Discriminating between nesting and non-nesting habitat in a vulnerable bird species: Implications for behavioural ecology

Nowadays, partitioning amongst nesting and non-nesting habitats is not much studied. Here, I investigate whether or not the turtle dove (Streptopelia turtur) nesting habitats overlap with those used for other purposes in a North African agroforestry system. A total of 33 nest points and 33 turtle dove presence points were considered. The study, conducted in May to June 2017, attempted to determine the factors that may play a role in discriminating between the nesting habitats and non-nesting habitats. I used a linear discriminant analysis (LDA) to test the relevance of proximity of food resources, forest edge and human presence variables in the distribution of the species. The results show substantial segregation in the habitats selected for nesting and those selected for other uses [average distance was 1129.69 ± 169.40 m (n = 66) with a maximum of 1518.6 m and a minimum of 617.72 m], with selection depending primarily on the proximity to forest edge and feeding areas. I discuss these findings and their implications on behavioural ecology and future researches of this vulnerable species. I suggest guidelines for future studies that will seek to better understand the behavioural dynamics of turtle doves in the Mediterranean agroforestry systems. This can only be done when disturbance covariates, such as: (i) forest logging, (ii) cereal harvesting and (iii) hunting and predation pressures, were imperatively taken into account

La grossesse gémellaire sur un utérus pseudo unicorne: à propos d’un cas

L'incidence des malformations utérines est estimée dans la population générale entre 0,1 et 3%. La survenue d'une grossesse en cas de malformation utérine est une situation potentiellement à haut risque obstétrical. Nous décrivons un cas très rare d'une grossesse gémellaire sur un utérus pseudo unicorne découverte précocement à 8 SA, permettant la réalisation d'une hémihysterectomie de la corne rudimentaire prévenant ainsi le risque majeur de la rupture utérine. L'évolution était favorable jusqu'à 37 SA où la patiente a été programmée pour césarienne prophylactique. Le dépistage échographique au premier trimestre de la grossesse est donc primordial permettant la détection systématique de ce genre de malformation afin de prévenir les complications.Pan African Medical Journal 2015; 2

Oral manifestations in young adults infected with COVID-19 and impact of smoking:a multi-country cross-sectional study

Background: Oral manifestations and lesions could adversely impact the quality of people's lives. COVID-19 infection may interact with smoking and the impact on oral manifestations is yet to be discovered. Objectives: The aim of this study was to assess the self-reported presence of oral lesions by COVID-19-infected young adults and the differences in the association between oral lesions and COVID-19 infection in smokers and non-smokers. Methods: This cross-sectional multi-country study recruited 18-to-23-year-old adults. A validated questionnaire was used to collect data on COVID-19-infection status, smoking and the presence of oral lesions (dry mouth, change in taste, and others) using an online platform. Multi-level logistic regression was used to assess the associations between the oral lesions and COVID-19 infection; the modifying effect of smoking on the associations. Results: Data was available from 5,342 respondents from 43 countries. Of these, 8.1% reported COVID-19-infection, 42.7% had oral manifestations and 12.3% were smokers. A significantly greater percentage of participants with COVID-19-infection reported dry mouth and change in taste than non-infected participants. Dry mouth (AOR=, 9=xxx) and changed taste (AOR=, 9=xxx) were associated with COVID-19-infection. The association between COVID-19-infection and dry mouth was stronger among smokers than non-smokers (AOR = 1.26 and 1.03, p = 0.09) while the association with change in taste was stronger among non-smokers (AOR = 1.22 and 1.13, p = 0.86). Conclusion: Dry mouth and changed taste may be used as an indicator for COVID-19 infection in low COVID-19-testing environments. Smoking may modify the association between some oral lesions and COVID-19-infection

Anxiety among adolescents and young adults during COVID-19 pandemic: A multi-country survey

(1) Background: Adolescents-and-young-adults (AYA) are prone to anxiety. This study assessed AYA's level of anxiety during the COVID-19 pandemic; and determined if anxiety levels were associated with country-income and region, socio-demographic profile and medical history of individuals. (2) Methods: A survey collected data from participants in 25 countries. Dependent-variables included general-anxiety level, and independent-variables included medical problems, COVID-19 infection, age, sex, education, and country-income-level and region. A multilevel-multinomial-logistic regression analysis was conducted to determine the association between dependent, and independent-variables. (3) Results: Of the 6989 respondents, 2964 (42.4%) had normal-anxiety, and 2621 (37.5%), 900 (12.9%) and 504 (7.2%) had mild, moderate and severe-anxiety, respectively. Participants from the African region (AFR) had lower odds of mild, moderate and severe than normal-anxiety compared to those from the Eastern-Mediterranean-region (EMR). Also, participants from lower-middle-income-countries (LMICs) had higher odds of mild and moderate than normal-anxiety compared to those from low-income-countries (LICs). Females, older-adolescents, with medical-problems, suspected-but-not-tested-for-COVID-19, and those with friends/family-infected with COVID-19 had significantly greater odds of different anxiety-levels. (4) Conclusions: One-in-five AYA had moderate to severe-anxiety during the COVID-19-pandemic. There were differences in anxiety-levels among AYAs by region and income-level, emphasizing the need for targeted public health interventions based on nationally-identified priorities

Cigarettes' use and capabilities-opportunities-motivation-for-behavior model:a multi-country survey of adolescents and young adults

The use of cigarettes among adolescents and young adults (AYA) is an important issue. This study assessed the association between regular and electronic-cigarettes use among AYA and factors of the Capability-Motivation-Opportunity-for-Behavior-change (COM-B) model. A multi-country survey was conducted between August-2020 and January-2021, Data was collected using the Global-Youth-Tobacco-Survey and Generalized-Anxiety-Disorder-7-item-scale. Multi-level logistic-regression-models were used. Use of regular and electronic-cigarettes were dependent variables. The explanatory variables were capability-factors (COVID-19 status, general anxiety), motivation-factors (attitude score) and opportunity-factors (country-level affordability scores, tobacco promotion-bans, and smoke free-zones) controlling for age and sex. Responses of 6,989-participants from 25-countries were used. Those who reported that they were infected with COVID-19 had significantly higher odds of electronic-cigarettes use (AOR = 1.81, P = 0.02). Normal or mild levels of general anxiety and negative attitudes toward smoking were associated with significantly lower odds of using regular-cigarettes (AOR = 0.34, 0.52, and 0.75, P < 0.001) and electronic-cigarettes (AOR = 0.28, 0.45, and 0.78, P < 0.001). Higher affordability-score was associated with lower odds of using electronic-cigarettes (AOR = 0.90, P = 0.004). Country-level-smoking-control policies and regulations need to focus on reducing cigarette affordability. Capability, motivation and opportunity factors of the COM-B model were associated with using regular or electronic cigarettes

A multi-country study on the impact of sex and age on oral features of COVID-19 infection in adolescents and young adults

Background: Oral diseases are features of COVID-19 infection. There is, however, little known about oral diseases associated with COVID-19 in adolescents and young adults (AYA). Therefore, the aim of this study was to assess oral lesions’ association with COVID-19 infection in AYA; and to identify if sex and age will modify these associations. Methodology: Data was collected for this cross-sectional study between August 2020 and January 2021 from 11-to-23 years old participants in 43-countries using an electronic validated questionnaire developed in five languages. Data collected included information on the dependent variables (the presence of oral conditions- gingival inflammation, dry mouth, change in taste and oral ulcers), independent variable (COVID-19 infection) and confounders (age, sex, history of medical problems and parents’ educational level). Multilevel binary logistic regression was used for analysis. Results: Complete data were available for 7164 AYA, with 7.5% reporting a history of COVID-19 infection. A significantly higher percentage of participants with a history of COVID-19 infection than those without COVID-19 infection reported having dry mouth (10.6% vs 7.3%, AOR = 1.31) and taste changes (11.1% vs 2.7%, AOR = 4.11). There was a significant effect modification in the association between COVID-19 infection and the presence of dry mouth and change in taste by age and sex (P = 0.02 and < 0.001). Conclusion: COVID-19 infection was associated with dry mouth and change in taste among AYA and the strength of this association differed by age and sex. These oral conditions may help serve as an index for suspicion of COVID-19 infection in AYA

Fetal biometry and amniotic fluid volume assessment end-to-end automation using Deep Learning

Abstract Fetal biometry and amniotic fluid volume assessments are two essential yet repetitive tasks in fetal ultrasound screening scans, aiding in the detection of potentially life-threatening conditions. However, these assessment methods can occasionally yield unreliable results. Advances in deep learning have opened up new avenues for automated measurements in fetal ultrasound, demonstrating human-level performance in various fetal ultrasound tasks. Nevertheless, the majority of these studies are retrospective in silico studies, with a limited number including African patients in their datasets. In this study we developed and prospectively assessed the performance of deep learning models for end-to-end automation of fetal biometry and amniotic fluid volume measurements. These models were trained using a newly constructed database of 172,293 de-identified Moroccan fetal ultrasound images, supplemented with publicly available datasets. the models were then tested on prospectively acquired video clips from 172 pregnant people forming a consecutive series gathered at four healthcare centers in Morocco. Our results demonstrate that the 95% limits of agreement between the models and practitioners for the studied measurements were narrower than the reported intra- and inter-observer variability among expert human sonographers for all the parameters under study. This means that these models could be deployed in clinical conditions, to alleviate time-consuming, repetitive tasks, and make fetal ultrasound more accessible in limited-resource environments