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The crinipelloid genera Crinipellis and Moniliophthora (Agaricales, Marasmiaceae) are characterized by basidiomes that produce long, dextrinoid, hair-like elements on the pileus surface. Historically, most species are believed to be saprotrophic or, rarely, parasitic on plant hosts. The primary morphological diagnostic characters that separate Crinipellis and Moniliophthora are pliant vs. stiff (Crinipellis) stipes and a tendency toward production of reddish pigments (ranging from violet to orange) in the basidiome in Moniliophthora. Additionally, most species of Moniliophthora appear to have a biotrophic habit, while those of Crinipellis are predominantly saprotrophic. Recently, several new neotropical collections prompted a morphological and phylogenetic analysis of this group. Herein, we propose a new species and two new combinations Moniliophthora mayarum sp. nov., described from Belize, is characterized by its larger pileus and narrower basidiospores relative to other related species; Moniliophthora ticoi comb. nov. (= Crinipellis ticoi) is recollected and redescribed from biotrophic collections from northern Argentina; and M. brasiliensis comb. nov. (= Crinipellis brasiliensis), a parasite of Heteropterys acutifolia. The addition of these three parasitic species into Moniliophthora support a hypothesis of a primarily biotrophic/parasitic habit within this genus.With only three published reports, the genus Chroogomphus (Boletales, Gomphidiaceae) is poorly studied in Pakistan. During recent sampling events in Khyber Pakhtunkhawa province, Pakistan, several collections of Chroogomphus were made, representing undescribed taxa. Based on morphological and molecular data, two new species are described Chroogomphus pakistanicus and C. pruinosus. We present a description and illustrations for both taxa. A molecular phylogenetic reconstruction, based on the internal transcribed spacer (ITS1-5.8S-ITS2) barcode region, shows that C. Selleckchem JNJ-64619178 pakistanicus and C. pruinosus are placed in two different subgenera of Chroogomphus (subg. Chroogomphus and subg. Siccigomphus, respectively). Munazza Kiran, Ammara Sattar, Khushbakht Zamir, Danny Haelewaters, Abdul Nasir Khalid.A new disease of fennel is described from Sicily (southern Italy). Surveys of the disease and sampling were conducted during spring 2017 and 2018 in Adrano and Bronte municipalities (Catania province) where this crop is widely cultivated. Isolations from the margin of symptomatic tissues resulted in fungal colonies with the same morphology. Pathogenicity tests with one isolate of the fungus on 6-month-old plants of fennel reproduced similar symptoms to those observed in nature. Inoculation experiments to assess the susceptibility of six different fennel cultivars to infection by the pathogen showed that the cultivars ‘Narciso’, ‘Apollo’, and ‘Pompeo’ were more susceptible than ‘Aurelio’, ‘Archimede’, and ‘Pegaso’. Phylogenetic analyses based on a matrix of the internal transcribed spacer (ITS), the large subunit (LSU), and the small subunit (SSU) rDNA regions revealed that the isolates represent a new genus and species within the Leptosphaeriaceae, which is here described as Ochraceocephala foeniculi gen. et sp. nov. This study improves the understanding of this new fennel disease, but further studies are needed for planning effective disease management strategies. According to the results of the phylogenetic analyses, Subplenodomus iridicola is transferred to the genus Alloleptosphaeria and Acicuseptoria rumicis to Paraleptosphaeria. Dalia Aiello, Alessandro Vitale, Giancarlo Polizzi, Hermann Voglmayr.Background Birth weight predicts the infant’s future health, growth, and viability. It is a good summary measure of many public health problems that include long-term maternal malnutrition, and poor health care during pregnancy. In developing countries, a birth weight below 2500 g is the leading cause of infant and child mortality. In Ethiopia, LBW had more than 13% prevalence. Determinants of low birth weight were yet to be completely understood. Therefore, this study investigates the predictors of low birth weight. Objective To identify determinants of low birth weight among newborns delivered at Addis Ababa public hospitals, 2019. Methods Institution-based unmatched case-control study was conducted among 279 (93 cases and 186 controls) newborns delivered from March 15 to April 30, 2019, in Addis Ababa public hospitals. Consecutive and systematic random sampling were employed to select cases and controls, respectively. Data were collected by interview using structured and pretested questionnaire. Finally, data were entered using Epi-data 4.2 and analysed using SPSS version 25. Factors having P-value less then 0.25 in the bivariable logistic regression model were entered into a multivariable logistic regression model. Statistical significance was declared at P-value ≤ 0.05. Results From 279 selected participants, 270 new-borns (90 cases and 180 controls) participated. In logistic regression model, significant association was found with gestational hypertension [AOR 3.7 (95% CI 1.6-8.7)], maternal height [AOR 5.7 (95% CI 1.7-19.7)], incomplete antenatal visit [AOR 6.7 (95% CI 3.2-15.3)], and low maternal educational status [AOR 3.8 (95% CI 1.3-10.9)]. Conclusion Predictors of low birth weight were maternal height less then 155 cm, complications during pregnancy, gestational hypertension, and incomplete Antenatal visit, and low maternal education. Stakeholders would better work together to reduce low birth weight by preparing appropriate intervention and monitoring policy. © 2020 Baye Mulu et al.Background Undernutrition remains one of the most common causes of morbidity and mortality among children throughout the world particularly in developing countries. The present study aimed to assess the magnitude and associated factors of undernutrition among children aged 12-59 months. Methods A community-based cross-sectional study was conducted in Wolaita district from May to June 2015. Multi-stage stratified systematic random sampling procedure was used. Data were collected using a pretested interviewer-administered questionnaire from 626 children aged 12-59 months. Height and weight were measured by trained data collectors and WHO Anthro version 3.2.2 software was used. Data were entered into Epi Info version 3.3.5 and were exported and analyzed using SPSS version 21. Multivariable logistic regression model with a step-wise method was used to determine the predictors of undernutrition. Results One third (34.1%; 95% CI 30.4-37.9%) of children were stunted while 6.9% and 11.9% of them were wasted and underweight, respectively, based on WHO Z score less then -2.