The Nutritional Composition of Maca in Hypocotyls ( Lepidium meyenii

Maca (Lepidium meyenii Walp.) was introduced to China in the recent two decades. Proximate compositions and secondary metabolites in dried maca tuber powders of different cultivation areas and colour types were analyzed and compared in order to provide the scientific guideline for its application. Cultivation region significantly affects the compositions of maca. The protein content of maca ranged from 9.31% to 21.02% by dry basis of maca powders and Xiaopingba-Y, Yulong-Y, and Pamirs-Y have the higher protein contents. The essential amino acids (EAA) contents ranged from 189.19 to 312.90 mg/g protein. The crude lipid content of different maca ranged from 0.59% to 1.00% and has no significant difference (P>0.05). The total dietary fiber (TDF) contents ranged from 17.82% to 26.00% and soluble dietary fiber (SDF) ranged from 2.46% to 7.88%, respectively. Maca samples were rich in Na, Mg, Ca, and K elements which ranged 138.3–187.8, 625.2–837.2, 3838.9–4502.7, and 5394.8–8063.3 mg/kg dry matter (DM). Xiaopingba-Y has the highest benzyl glucosinolate content which was 2.31 mg/g DM. Peru-Y and Xiaopingba have the higher contents of total alkaloids contents which was 2.61 and 2.56 mg/kg DM. Yongsheng-Y, Yulong-Y, and Pamirs-Y were rich in N-benzyl hexadecanamide contents, which were 0.164, 0.174, and 0.173 mg/g DM, respectively. Significant higher protein, total dietary fiber, insoluble dietary fiber, total alkaloids, and benzyl glucosinolate contents were found in purple and black maca compared to yellow maca in Pamirs, while there was no significant difference in N-benzyl hexadecanamide content

"Brilliant AI Doctor" in Rural China: Tensions and Challenges in AI-Powered CDSS Deployment

Artificial intelligence (AI) technology has been increasingly used in the implementation of advanced Clinical Decision Support Systems (CDSS). Research demonstrated the potential usefulness of AI-powered CDSS (AI-CDSS) in clinical decision making scenarios. However, post-adoption user perception and experience remain understudied, especially in developing countries. Through observations and interviews with 22 clinicians from 6 rural clinics in China, this paper reports the various tensions between the design of an AI-CDSS system ("Brilliant Doctor") and the rural clinical context, such as the misalignment with local context and workflow, the technical limitations and usability barriers, as well as issues related to transparency and trustworthiness of AI-CDSS. Despite these tensions, all participants expressed positive attitudes toward the future of AI-CDSS, especially acting as "a doctor's AI assistant" to realize a Human-AI Collaboration future in clinical settings. Finally we draw on our findings to discuss implications for designing AI-CDSS interventions for rural clinical contexts in developing countries

Human-centered design and evaluation of AI-empowered clinical decision support systems: a systematic review

IntroductionArtificial intelligence (AI) technologies are increasingly applied to empower clinical decision support systems (CDSS), providing patient-specific recommendations to improve clinical work. Equally important to technical advancement is human, social, and contextual factors that impact the successful implementation and user adoption of AI-empowered CDSS (AI-CDSS). With the growing interest in human-centered design and evaluation of such tools, it is critical to synthesize the knowledge and experiences reported in prior work and shed light on future work.MethodsFollowing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic review to gain an in-depth understanding of how AI-empowered CDSS was used, designed, and evaluated, and how clinician users perceived such systems. We performed literature search in five databases for articles published between the years 2011 and 2022. A total of 19874 articles were retrieved and screened, with 20 articles included for in-depth analysis.ResultsThe reviewed studies assessed different aspects of AI-CDSS, including effectiveness (e.g., improved patient evaluation and work efficiency), user needs (e.g., informational and technological needs), user experience (e.g., satisfaction, trust, usability, workload, and understandability), and other dimensions (e.g., the impact of AI-CDSS on workflow and patient-provider relationship). Despite the promising nature of AI-CDSS, our findings highlighted six major challenges of implementing such systems, including technical limitation, workflow misalignment, attitudinal barriers, informational barriers, usability issues, and environmental barriers. These sociotechnical challenges prevent the effective use of AI-based CDSS interventions in clinical settings.DiscussionOur study highlights the paucity of studies examining the user needs, perceptions, and experiences of AI-CDSS. Based on the findings, we discuss design implications and future research directions

The Composition Analysis of Maca (<i>Lepidium meyenii</i>Walp.) from Xinjiang and Its Antifatigue Activity

Environment would affect the nutritional composition of maca, especially its secondary metabolite. The chemical compositions and function of Xinjiang maca were not very clear. The chemical compositions and bioactivity of Xinjiang maca were determined. A mouse model was also used to evaluate the antifatigue activity of Xinjiang maca as a forced swimming test was performed and certain biochemical parameters related were estimated. The results show that the Xinjiang maca is rich in protein content and amino acids, especially branched chain amino acids such as Valine and Isoleucine related to the effect of antifatigue. It also has considerable minerals ions such as Ca and Mg. Besides, bioactive ingredients such as maca amide, glucosinolate, and alkaloid of Xinjiang maca are similar to those of maca from other areas, which qualify the biological value of Xinjiang maca. The results of mice model suggest that maca has a dose-dependent antifatigue activity by decreasing blood lactic acid, as well as increasing liver glycogen content and the forced swimming time.</jats:p