of the potential misuse of neurotechnology. In October 2021, Chile became the first country to include neurorights in its Constitution. The present article is divided into two parts. In the first section, we describe the path followed by neurorights that led to its inclusion in the Chilean Constitution, and the neurotechnologies usually involved in neurorights discussions. In the second part, we discuss two potential problems of neurorights. We begin by pointing out some epistemological concerns regarding neurorights, mainly referring to the ambiguity of the concepts used in neurolegislations, the difficult relationship between neuroscience and politics and the weak reasons for urgency in legislating. We then describe the dangers of overprotective laws in medical research, based on the detrimental effect of recent legislation in Chile and the potential risk posed by neurorights to the benefits of neuroscience development. This article aims to engage with the scientific community interested in neurotechnology and neurorights in an interdisciplinary reflection of the potential consequences of neurorights.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

A Hybrid Approach for Intrusion Detection by Dragonfly Optimization and Bayesian Neural Network Methodologies

The technique of keeping an eye out for malicious activity or policy violations on a computer network or system is known as intrusion detection. It entails examining system logs, network traffic, and other data sources to spot potential security breaches, misuse, and illegal access. Network-based and host-based intrusion detection systems (IDS) are the two types available. The former analyzes network traffic and packets, while the latter concentrates on specific hosts or devices. This paper investigates how to improve intrusion detection systems in cyber security by combining dragonfly optimization (DFO) and Bayesian neural network (BNN) methodologies. The NSL-KDD dataset, which is tested and trained in the system, is the source of the dataset used in the study. By utilizing the optimization skills of DFO and the probabilistic reasoning powers of BNN, the hybrid technique improves the accuracy and flexibility of detecting and addressing network intrusions. This research illustrates the effectiveness of the suggested methodology in navigating dynamic network environments and identifying emerging dangers through a thorough examination. In addition to improving detection performance, the integration of BNN and DFO gives enterprises insightful information about infiltration patterns and the ability to take proactive measures to thwart hostile activity. The created model's enhanced intrusion detection performance is demonstrated by the experimental findings. These results are validated in terms of accuracy, precision, recall, execution time, and F1 score by comparing them with models that are currently in use.

Driving performance and ocular activity following acute administration of 10 mg methylphenidate: A randomised, double-blind, placebo-controlled study.

Methylphenidate is a routinely prescribed treatment for attention-deficit/hyperactivity disorder with misuse potential owing to its perceived performance-enhancing and euphoric properties. Although clinically effective, there is limited understanding of how methylphenidate affects safety-sensitive tasks such as driving when used by healthy individuals. Explore the acute effects of 10 mg methylphenidate on driving performance and gaze behaviour. Twenty-five fully licensed, healthy adults (mean age = 33.5 ± 7.8 years, 64% male) took part in two 40-min simulated highway drives with simultaneous eye movements monitored using a proprietary automotive-grade driver monitoring system (Seeing Machines). Driving performance was assessed using the standard deviation of lateral position, standard deviation of speed and steering variability. Visual scanning efficiency was determined using ocular metrics, such as fixation duration and rate, gaze transition entropy, and stationary gaze entropy, were assessed to determine visual scanning efficiency. Methylphenidate significantly improved driving performance by reducing lane weaving and speed variation, particularly in the latter half of the drive. Although a significant reduction in fixation duration was observed, all other ocular metrics remained unchanged. Methylphenidate mitigates performance decrements typically associated with prolonged and monotonous driving. The absence of pronounced oculomotor effects suggests that a single 10 mg dose of methylphenidate has no deleterious impact on visual scanning behaviour during driving tasks with low-to-moderate cognitive demand. Future research should investigate the effects of methylphenidate under various dosing and driving conditions to better understand its impact. ACTRN12620000499987.

Simultaneous detection of myostatin-targeting monoclonal antibodies in dried blood spots and plasma using liquid chromatography-tandem mass spectrometry with field asymmetric ion mobility spectrometry

Transforming growth factor-β superfamily members, such as myostatin, growth/differentiation factor 11, and activin A, negatively regulate skeletal muscle mass. Inhibitors targeting these cytokines or activin receptor type IIB have the potential to treat muscular diseases and enhance physical performance. However, because of their effects on muscle mass and potential misuse, they are strictly prohibited in sports. Given the high potential for misuse as a doping agent in sports, effective analytical methods for these prohibited antibodies targeting these specific cytokines or their receptor are critically needed. In this study, we aimed to develop and validate a multitarget method to detect the prohibited transforming growth factor-β superfamily-targeting monoclonal antibodies, such as landogrozumab, domagrozumab, and the activin receptor type IIB-targeting antibody, bimagrumab, in human plasma and dried blood spot (DBS) samples using liquid chromatography-tandem mass spectrometry. Antibodies were purified from both the DBS and plasma samples using protein G magnetic beads and field-asymmetric ion mobility spectrometry (FAIMS) to minimize interference, followed by liquid chromatography-tandem mass spectrometry analysis. The validation process included tests for specificity, selectivity, linearity, limit of detection (LOD), limit of identification, precision, recovery, carryover effect, and matrix effect. The LODs for the target antibodies were identical in both DBS and plasma samples at 0.1 µg/mL for landogrozumab heavy and light chains, as well as 0.25 µg/mL for the domagrozumab light chain and 0.25 µg/mL for the bimagrumab heavy chain. However, the heavy chain of domagrozumab exhibited an LOD of 0.5 µg/mL in DBS and 1 µg/mL in plasma. The analytical method demonstrated strong linearity, with R² values greater than 0.99 for both plasma and DBS, and no carryover effect. Precision (CV%) was below 15 % at both middle (1 or 5 µg/mL; specific to the heavy chain of domagrozumab in plasma) and high (10 µg/mL) concentrations and was less than 20 % at the LOD. The selectivity and specificity indicated no interference in the analysis of target mAbs in different blood samples. Recovery was 31.6–49.8 % for DBS and 51.4–85.3 % for plasma, with no significant matrix effect. This study provides an effective method for doping analysis and novel protein detection.

Legal Perspective on Consumer Personal Data Protection in Fintech Services

The development of science and technology has significantly affected the financial transaction system in Indonesia, especially with the emergence of the Fintech business model. The rapid growth of Fintech indicates the need for smart management in order to provide optimal benefits to society. However, the potential misuse of consumers' personal data poses a risk that needs to be considered. This research uses a normative juridical and analytical descriptive approach to understand the legal dynamics in the Fintech industry and legal measures aimed at Safeguarding user data security in Indonesia, in accordance with the provisions of Financial Services Authority Regulation Number 13/Pojk.02/2018. The results show that Fintech business organizers and users have a relationship that is regulated through an electronic agreement. The legal safeguarding of personal data for Fintech user is governed by Financial Services Authority Regulation Number 1/Pojk.07/2013 and other pertinent regulations, addressing aspects such as confidentiality, data security, and the governance and risk management of information technology.