Antimicrobial activities of endophytic fungi isolated from <it>Ophiopogon japonicus</it> (Liliaceae)

Abstract Background Drug resistance in bacteria has become a global concern and the search for new antibacterial agents is urgent and ongoing. Endophytes provide an abundant reservoir of bioactive metabolites for medicinal exploitation, and an increasing number of novel compounds are being isolated from endophytic fungi. Ophiopogon japonicus, containing compounds with antibacterial activity, is a traditional Chinese medicinal plant used for eliminating phlegm, relieving coughs, latent heat in the lungs, and alleviating diabetes mellitus. We investigated the antimicrobial activities of 30 strains of O. japonicus. Methods Fungal endophytes were isolated from roots and stems of O. japonicus collected from Chongqing City, southwestern China. Mycelial extracts (MC) and fermentation broth (FB) were tested for antimicrobial activity using peptide deformylase (PDF) inhibition fluorescence assays and MTT cell proliferation assays. Results A total of 30 endophytic strains were isolated from O. japonicus; 22 from roots and eight from stems. 53.33% of the mycelial extracts (MC) and 33.33% of the fermentation broths (FB) displayed potent inhibition of PDF. 80% of MC and 33.33% of FB significantly inhibited Staphylococcus aureus. 70% of MC and 36.67% of FB showed strong activities against Cryptococcus neoformans. None showed influence on Escherichia coli. Conclusion The secondary metabolites of endophytic fungi from O. japonicus are potential antimicrobial agents.</p

Optimal cut-offs of depression screening tools during the COVID-19 pandemic: a systematic review

Abstract Background Studies have reported an increase in the prevalence of depression during the COVID-19 pandemic. The accuracy of screening tools may change with the prevalence and distribution of a disease in a population or sample: the “Spectrum Effect”. Methods First, we selected commonly used screening tools and developed search strategies for the inclusion of original studies during the pandemic. Second, we searched PsycINFO, EMBASE, and MEDLINE from March 2020 to September 2022 to obtain original studies that investigated the accuracy of depression screening tools during the pandemic. We then searched these databases to identify meta-analyses summarizing the accuracy of these tools conducted before the pandemic and compared the optimal cut-offs for depression screening tools during the pandemic with those before. Result Four original studies evaluating the optimal cut-offs for four screening tools (Beck Depression Inventory [BDI-II], Hospital Anxiety and Depression Scale-Depression [HADS-D], Patient Health Questionnaire-9 [PHQ-9], and Geriatric Depression Scale-4 [GDS-4]) were published during the pandemic. Four meta-analyses summarizing these tools before the pandemic. We found that the optimal cut-off of BDI-II was 14 during the pandemic (23.8% depression prevalence, screening patients with Type 2 diabetes) and 14.5 before the pandemic (17.6% depression prevalence, screening psychiatric, primary care, and healthy populations); HADS-D was 10 during the pandemic (23.8% depression prevalence, screening patients with type 2 diabetes) and 7 before the pandemic (15.0% depression prevalence, screening medically ill patients); PHQ-9 was 11 during the pandemic (14.5% depression prevalence, screening university students) and 8 before the pandemic (10.9% depression prevalence, screening the unrestricted population), and GDS-4 was 1.8 during the pandemic (29.0% depression prevalence, screening adults seen in a memory clinic setting) and 3 before the pandemic (18.5% depression prevalence, screening older adults). Conclusion The optimal cut-off for different screening tools may be sensitive to changes in study populations and reference standards. And potential spectrum effects that should be considered in post-COVID time which aiming to improve diagnostic accuracy