Unsupervised Human Activity Recognition through Two-stage Prompting with ChatGPT

Wearable sensor devices, which offer the advantage of recording daily objects used by a person while performing an activity, enable the feasibility of unsupervised Human Activity Recognition (HAR). Unfortunately, previous unsupervised approaches using the usage sequence of objects usually require a proper description of activities manually prepared by humans. Instead, we leverage the knowledge embedded in a Large Language Model (LLM) of ChatGPT. Because the sequence of objects robustly characterizes the activity identity, it is possible that ChatGPT already learned the association between activities and objects from existing contexts. However, previous prompt engineering for ChatGPT exhibits limited generalization ability when dealing with a list of words (i.e., sequence of objects) due to the similar weighting assigned to each word in the list. In this study, we propose a two-stage prompt engineering, which first guides ChatGPT to generate activity descriptions associated with objects while emphasizing important objects for distinguishing similar activities; then outputs activity classes and explanations for enhancing the contexts that are helpful for HAR. To the best of our knowledge, this is the first study that utilizes ChatGPT to recognize activities using objects in an unsupervised manner. We conducted our approach on three datasets and demonstrated the state-of-the-art performance.Comment: 4 page

Recent Trends in Sensor-based Activity Recognition

This seminar introduces recent trends in sensor-based activity recognition technology. Technology to recognize human activities using sensors has been a hot topic in the field of mobile and ubiquitous computing for many years. Recent developments in deep learning and sensor technology have expanded the application of activity recognition to various domains such as industrial and natural science fields. However, because activity recognition in the new domains suffers from various real problems such as the lack of sufficient training data and complexity of target activities, new solutions have been proposed for the practical problems in applying activity recognition to real-world applications in the new domains. In this seminar, we introduce recent topics in activity recognition from the viewpoints of (1) recent trends in state-of-the-art machine learning methods for practical activity recognition, (2) recently focused domains for human activity recognition such as industrial and medical domains and their public datasets, and (3) applications of activity recognition to the natural science field, especially in animal behavior understanding.Maekawa T., Xia Q., Otsuka R., et al. Recent Trends in Sensor-based Activity Recognition. Proceedings - IEEE International Conference on Mobile Data Management 2023-July, 36 (2023); https://doi.org/10.1109/MDM58254.2023.00018

Significance of differential expression of thymidylate synthase in normal and primary tumor tissues from patients with colorectal cancer

The role of thymidylate synthase (TS) is essential as a key rate-limiting enzyme in DNA synthesis. It is the primary target of fluorouracil and its derivates in colorectal cancer. In this study, TS mRNA expression was examined in primary tumor and normal tissues from 76 patients with high- risk stage II/III colorectal cancer by laser capture microdissection and polymerase chain reaction. Thirty (39.47%) patients were found to have higher TS expression in primary tumors with earlier stage (P = 0.018), lower histological grades (P = 0.001) and high frequency microsatellite instability (P = 0.000). Multivariate analysis showed that microsatellite instability, histological grade and number of lymph nodes examined are independent prognostic markers

Detection of various fusion genes by one-step RT-PCR and the association with clinicopathological features in 242 cases of soft tissue tumor

Introduction: Over the past decades, an increasing number of chromosomal translocations have been found in different STSs, which not only has value for clinical diagnosis but also suggests the pathogenesis of STS. Fusion genes can be detected by FISH, RT-PCR, and next-generation sequencing. One-step RT-PCR is a convenient method to detect fusion genes with higher sensitivity and lower cost.Method: In this study, 242 cases of soft tissue tumors were included, which were detected by one-step RT-PCR in multicenter with seven types of tumors: rhabdomyosarcoma (RMS), peripheral primitive neuroectodermal tumor (pPNET), synovial sarcoma (SS), myxoid liposarcomas (MLPS), alveolar soft part sarcoma (ASPS), dermatofibrosarcoma protuberans (DFSP), and soft tissue angiofibroma (AFST). 18 cases detected by one-step RT-PCR were further tested by FISH. One case with novel fusion gene detected by RNA-sequencing was further validated by one-step RT-PCR.Results: The total positive rate of fusion genes was 60% (133/213) in the 242 samples detected by one-step RT-PCR, in which 29 samples could not be evaluated because of poor RNA quality. The positive rate of PAX3–FOXO1 was 88.6% (31/35) in alveolar rhabdomyosarcoma, EWSR1–FLI1 was 63% (17/27) in pPNET, SYT–SSX was 95.4% in SS (62/65), ASPSCR1–TFE3 was 100% in ASPS (10/10), FUS–DDIT3 was 80% in MLPS (4/5), and COL1A1–PDGFB was 66.7% in DFSP (8/12). For clinicopathological parameters, fusion gene status was correlated with age and location in 213 cases. The PAX3–FOXO1 fusion gene status was correlated with lymph node metastasis and distant metastasis in RMS. Furthermore, RMS patients with positive PAX3–FOXO1 fusion gene had a significantly shorter overall survival time than those patients with the negative fusion gene. Among them, the FISH result of 18 cases was concordant with one-step RT-PCR. As detected as the most common fusion types of AHRR–NCOA2 in one case of AFST were detected as negative by one-step RT-PCR. RNA-sequencing was used to determine the fusion genes, and a novel fusion gene PTCH1–PLAG1 was found. Moreover, the fusion gene was confirmed by one-step RT-PCR.Conclusion: Our study indicates that one-step RT-PCR displays a reliable tool to detect fusion genes with the advantage of high accuracy and low cost. Moreover, it is a great tool to identify novel fusion genes. Overall, it provides useful information for molecular pathological diagnosis and improves the diagnosis rate of STSs

A high interferon gamma signature of CD8+ T cells predicts response to neoadjuvant immunotherapy plus chemotherapy in gastric cancer

BackgroundWhile the tumor microenvironment (TME) affects immune checkpoint blockade (ICB) efficacy, ICB also reshapes the characteristics of TME. Thus far, studies have focused on the TME evolution during neoadjuvant or adjuvant ICB therapy in gastric cancer (GC). However, the interaction between TME characteristics and neoadjuvant immunotherapy plus chemotherapy remains to be elucidated.MethodsWe performed single-cell RNA sequencing on ten GC specimens pre- and post-neoadjuvant camrelizumab plus mFOLFOX6 to determine the impact of the TME on the efficacy of the combination therapy and the remodeling of TME by the therapy.ResultsA high baseline interferon gamma (IFN-γ) signature in CD8+ T cells predicts better responses to the combination therapy. We also observed that the IFN-γ signature significantly decreased in multiple cell types, and the exhausted signature of CD8+ T cells was significantly suppressed during the neoadjuvant therapy.ConclusionsOur data reveal interactions between the TME and neoadjuvant immunotherapy plus chemotherapy in GC. Importantly, it also highlights the signature of CD8+ T cells in predicting response to the combination therapy in GC

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (D500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-beta levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-beta responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.Peer reviewe

Bacillus pumilus WP8 exhibits biocontrol efficacy against tomato bacterial wilt via attenuation of the virulence of the pathogenic bacterium

Bacillus pumilus WP8 is a plant growth-promoting rhizobacterium (PGPR) with good biocontrol efficacy against tomato bacterial wilt caused by Ralstonia solanacearum Rs1115. Biocontrol, however, is not due to antagonism of the pathogenic bacterium. Thus, we hypothesised that the biocontrol efficacy of WP8 was achieved by attenuation of Rs1115 virulence. Here, pot experiments for comparison of Rs1115 in different plant parts were conducted to investigate the ability of WP8 to prevent entry of Rs1115 into the regions of the plant above ground. Primary and secondary metabolite contents of WP8 and their inhibitory effects on twitching and swarming motilities of Rs1115 were determined by microscopic examination and crystal violet staining. The effects of WP8 metabolites on the expression of typical virulence genes in Rs1115 were established by quantitative PCR. Rs1115 abundance in the rhizosphere increased with time after inoculation. However, the shoots treated with WP8 were pathogen-free on days 3 and 6 after inoculation. In the WP8 + Rs1115 treatment group, the abundance of Rs1115 in shoots was 1.5 lg units higher on day 9 post-inoculation than that in the Rs1115 treatment group, while less Rs1115 was observed in the leaves. This indicated that WP8 prevented Rs1115 from spreading to the regions of the plant above ground. Furthermore, some heat-resistant secondary metabolites of WP8 (e.g. lipopeptides) inhibited the twitching and swarming motility of Rs1115. Moreover, the metabolites decreased the expression of typical virulence genes in Rs1115. Therefore, WP8 was shown to attenuate Rs1115 virulence, possibly through pumilacidin secretion

Recent Trends in Sensor-based Activity Recognition

Maekawa T., Xia Q., Otsuka R., et al. Recent Trends in Sensor-based Activity Recognition. Proceedings - IEEE International Conference on Mobile Data Management 2023-July, 36 (2023); https://doi.org/10.1109/MDM58254.2023.00018.This seminar introduces recent trends in sensor-based activity recognition technology. Technology to recognize human activities using sensors has been a hot topic in the field of mobile and ubiquitous computing for many years. Recent developments in deep learning and sensor technology have expanded the application of activity recognition to various domains such as industrial and natural science fields. However, because activity recognition in the new domains suffers from various real problems such as the lack of sufficient training data and complexity of target activities, new solutions have been proposed for the practical problems in applying activity recognition to real-world applications in the new domains. In this seminar, we introduce recent topics in activity recognition from the viewpoints of (1) recent trends in state-of-the-art machine learning methods for practical activity recognition, (2) recently focused domains for human activity recognition such as industrial and medical domains and their public datasets, and (3) applications of activity recognition to the natural science field, especially in animal behavior understanding