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The number of people afflicted with oral carcinoma in Japan has increased in recent years. Although preoperative neoadjuvant therapy with cisplatin and 5-fluorouracil are performed, chemotherapeutic response varies widely among the patients. With the aim of establishing novel indices to predict the therapeutic response to chemotherapy, we investigated the relationship between morphological features of pre-treatment oral carcinoma nuclei and the chemotherapeutic response using quantifying morphology of cell nuclei in pathological specimen images. We measured 4 morphological features of the nucleus of oral squamous cell carcinoma cases classified by the response to chemotherapy: No Change (NC) group, Partial Response (PR) group and Complete Response (CR) group. Furthermore, we performed immunohistochemical staining for p53 and Ki67 and calculated their positive rates in cancer tissues. Compactness and symmetry of the nucleus were significantly higher and nuclear edge response was significantly lower in cancer cells with lower chemotherapeutic responses compared high chemotherapeutic responders. As for positive rates of p53 and Ki67, there were no significant differences between any of the response groups. Morphological features of cancer cell nuclei in pathological specimens are sensitive predictive factors for the chemotherapeutic response to oral squamous cell carcinoma. [ABSTRACT FROM AUTHOR]

Abstract: Five bacterial strains capable of utilizing 17β-estradiol (E2) and estrone (E1) were isolated from soil samples. Using their morphological and physiological features and 16S rDNA sequences, we classified these isolates into two groups: Group A (Rhodococcus sp. strains ED6, ED7, and ED10) and Group B (Sphingomonas sp. strains ED8 and ED9). All isolates used E2 and E1 as the sole carbon sources and showed high E1 and E2 degradation activities. In all strains, more than 50% of 0.8 mg of E1 or E2 was degraded in 4 mL of inorganic medium over 24 h, and 90% was degraded over 120 h. By incubating the resting ED8 cells with E2 and the meta-cleavage inhibitor 3-chlorocatechol, we identified two metabolites, 4-hydroxyestrone (4-OH-E1) and 4-hydroxyestradiol (4-OH-E2), and confirmed their identity using authentic chemicals. The 4-OH-E1 and 4-OH-E2 compounds were assumed to be intermediate metabolites formed before meta-cleavage, as they were not identified in culture without 3-chlorocatechol. Degradation of E2 by strain ED8 can be initiated by hydroxylation of the C-4 position, followed by meta-cleavage of the benzene ring. When strains ED8 degraded E2, we further identified hydroxy-E2, keto-E1 and -E2, and an additional degradation product via mass spectrometry. The presence of these compounds implied degradation through a second pathway initiated through an attack of the saturated ring. [Copyright &y& Elsevier]

The development of next-generation sequencing (NGS) has enabled the discovery of cancer-specific driver gene alternations, making precision medicine possible. However, accurate genetic testing requires a sufficient amount of tumor cells in the specimen. The evaluation of tumor content ratio (TCR) from hematoxylin and eosin (H&E)-stained images has been found to vary between pathologists, making it an important challenge to obtain an accurate TCR. In this study, three pathologists exhaustively labeled all cells in 41 regions from 41 lung cancer cases as either tumor, non-tumor or indistinguishable, thus establishing a "gold standard" TCR. We then compared the accuracy of the TCR estimated by 13 pathologists based on visual assessment and the TCR calculated by an AI model that we have developed. It is a compact and fast model that follows a fully convolutional neural network architecture and produces cell detection maps which can be efficiently post-processed to obtain tumor and non-tumor cell counts from which TCR is calculated. Its raw cell detection accuracy is 92% while its classification accuracy is 84%. The results show that the error between the gold standard TCR and the AI calculation was significantly smaller than that between the gold standard TCR and the pathologist's visual assessment ( p < 0.05 ). Additionally, the robustness of AI models across institutions is a key issue and we demonstrate that the variation in AI was smaller than that in the average of pathologists when evaluated by institution. These findings suggest that the accuracy of tumor cellularity assessments in clinical workflows is significantly improved by the introduction of robust AI models, leading to more efficient genetic testing and ultimately to better patient outcomes. [ABSTRACT FROM AUTHOR]

Abstract: Each chromosome occupies its own-specific space called a ‘territory’ within the interphase nucleus, and the arrangement of chromosome territories (CTs) is important in epigenetic mechanisms. The molecular mechanism to determine the positioning of CTs, however, remains unknown. On the other hand, dioxin is known to be the typical environmental pollutant that affects a wide variety of biological events in many species. Here, we show that dioxin enlarges the minimum distance between chromosome 12 and chromosome 16 territories in human preadipocyte cells, and the alteration of chromosome positioning is canceled by an aryl hydrocarbon receptor (AhR) antagonist α-naphthoflavone. Thus, AhR may be a key molecule to regulate chromosome positioning. Our results suggest a novel effect of dioxin toxicity, and demonstrate a clue to reveal the novel molecular mechanism for the arrangement of CTs. [Copyright &y& Elsevier]