Adam Khan

In the shadowy realm of cybercrime, DarkBard has emerged as a significant player, representing a crossover into non-OpenAI territory. As its name suggests, DarkBard is modeled as the dark counterpart to Google's Bard artificial intelligence (AI). This tool surfaced in mid-2023, riding the same wave that brought other malicious AI tools like FraudGPT and WormGPT to prominence. Notably, the cybercriminal seller known as “CanadianKingpin,” who launched FraudGPT, also advertised DarkBard on dark web forums and Telegram channels.

Cyberattackers are using generative AI to draft polished spam, create malicious code and write persuasive phishing lures.

Background Regional anesthesia (RA) is central to multimodal analgesia, yet many supporting randomized controlled trials (RCTs) may lack the rigor needed for evidence-based block selection.Objectives To evaluate the clinical usefulness and transparency of RCTs investigating RA interventions for lower extremity surgeries, using the van ’t Hooft et al framework.Methods Embase/MEDLINE were searched for RCTs (2014–2024) examining RA interventions for lower-extremity surgery. Data were extracted in duplicate using clinical-utility and transparency criteria. Analyses included descriptive statistics, linear regression for temporal trends, Pearson correlation, and multivariable regression to identify predictors of usefulness.Results Among 248 RCTs, patient-centeredness was universal, while feasibility (77.0%) and context placement (77.4%) were common. Pragmatism (2.0%) and value-for-money analyses (0%) were rare. Transparency varied: conflicts of interest were disclosed in 88.7%, pre-registration occurred in 39.9%, public protocols in 10.1%, and raw-data sharing in 1.2%. Transparency improved over time, correlated with clinical-utility scores (r=0.32, p<0.001) and was greater in hospital-funded, self-funded, and higher-impact journals.Limitations Usefulness scoring involves subjective judgment; non-English trials were excluded; the absence of formal risk of bias analysis limits interpretability of trial quality.Discussions/conclusions Although transparency is improving, most trials remain insufficiently pragmatic, lack economic evaluation, and rarely share data, limiting real-world applicability. The results of this study suggest that aligning funder, journal, and collaborative expectations around open science and pragmatic design could accelerate the generation of high-utility evidence for perioperative block selection.

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COMMENTARY: “Look for spelling mistakes and bad grammar .” For years, that was one of the defining pieces of advice for spotting phishing attempts.