Photodynamic therapy (PDT) has been considered a noninvasive and cost-effective modality for tumor treatment. However, the complexity of tumor microenvironments poses challenges to the implementation of traditional PDT. Here, we review recent advances in PDT to resolve the current problems. Major breakthroughs in PDTs are enabling significant progress in molecular medicine and are interconnected with innovative strategies based on smart bio/nanomaterials or therapeutic insights. We focus on newly developed PDT strategies designed by tailoring photosensitive reactive oxygen species generation, which include the use of proteinaceous photosensitizers, self-illumination, or oxygen-independent approaches. While these updated PDT platforms are expected to enable major advances in cancer treatment, addressing future challenges related to biosafety and target specificity is discussed throughout as a necessary goal to expand the usefulness of PDT.

We report bioluminescence analysis of matrix metalloproteinase (MMP) activity in biological substances using a surface-bound luciferase probe. Intein-fused luciferase protein enables site-specific biotinylation of luciferase in the presence of N-terminus cysteine-biotin via intein-mediated splicing process, resulting in a strong association with high bioluminescence signal onto a NeutrAvidin-coated surface. When the peptide substrate for MMP-7 was inserted into a region between luciferase and intein, the biotinylated probe detected MMP-7 activity by cleaving the peptide, and surface-induced bioluminescence signal was strongly reduced in the MMP-secreted media or mouse tissue extracts, compared with that in MMP-deficient control set. Our approach is anticipated to be useful for generating biotinylated proteins and for their applications in diagnosing MMP activity in human diseases.

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Key Point Analysis (KPA) is one of the most essential tasks in building an Opinion Summarization system, which is capable of generating key points for a collection of arguments toward a particular topic. Furthermore, KPA allows quantifying the coverage of each summary by counting its matched arguments. With the aim of creating high-quality summaries, it is necessary to have an in-depth understanding of each individual argument as well as its universal semantic in a specified context. In this paper, we introduce a promising model, named Matching the Statements (MTS) that incorporates the discussed topic information into arguments/key points comprehension to fully understand their meanings, thus accurately performing ranking and retrieving best-match key points for an input argument. Our approach 1 has achieved the 4 th place in Track 1 of the Quantitative Summarization -Key Point Analysis Shared Task by IBM, yielding a competitive performance of 0.8956 (3 rd ) and 0.9632 (7 th ) strict and relaxed mean Average Precision, respectively. Argument Analysis Key point Analysis Matching Input argument Topic: We should end mandatory retirement Argument: Older workers have more experience and expertise than young workers.

In recent years, voicebot has become a popular communication tool between humans and machines. In this paper, we will introduce our voicebot integrating text-to-speech (TTS) and speech-to-text (STT) modules provided by FPT.AI. This voicebot can be considered as a critical improvement of a typical chatbot because it can respond to human’s queries by both text and speech. FPT Open Speech, LibriSpeech datasets, and music files were used to test the accuracy and performance of the STT module. For the TTS module, it was tested by using text on news pages in both Vietnamese and English. To test the voicebot, Homestay Service topic questions and off-topic messages were input to the system. The TTS module achieved 100% accuracy in the Vietnamese text test and 72.66% accuracy in the English text test. In the STT module test, the accuracy for FPT open speech dataset (Vietnamese) is 90.51% and for LibriSpeech Dataset (English) is 0% while the accuracy in music files test is 0% for both. The voicebot achieved 100% accuracy in its test. Since the FPT.AI STT and TTS modules were developed to support only Vietnamese for dominating the Vietnam market, it is reasonable that the test with LibriSpeech Dataset resulted in 0% accuracy.