Search

This study is aimed at examining the impact of ChatGPT on pediatric endocrine and metabolic conditions, particularly in the areas of screening and diagnosis, in both Chinese and English modes. A 40-question questionnaire covering the four most common pediatric endocrine and metabolic conditions was posed to ChatGPT in both Chinese and English three times each. Six pediatric endocrinologists evaluated the responses. ChatGPT performed better when responding to questions in English, with an unreliable rate of 7.5% compared to 27.5% for Chinese questions, indicating a more consistent response pattern in English. Among the reliable questions, the answers were more comprehensive and satisfactory in the English mode. We also found disparities in ChatGPT's performance when interacting with different target groups and diseases, with improved performance for questions posed by clinicians in English and better performance for questions related to diabetes and overweight/obesity in Chinese for both clinicians and patients. Language comprehension, providing incomprehensive answers, and errors in key data were the main contributors to the low scores, according to reviewer feedback. Conclusion: Despite these limitations, as ChatGPT continues to evolve and expand its network, it has significant potential as a practical and effective tool for clinical diagnosis and treatment. What is Known: • The deep learning-based large-language model ChatGPT holds great promise for improving clinical practice for both physicians and patients and has the potential to increase the speed and accuracy of disease screening and diagnosis, as well as enhance the overall efficiency of the medical process. However, the reliability and appropriateness of AI model responses in specific field remains unclear. • This study focused on the reliability and appropriateness of AI model responses to straightforward and fundamental questions related to the four most prevalent pediatric endocrine and metabolic disorders, for both healthcare providers and patients, in different language scenarios. What is New: • The AI model performed better when responding to questions in English, with more consistent, as well as more comprehensive and satisfactory responses. In addition, we also found disparities in ChatGPT's performance when interacting with different target groups and different diseases. • Despite these limitations, as ChatGPT continues to evolve and expand its network, it has significant potential as a practical and effective tool for clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Obstructive Sleep Apnea (OSA) is related to repeated upper airway collapse, intermittent hypoxia, and intestinal barrier dysfunction. The resulting damage to the intestinal barrier may affect or be affected by the intestinal microbiota. A prospective case–control was used, including 48 subjects from Sleep Medicine Center of Nanfang Hospital. Sleep apnea was diagnosed by overnight polysomnography. Fecal samples and blood samples were collected from subjects to detect fecal microbiome composition (by 16S rDNA gene amplification and sequencing) and intestinal barrier biomarkers—intestinal fatty acid-binding protein (I-FABP) and D-lactic acid (D-LA) (by ELISA and colorimetry, respectively). Plasma D-LA and I-FABP were significantly elevated in patients with OSA. The severity of OSA was related to differences in the structure and composition of the fecal microbiome. Enriched Fusobacterium, Megamonas, Lachnospiraceae_UCG_006, and reduced Anaerostipes was found in patients with severe OSA. Enriched Ruminococcus_2, Lachnoclostridium, Lachnospiraceae_UCG_006, and Alloprevotella was found in patients with high intestinal barrier biomarkers. Lachnoclostridium and Lachnospiraceae_UCG_006 were the common dominant bacteria of OSA and intestinal barrier damage. Fusobacterium and Peptoclostridium was independently associated with apnea–hypopnea index (AHI). The dominant genera of severe OSA were also related to glucose, lipid, neutrophils, monocytes and BMI. Network analysis identified links between the fecal microbiome, intestinal barrier biomarkers, and AHI. The study confirms that changes in the intestinal microbiota are associated with intestinal barrier biomarkers among patients in OSA. These changes may play a pathophysiological role in the systemic inflammation and metabolic comorbidities associated with OSA, leading to multi-organ morbidity of OSA. [ABSTRACT FROM AUTHOR]

With the increasing demand for resources from cloud computing users, enhancing the energy efficiency of data centers and ensuring the Quality of Service have become noteworthy research topics. Most Previous studies on Virtual Machine (VM) consolidation often neglect the delay and energy consumption associated with Power Mode Transitions (PMTs), leading to potential deviations in experimental results from real-world scenarios. In this paper, we propose a Two-Level Heuristics Virtual Machine Consolidation (TLHVMC) method that takes into account the overheads of PMTs. This method employs a Greedy Strategy-based hybrid heuristic Placement (GSP) algorithm for resource allocation. After incorporating underloaded host detection for host classification, GSP applies distinct greedy strategies on various host lists, which balances data center workload and minimizes active hosts. Moreover, Time Window-based Centralized power mode Control policies are implemented to centrally manage host power modes. These policies improve energy-saving by suspending idle hosts and reduce the Service Level Agreement violations by adaptively resuming hosts based on the data center’s state within a time window. Experimental results on real workload traces show that TLHVMC significantly improves the energy efficiency of the data center and maintains the required cloud system performance compared to some other VM consolidation algorithms. [ABSTRACT FROM AUTHOR]

There is an urgent need to explore new antimicrobial agents due to the looming threat of bacteria resistance. Bovine lactoferricin (LfcinB), as a multifunctional peptide, has the potential to be a new active drug in the future. In this study, it aims to investigate the effect of fatty acid conjugation on antimicrobial peptide activity and topical therapeutic efficacy in a mouse model infected with Staphylococcus hyicus. Both Lfcin4 and Lfcin5 were conjugated with the unsaturated fatty acid linoleic acid (18-C) at their N-terminus and modified by acylation at the C-terminus. The derived peptides of Lin-Lf4NH2 and Lin-Lf5NH2 showed better antibacterial activity (MICs of 3.27 to 6.64 μM) than their parent peptides (MICs of 1.83 to 59.57 μM). Lin-Lf4NH2 (63.2%, 5 min) and Lin-Lf5NH2 (35.8%, 5 min) could more rapidly penetrate bacterial membrane than Lf4NH2 (2.34%, 5 min) and Lf5NH2 (1.94%, 5 min), which further confirmed by the laser scanning confocal microscopy (LSCM). Electron microscopy observations showed Lin-Lf4NH2 and Lin-Lf5NH2 disrupted S. hyicus cell membranes and led to the leakage of contents. Furthermore, after treatment with Lin-Lf4NH2 and Lin-Lf5NH2, the abscess symptoms of mice were significantly alleviated; the recovery rate of abscesses scope of Lin-Lf4NH2 (73.25%) and Lin-Lf5NH2 (71.71%) were 38.8 and 37.9-fold higher than that of untreated group (1.89%), respectively, and superior to Lf4NH2 (46.87%) and Lf5NH2 (58.75%). They significantly reduced the bacterial load and the levels of the pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β) and chemokine (MCP-1) in S. hyicus skin lesions. This study provides evidence that conjugation of a fatty acid to antimicrobial peptides can improve the activity and have potential for topical therapeutic of S. hyicus skin infections. Key points: • Lin-Lfcin4NH2/Lfcin5NH2 showed stronger antimicrobial activity than parent peptides. • Lin-Lfcin4NH2/Lfcin5NH2 had a more effective ability to destroy bacterial membranes. • Lin-Lfcin4NH2/Lfcin5NH2 showed a topically higher efficacy than parent peptides. [ABSTRACT FROM AUTHOR]