The microbiologic evaluations of 332 consecutive patients with the primary diagnosis of chronic blepharitis were reviewed and compared to those of 160 control patients. The most commonly isolated organisms from lids with blepharitis were Staphylococcus epidermidis (95.8%), Propronibacterium acnes (92.8%), Corynebacterium sp. (76.8%), Acinetobacter sp. (11.4%), and Staphylococcus aureus (10.5%). Compared to controls, S. epidermidis (p less than 0.01), P. acnes (p less than 0.02), and Corynebacterium sp. (p less than 0.001) were present significantly more often. S. aureus and the isolation of more than one microbial species were not more common in blepharitis patients. Quantitatively, heavy growth, by total and individual species, was significantly more common in blepharitis patients (total, p less than 0.001; S. epidermidis, p less than 0.001, P. acnes, p less than 0.001). These data demonstrate that patients with blepharitis are more likely to have normal skin bacteria on their lids and in greater quantities than nonblepharitis patients.
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BMC Bioinformatics
January 2025
MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
Background: CRISPRi screening has become a powerful approach for functional genomic research. However, the off-target effects resulting from the mismatch tolerance between sgRNAs and their intended targets is a primary concern in CRISPRi applications.
Results: We introduce Guide Library Designer (GLiDe), a web-based tool specifically created for the genome-scale design of sgRNA libraries tailored for CRISPRi screening in prokaryotic organisms.
J Anim Ecol
January 2025
University of Florida, Department of Wildlife Ecology and Conservation, Gainesville, Florida, USA.
Invasive predators pose a substantial threat to global biodiversity. Native prey species frequently exhibit naïveté to the cues of invasive predators, and this phenomenon may contribute to the disproportionate impact of invasive predators on prey populations. However, not all species exhibit naïveté, which has led to the generation of many hypotheses to explain patterns in prey responses.
View Article and Find Full Text PDFNat Microbiol
January 2025
Department of Integrative Biology, The University of Texas at Austin, Austin, TX, USA.
Ecology and evolution are considered distinct processes that interact on contemporary time scales in microbiomes. Here, to observe these processes in a natural system, we collected a two-decade, 471-metagenome time series from Lake Mendota (Wisconsin, USA). We assembled 2,855 species-representative genomes and found that genomic change was common and frequent.
View Article and Find Full Text PDFCell
December 2024
Key Laboratory Experimental Teratology of the Ministry of Education, New Cornerstone Science Laboratory, Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Shandong University, Jinan, Shandong 250012, China; NHC Key Laboratory of Otorhinolaryngology, Qilu Hospital of Shandong University, Advanced Medical Research Institute, Shandong University, Jinan, China; Department of Physiology and Pathophysiology, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, China. Electronic address:
Animals have evolved pH-sensing membrane receptors, such as G-protein-coupled receptor 4 (GPR4), to monitor pH changes related to their physiology and generate adaptive reactions. However, the evolutionary trajectory and structural mechanism of proton sensing by GPR4 remain unresolved. Here, we observed a positive correlation between the optimal pH of GPR4 activity and the blood pH range across different species.
View Article and Find Full Text PDFComput Biol Med
January 2025
Division of Electronics and Information Engineering, College of Engineering, Jeonbuk National University, 567, Baekje-daero, Deokjin-gu, 54896, Jeonju, Republic of Korea. Electronic address:
Kidney stone is a common urological disease in dogs and can lead to serious complications such as pyelonephritis and kidney failure. However, manual diagnosis involves a lot of burdens on radiologists and may cause human errors due to fatigue. Automated methods using deep learning models have been explored to overcome this limitation.
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