- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Transmission electron microscopy revealing the mechanism of action of photodynamic therapy on Trichomonas vaginalis
摘要： Trichomonas vaginalis is an amitochondrial parasite that causes human trichomoniasis. Despite metronidazole effectiveness, resistant cases are becoming more frequent. This scenario reveals the need to develop new therapeutic options. Photodynamic Therapy (PDT) is an experimental treatment that involves the activation of photosensitive substances and the generation of cytotoxic oxygen species and free radicals to promote the selective destruction of target tissues. In previous work, we identified an excellent in vitro PDT activity using methylene blue and light emitting diode against metronidazole sensitive and resistant strains of T. vaginalis. Here, we evaluated the efficacy of PDT in vivo and its high trichomonicidal activity was assessed through transmission electron microscopy. Female Balb/c mice were infected intravaginally with T. vaginalis trophozoites. On the third day of infection, methylene blue was introduced into the vaginal canal, which then received 68.1 J / cm2 of radiation for 35.6 sec. Twenty-four hours after treatment the vaginal canal of the animals was scraped and the samples processed by the immunocytochemistry technique. Besides that, in vitro photodynamic treatment was performed and T. vaginalis trophozoites were processed by transmission electron microscopy. PDT significantly reduced infection in animals treated, compared to control groups, being as efficient as metronidazole. Morphological changes observed have suggested that PDT activity on T. vaginalis was due to necrosis. These results, added to the high trichomonicidal activity of PDT confirm its feasibility for trichomoniasis treatment.
关键词： Methylene Blue,Transmission Electron Microscopy,Trichomonas vaginalis,Photodynamic Therapy,Treatment
更新于2025-09-09 09:28:46
-
Motility-based label-free detection of parasites in bodily fluids using holographic speckle analysis and deep learning
摘要： Parasitic infections constitute a major global public health issue. Existing screening methods that are based on manual microscopic examination often struggle to provide sufficient volumetric throughput and sensitivity to facilitate early diagnosis. Here, we demonstrate a motility-based label-free computational imaging platform to rapidly detect motile parasites in optically dense bodily fluids by utilizing the locomotion of the parasites as a specific biomarker and endogenous contrast mechanism. Based on this principle, a cost-effective and mobile instrument, which rapidly screens ~3.2 mL of fluid sample in three dimensions, was built to automatically detect and count motile microorganisms using their holographic time-lapse speckle patterns. We demonstrate the capabilities of our platform by detecting trypanosomes, which are motile protozoan parasites, with various species that cause deadly diseases affecting millions of people worldwide. Using a holographic speckle analysis algorithm combined with deep learning-based classification, we demonstrate sensitive and label-free detection of trypanosomes within spiked whole blood and artificial cerebrospinal fluid (CSF) samples, achieving a limit of detection of ten trypanosomes per mL of whole blood (~five-fold better than the current state-of-the-art parasitological method) and three trypanosomes per mL of CSF. We further demonstrate that this platform can be applied to detect other motile parasites by imaging Trichomonas vaginalis, the causative agent of trichomoniasis, which affects 275 million people worldwide. With its cost-effective, portable design and rapid screening time, this unique platform has the potential to be applied for sensitive and timely diagnosis of neglected tropical diseases caused by motile parasites and other parasitic infections in resource-limited regions.
关键词： parasitic infections,holographic speckle analysis,trypanosomes,resource-limited settings,deep learning,Trichomonas vaginalis,label-free imaging,motility-based detection
更新于2025-09-04 15:30:14