Assessing the safety and use of medicinal herbs during pregnancy: a cross-sectional study in São Paulo, Brazil

Background: Despite the lack of evidence supporting the safety and clinical efficacy of herbal medicine (HM), its use among pregnant women continues to increase. Given the high prevalence of contraindicated herbs among the pregnant population in Brazil, it is crucial to examine the use of HM and evaluate its safety based on the current scientific literature to ensure that women are using HM appropriately.Methods: A cross-sectional study was conducted from October 2022 to January 2023 at a public teaching hospital in São Paulo, Brazil. A total of 333 postpartum women in the postnatal wards and postnatal clinic were interviewed using a semi-structured questionnaire. The survey instrument consisted of 51 items covering the use of HM during pregnancy, sociodemographic and health-related characteristics, COVID-19 experiences, and pregnancy outcomes. For data analysis, chi-square and multivariate logistic regression were conducted using SPSS ver. 26.0.Results: Approximately 20% of respondents reported using HM during their most recent pregnancy, with a higher use observed among women from ethnic minority groups and those with prior HM experience. Among the 20 medicinal herbs identified, 40% were found to be contraindicated or recommended for use with caution during pregnancy. However, only half of the women discussed their HM use with obstetric care providers.Conclusion: This study emphasizes the continued public health concern regarding the use of contraindicated or potentially harmful HM among pregnant women in Brazil, highlighting the need for sustained efforts to reduce the risk of inappropriate HM use. By updating antenatal care guidelines based on the latest scientific evidence, healthcare providers can make informed clinical decisions and effectively monitor pregnant women’s HM use, ultimately promoting safer and more effective healthcare practices

Safety classification of herbal medicines used among pregnant women in Asian countries: a systematic review

Abstract Background High prevalence of herbal medicines used in pregnancy and the lack of information on their safety is a public concern. Despite this, no significant research has been done regarding potential adverse effects of using herbal medicines during pregnancy, especially among developing Asian countries. Methods Cross-sectional studies were searched up to year 2016 on PubMed/Medline and EMBASE, the data were extracted and quality of studies was assessed using the quality appraisal tool. The findings are reported in accordance to the PRISMA checklist (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Classification on safety of identified herbal medicines was done based on current scientific literature. Results This study included eight cross-sectional studies (2729 participants) from seven different Asian countries, of which 1283 (47.01%) women used one or more herbal medicines during pregnancy. Peppermint (22.8%), aniseed (14.7%), olibanum (12.9%), flixweed seed (12.2%) and ginger (11.5%) were the most frequently used herbal medicines. Out of the 33 identified herbal medicines, 13 were classified as safe to use, five as use with caution, eight were potentially harmful to use in pregnancy and information on seven herbal medicines was not available in the current literature. Conclusions Several herbal medicines identified in this review were classified to be potentially harmful or the information regarding safety in pregnancy was missing. It is recommended that contraindicated herbal medicines should be avoided and other herbals should be taken under supervision of a qualified health care practitioner. The classification regarding safety of herbal medicines in pregnancy can be utilized to create awareness on prevention of adverse effects

Herbal medicine use by pregnant women in Bangladesh: a cross-sectional study

Abstract Background Herbal medicines in pregnancy are increasingly used worldwide with prevalence of up to 67%. Although this popularity is mainly because of the common belief that these medicines are safe, recent reports suggest that several herbal medicines are potentially harmful to mother and fetus if used in pregnancy. Methods This cross-sectional study was conducted in July and August of year 2017, at maternity wards of two public hospitals in Dhaka, Bangladesh. Postpartum women were interviewed via the structured questionnaire to collect information regarding socio-demographic and health characteristics, patterns of herbal medicines used in the previous pregnancy, and outcome of pregnancy. Results Two hundred forty-three postpartum women participated in the study, with 70% of them using at least one modality of herbal medicines in previous pregnancy. Ginger, black seed, lemon tea, prune, and mustard oil were most commonly used herbal medicines. Herbal medicines were mostly used for pregnancy-related symptoms such as nausea, vomiting, and cold. Fifteen (8.8%) herbal medicine users reported side effects. Conclusions This study highlights popularity of herbal medicines during pregnancy in Bangladesh. Previous herbal medicine users and unemployed women turned significantly more to herbal medicines during pregnancy. Reports of side effects and use of some potentially harmful modalities warrant awareness regarding proper use of herbal medicines in pregnancy and its pharmacovigilance

Optimizing Android Facial Expressions Using Genetic Algorithms

Because the internal structure, degree of freedom, skin control position and range of the android face are different, it is very difficult to generate facial expressions by applying existing facial expression generation methods. In addition, facial expressions differ among robots because they are designed subjectively. To address these problems, we developed a system that can automatically generate robot facial expressions by combining an android, a recognizer capable of classifying facial expressions and a genetic algorithm. We have developed two types (older men and young women) of android face robots that can simulate human skin movements. We selected 16 control positions to generate the facial expressions of these robots. The expressions were generated by combining the displacements of 16 motors. A chromosome comprising 16 genes (motor displacements) was generated by applying real-coded genetic algorithms; subsequently, it was used to generate robot facial expressions. To determine the fitness of the generated facial expressions, expression intensity was evaluated through a facial expression recognizer. The proposed system was used to generate six facial expressions (angry, disgust, fear, happy, sad, surprised); the results confirmed that they were more appropriate than manually generated facial expressions

Feasibility of extracting cancer stage and metastasis codes from health insurance claims of outpatients and expressibility in ICD-11: a cross-sectional study using national health insurance data from South Korea

Objectives This study aimed to evaluate the incidence of health insurance claims recording the cancer stage and TNM codes representing tumor extension size (T), lymph node metastasis (N), and distant metastasis (M) for patients diagnosed with cancer and to determine whether this extracted data could be applied to the new ICD-11 codes.Design A cross-sectional study design was used, with the units of analysis as individual outpatients. Two dependent variables were extraction feasibility of cancer stage and TNM metastasis information from each claim. Expressibility of the two variables in ICD-11 was descriptively analysed.Setting and participants The study was conducted in South Korea and study participants were outpatients: lung cancer (LC) (46616), stomach cancer (SC) (50103) and colorectal cancer (CC) (54707). The data set consisted of the first health insurance claim of each patient visiting a hospital from 1 July to 31 December 2021.Results The absolute extraction success rates for cancer stage based on claims with cancer stage was 33.3%. The rates for stage for LC, SC and CC were 30.1%, 35.5% and 34.0%, respectively. The rate for TNM was 11.0%. The relative extraction success rates for stage compared with that for CC (the reference group) were lower for patients with LC (adjusted OR (aOR), 0.803; 95% CI 0.782 to 0.825; p<0.0001) but higher for SC (aOR 1.073; 95% CI 1.046 to 1.101; p<0.0001). The rates of TNM compared that for CC were 40.7% lower for LC (aOR, 0.593; 95% CI 0.569 to 0.617; p<0.0001) and 43.0% lower for SC (aOR 0.570; 95% CI 0.548 to 0.593; p<0.0001). There were limits to expressibility in ICD-11 regarding the detailed cancer stage and TNM metastasis codes.Conclusion Extracting cancer stage and TNM codes from health insurance claims were feasible, but expressibility in ICD-11 codes was limited. WHO may need to create specific cancer stage and TNM extension codes for ICD-11 due to the absence of current rules in ICD-11

Communications Protocol Design for 5G Vehicular Networks

The automotive industry is a challenging domain for the integration and evolution of heterogeneous Information and Communication Technologies (ICTs). Indeed, in order to provide drivers with a more pleasant and safer driving experience, vehicles are gradually endowed with sensing, actuation, computing, user-interaction and communications capabilities. Boosted by marketing and commercial competition, vehicles are thus becoming intelligent nodes capable of interconnecting, cooperating and even autonomously adapting to the surrounding environment. Since drivers usually spend a non-negligible fraction of time in vehicles and their behaviour may have a strong impact at a collective scale (e.g. pollution and noise in a city), the adoption of advanced ICT approaches for achieving a more safe, green and effective mobility management is still an open research issue. Moreover, the familiarity with the social networking paradigm makes people used to share information on-line with (in)direct contacts and use it in their everyday life depending on the degree of trust. It is worth noticing that this vision inherently deals with multimedia information, as it aggregates, process and disseminates sensed data (originating both on board and on the road side) integrated with warning/alarms, navigation suggestions, and context details that come from a specific area or even the Internet