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In this study, we introduce a framework designed to help educators assess the effectiveness of popular generative artificial intelligence (AI) tools in solving authentic assessments. We employed Bloom's taxonomy as a guiding principle to create authentic assessments that evaluate the capabilities of generative AI tools. We applied this framework to assess the abilities of ChatGPT-4, ChatGPT-3.5, Google Bard and Microsoft Bing in solving authentic assessments in economics. We found that generative AI tools perform very well at the lower levels of Bloom's taxonomy while still maintaining a decent level of performance at the higher levels, with "create" being the weakest level of performance. Interestingly, these tools are better able to address numeric-based questions than text-based ones. Moreover, all the generative AI tools exhibit weaknesses in building arguments based on theoretical frameworks, maintaining the coherence of different arguments and providing appropriate references. Our study provides educators with a framework to assess the capabilities of generative AI tools, enabling them to make more informed decisions regarding assessments and learning activities. Our findings demand a strategic reimagining of educational goals and assessments, emphasising higher cognitive skills and calling for a concerted effort to enhance the capabilities of educators in preparing students for a rapidly transforming professional environment.

In recent years, single-channel physiological recordings have gained popularity in portable health devices and research settings due to their convenience. However, the presence of electrooculogram (EOG) artifacts can significantly degrade the quality of the recorded data, impacting the accuracy of essential signal features. Consequently, artifact removal from physiological signals is a crucial step in signal processing pipelines. Current techniques often employ Independent Component Analysis (ICA) to efficiently separate signal and artifact sources in multichannel recordings. However, limitations arise when dealing with single or a few channel measurements in minimal instrumentation or portable devices, restricting the utility of ICA. To address this challenge, this paper introduces an innovative artifact removal algorithm utilizing enhanced empirical mode decomposition to extract the intrinsic mode functions (IMFs). Subsequently, the algorithm targets the removal of segments related to EOG by isolating them within these IMFs. The proposed method is compared with existing single-channel EEG artifact removal algorithms, demonstrating superior performance. The findings demonstrate the effectiveness of our approach in isolating artifact components, resulting in a reconstructed signal characterized by a strong correlation and a power spectrum closely resembling the ground-truth EEG signal. This outperforms the existing methods in terms of artifact removal. Additionally, the proposed algorithm exhibits significantly reduced execution time, enabling real-time online analysis.

The desired performance of nucleic acid testing (NAT) may vary if used for disease diagnosis or for the evaluation of the therapeutic efficacy of a treatment, although in most cases, the same assay is used. However, these tests may not be affordable in many situations including in low/middle income countries that in response have developed domestic assays. Given the example of HCV NAT among people who inject drugs in Vietnam, we aimed at evaluating a domestic assay versus an FDA- and CE-approved assay. This cross-evaluation revealed that (i) the domestic assay had a poorer sensitivity with a threshold of detection above 104 IU/mL, and (ii) the FDA-approved assay had a percentage of false negative results close to 1%. Together, in the present study, the domestic assay had a performance compatible with diagnosis purposes (given that this population was 70% HCV seropositive) but not compatible with HCV treatment monitoring (given that treatment failures are rare and the observed viremia frequently below the threshold of detection). This study highlights the need for a proper evaluation of HCV RNA domestic assays in order to efficiently contribute to the WHO HCV elimination target by 2030.

BackgroundChronic granulomatous disease (CGD) is an inborn error of immunity (IEI) disorder that results from defects in the respiratory burst activity in phagocytes, leading to the inability to kill bacterial and fungal microorganisms. CGD patients usually have a high incidence of morbidity such as infections and autoinflammatory diseases and a high mortality rate. Allogeneic bone marrow transplantation (BMT) is the only definitive cure for patients who suffer from CGD.Case presentationWe report the first transplant case of chronic granulomatous disease in Vietnam. A 25-month-old boy with X-linked CGD underwent bone marrow transplantation from his 5-year-old, full-matched human leukocyte antigen (HLA)-carrier sibling after myeloablative conditioning regimen with busulfan 5.1 mg/kg/day for 4 days, fludarabine 30 mg/m2/day for 5 days, and rATG (Grafalon-Fresenius) 10 mg/kg/day for 4 days. Neutrophil was engrafted on day 13 posttransplant, donor chimerism was 100% on day 30 with the dihydrorhodamine-1,2,3 (DHR 123) flow cytometric assay test that reached 38% of the normal 45 days posttransplant. Five months after transplant, the patient was free of infection with stable DHR 123 assay at 37%, and donor chimerism remained 100%. No sign of a graft-versus-host disease had been observed posttransplant.ConclusionWe suggest that bone marrow transplantation is a safe and effectual cure for CGD patients, especially for patients with HLA-identical siblings.

Tetrasubstituted 2,3‐trans‐dihydrofuran and furan are important heterocyclic scaffolds in natural product, bioorganic and medicinal chemistry as well as in material science. The synthesis of both of these heterocycles starting from common and readily available starting materials are challenging. We found that in situ generated deoxybenzoin‐chalcone Michael adducts underwent oxidative annulation upon heating with molecular iodine in DMSO to provide selectively 2,3‐trans‐dihydrofurans at 80 °C and furans at 120 °C. [ABSTRACT FROM AUTHOR]

People who inject drugs (PWID) are a population exposed to many genotoxicants and with a high prevalence of HCV infection. Direct-acting antiviral (DAA) regimens are now widely used to treat chronic HCV infection. Although side effects to treatment are currently rare, the long-term effects such as suspicions of de novo hepatocellular carcinoma (HCC) occurrence or HCC recurrence and cardiac defects are still up for debate. Given the structure of DAAs, the molecules have a potential mitochondrial DNA (mtDNA) genotoxicity. We have previously reported acute mtDNA toxicity of three DAA regimens among PWID with a strong impact on the rate of mtDNA deletion, less on the quantity of mtDNA copy per cell at sustained viral response at 12 weeks (SVR12). Herein, we report the mtDNA parameters nine months after drug discontinuation. We observed that the percentage of the deleted mtDNA genome increased over time. No exposure to any other genotoxicants during this period was associated with a high deletion percentage, suggesting that the replicative advantage of the deleted molecules outweighed their elimination processes. Such observation calls for longer-term follow-up and may contribute to the molecular basis of subclinical side effects of DAA treatments.