A four-dimensional organoid system to visualize cancer cell vascular invasion

Yanagisawa, K.; Konno, M.; Liu, H.; Irie, S.; Mizushima, T.; Mori, M.; Doki, Y.; Eguchi, H.; Matsusaki, M.; Ishii, H. A Four-Dimensional Organoid System to Visualize Cancer Cell Vascular Invasion. Biology 2020, 9, 361

Efficacy of human resource development program for young industry personnel who will be involved in future medical device development

Background: Training next-generation personnel from small/medium enterprises (SMEs) is an urgent issue in promoting medical device research and development (R&D). Since 2014 we have engaged in governmentally funded human resource development program for medical/non-medical SMEs, and have assessed its effectiveness by analyzing self-evaluation of achievement level (SEAL) data obtained before and after the training course. Methods: Human resource development experts interviewed 34 key opinion leaders with deep knowledge of medical device R&D from industry, government, and academia. The skills required for R&D personnel were written down, and a set of skills was created by making a greatest common measure in the list of common elements among them. Using that skill sets, skill evaluations were conducted on trainees at “Osaka University Training Course,” twice before participation and after completion of the entire program using SEAL assessment. Results: There were 97 men and 25 women, with one-third in the’30 s. Among them, 61 participants (50%) were from R&D divisions, and 32 (26%) were from business/sales divisions. 94 (77%) were from medical SMEs, and 28 (23%) were from non-medical SMEs (new entry). After completing the training course, significant growth was observed in every item of both Soft and Hard skill sets. Especially in new entry SME members, a striking improvement was observed in practical medical knowledge to enhance communication with medical doctors (p < 0.0001). Conclusion: Our training course, though 7-day-short in total, showed that both Soft and Hard skills could be improved in young medical/non-medical SME members. Further assessment is needed to establish the necessary skill sets for our future partners from industries, to foster the creation of innovative medical devices through med-tech collaboration.The version of record of this article, first published in Surgical Endoscopy, is available online at Publisher’s website: https://doi.org/10.1007/s00464-023-10474-

Convolutional neural network can recognize drug resistance of single cancer cells

It is known that single or isolated tumor cells enter cancer patients' circulatory systems. These circulating tumor cells (CTCs) are thought to be an effective tool for diagnosing cancer malignancy. However, handling CTC samples and evaluating CTC sequence analysis results are challenging. Recently, the convolutional neural network (CNN) model, a type of deep learning model, has been increasingly adopted for medical image analyses. However, it is controversial whether cell characteristics can be identified at the single-cell level by using machine learning methods. This study intends to verify whether an AI system could classify the sensitivity of anticancer drugs, based on cell morphology during culture. We constructed a CNN based on the VGG16 model that could predict the efficiency of antitumor drugs at the single-cell level. The machine learning revealed that our model could identify the effects of antitumor drugs with ~0.80 accuracies. Our results show that, in the future, realizing precision medicine to identify effective antitumor drugs for individual patients may be possible by extracting CTCs from blood and performing classification by using an AI system

Changing the preferred direction of the refined topological vertex

We consider the issue of the slice invariance of refined topological string amplitudes, which means that they are independent of the choice of the preferred direction of the refined topological vertex. We work out two examples. The first example is a geometric engineering of five-dimensional U(1) gauge theory with a matter. The slice invariance follows from a highly non-trivial combinatorial identity which equates two known ways of computing the chi_y genus of the Hilbert scheme of points on C^2. The second example is concerned with the proposal that the superpolynomials of the colored Hopf link are obtained from a refinement of topological open string amplitudes. We provide a closed formula for the superpolynomial, which confirms the slice invariance when the Hopf link is colored with totally anti-symmetric representations. However, we observe a breakdown of the slice invariance for other representations.Comment: 35 pages, 3 figures; (v3) a few improvements, references update

Difference between carbohydrate antigen 19-9 and fluorine-18 fluorodeoxyglucose positron emission tomography in evaluating the treatment efficacy of neoadjuvant treatment in patients with resectable and borderline resectable pancreatic ductal adenocarcinoma: Results of a dual-center study

kita, H, Takahashi, H, Eguchi, H, et al. Difference between carbohydrate antigen 19‐9 and fluorine‐18 fluorodeoxyglucose positron emission tomography in evaluating the treatment efficacy of neoadjuvant treatment in patients with resectable and borderline resectable pancreatic ductal adenocarcinoma: Results of a dual‐center study. Ann Gastroenterol Surg. 2020; 00: 1– 9. https://doi.org/10.1002/ags3.12418

Establishment of an antibody specific for cancer-associated haptoglobin: a possible implication of clinical investigation

We previously found that the serum level of fucosylated haptoglobin (Fuc-Hpt) was significantly increased in pancreatic cancer patients. To delineate the mechanism underlying this increase and develop a simple detection method, we set out to generate a monoclonal antibody (mAb) specific for Fuc-Hpt. After multiple screenings by enzyme-linked immunosorbent assay (ELISA), a 10-7G mAb was identified as being highly specific for Fuc-Hpt generated in a cell line as well as for Hpt derived from a pancreatic cancer patient. As a result from affinity chromatography with 10-7G mAb, followed by lectin blot and mass spectrometry analyses, it was found that 10-7G mAb predominantly recognized both Fuc-Hpt and prohaptoglobin (proHpt), which was also fucosylated. In immunohistochemical analyses, hepatocytes surrounding metastasized cancer cells were stained by the 10-7G mAb, but neither the original cancer cells themselves nor normal hepatocytes exhibited positive staining, suggesting that metastasized cancer cells promote Fuc-Hpt production in adjacent hepatocytes. Serum level of Fuc-Hpt determined with newly developed ELISA system using the 10-7G mAb, was increased in patients of pancreatic and colorectal cancer. Interestingly, dramatic increases in Fuc-Hpt levels were observed at the stage IV of colorectal cancer. These results indicate that the 10-7G mAb developed is a promising antibody which recognizes Fuc-Hpt and could be a useful diagnostic tool for detecting liver metastasis of cancer.This study was performed as a research program of the Project for Development of Innovative Research on Cancer Therapeutics (P-Direct), Ministry of Education, Culture, Sports, Science and Technology of Japan and was supported by JSPS KAKENHI Grant Number JP16H05226

Free Boson Realization of Uq(slN^)U_q(\widehat{sl_N})

We construct a realization of the quantum affine algebra $U_q(\widehat{sl_N})$ of an arbitrary level $k$ in terms of free boson fields. In the $q\!\rightarrow\! 1$ limit this realization becomes the Wakimoto realization of $\widehat{sl_N}$. The screening currents and the vertex operators(primary fields) are also constructed; the former commutes with $U_q(\widehat{sl_N})$ modulo total difference, and the latter creates the $U_q(\widehat{sl_N})$ highest weight state from the vacuum state of the boson Fock space.Comment: 24 pages, LaTeX, RIMS-924, YITP/K-101

Pancreatic Cancer Research beyond DNA Mutations

Pancreatic ductal adenocarcinoma (PDAC) is caused by genetic mutations in four genes: KRAS proto-oncogene and GTPase (KRAS), tumor protein P53 (TP53), cyclin-dependent kinase inhibitor 2A (CDKN2A), and mothers against decapentaplegic homolog 4 (SMAD4), also called the big 4. The changes in tumors are very complex, making their characterization in the early stages challenging. Therefore, the development of innovative therapeutic approaches is desirable. The key to overcoming PDAC is diagnosing it in the early stages. Therefore, recent studies have investigated the multifaced characteristics of PDAC, which includes cancer cell metabolism, mesenchymal cells including cancer-associated fibroblasts and immune cells, and metagenomics, which extend to characterize various biomolecules including RNAs and volatile organic compounds. Various alterations in the KRAS-dependent as well as KRAS-independent pathways are involved in the refractoriness of PDAC. The optimal combination of these new technologies is expected to help treat intractable pancreatic cancer

Metabolic system alterations in pancreatic cancer patient serum: potential for early detection

BACKGROUND: The prognosis of pancreatic cancer (PC) is one of the poorest among all cancers, due largely to the lack of methods for screening and early detection. New biomarkers for identifying high-risk or early-stage subjects could significantly impact PC mortality. The goal of this study was to find metabolic biomarkers associated with PC by using a comprehensive metabolomics technology to compare serum profiles of PC patients to healthy control subjects. METHODS: A non-targeted metabolomics approach based on high-resolution, flow-injection Fourier transform ion cyclotron resonance mass spectrometry (FI-FTICR-MS) was used to generate comprehensive metabolomic profiles containing 2478 accurate mass measurements from the serum of Japanese PC patients (n=40) and disease-free subjects (n=50). Targeted flow-injection tandem mass spectrometry (FI-MS/MS) assays for specific metabolic systems were developed and used to validate the FI-FTICR-MS results. A FI-MS/MS assay for the most discriminating metabolite discovered by FI-FTICR-MS (PC-594) was further validated in two USA Caucasian populations; one comprised 14 PCs, six intraductal papillary mucinous neoplasims (IPMN) and 40 controls, and a second comprised 1000 reference subjects aged 30 to 80, which was used to create a distribution of PC-594 levels among the general population. RESULTS: FI-FTICR-MS metabolomic analysis showed significant reductions in the serum levels of metabolites belonging to five systems in PC patients compared to controls (all p<0.000025). The metabolic systems included 36-carbon ultra long-chain fatty acids, multiple choline-related systems including phosphatidylcholines, lysophosphatidylcholines and sphingomyelins, as well as vinyl ether-containing plasmalogen ethanolamines. ROC-AUCs based on FI-MS/MS of selected markers from each system ranged between 0.93 ±0.03 and 0.97 ±0.02. No significant correlations between any of the systems and disease-stage, gender, or treatment were observed. Biomarker PC-594 (an ultra long-chain fatty acid), was further validated using an independently-collected US Caucasian population (blinded analysis, n=60, p=9.9E-14, AUC=0.97 ±0.02). PC-594 levels across 1000 reference subjects showed an inverse correlation with age, resulting in a drop in the AUC from 0.99 ±0.01 to 0.90 ±0.02 for subjects aged 30 to 80, respectively. A PC-594 test positivity rate of 5.0% in low-risk reference subjects resulted in a PC sensitivity of 87% and a significant improvement in net clinical benefit based on decision curve analysis. CONCLUSIONS: The serum metabolome of PC patients is significantly altered. The utility of serum metabolite biomarkers, particularly PC-594, for identifying subjects with elevated risk of PC should be further investigated