Identification of TEKTIN1-expressing multiciliated cells during spontaneous differentiation of non-human primate embryonic stem cells.

Tektins are a group of microtubule-stabilizing proteins necessary for cilia and flagella assembly. TEKTIN1 (TEKT1) is used as a sperm marker for monitoring germ cell differentiation in embryonic stem (ES) and induced pluripotent stem (iPS) cells. Although upregulation of TEKT1 has been reported during spontaneous differentiation of ES and iPS cells, it is unclear which cells express TEKT1. To identify TEKT1-expressing cells, we established an ES cell line derived from cynomolgus monkeys (Macaca fascicularis), which expresses Venus controlled by the TEKT1 promoter. Venus expression was detected at 5 weeks of differentiation on the surface of the embryoid body (EB), and it gradually increased with the concomitant formation of a leash-like structure at the EB periphery. Motile cilia were observed on the surface of the Venus-positive leash-like structure after 8 weeks of differentiation. The expression of cilia markers as well as TEKT1-5 and 9 + 2 microtubule structures, which are characteristic of motile cilia, were detected in Venus-positive cells. These results demonstrated that TEKT1-expressing cells are multiciliated epithelial-like cells that form a leash-like structure during the spontaneous differentiation of ES and iPS cells. These findings will provide a new research strategy for studying cilia biology, including ciliogenesis and ciliopathies.

The Rab GTPase-binding protein EHBP1L1 and its interactors CD2AP/CIN85 negatively regulate the length of primary cilia via actin remodeling.

Primary cilia are organelles consisting of axonemal microtubules and plasma membranes, and they protrude from the cell surface to the extracellular region and function in signal sensing and transduction. The integrity of cilia, including the length and structure, is associated with signaling functions; however, factors involved in regulating the integrity of cilia have not been fully elucidated. Here, we showed that the Rab GTPase-binding protein EHBP1L1 and its newly identified interactors CD2AP and CIN85, known as adaptor proteins of actin regulators, are involved in ciliary length control. Immunofluorescence microscopy showed that EHBP1L1 and CD2AP/CIN85 are localized to the ciliary sheath. EHBP1L1 depletion caused mislocalization of CD2AP/CIN85, suggesting that CD2AP/CIN85 localization to the ciliary sheath is dependent on EHBP1L1. Additionally, we determined that EHBP1L1- and CD2AP/CIN85-depleted cells had elongated cilia. The aberrantly elongated cilia phenotype and the ciliary localization defect of CD2AP/CIN85 in EHBP1L1-depleted cells were rescued by the expression of WT EHBP1L1, although this was not observed in the CD2AP/CIN85-binding-deficient mutant, indicating that the EHBP1L1-CD2AP/CIN85 interaction is crucial for controlling ciliary length. Furthermore, EHBP1L1- and CD2AP/CIN85-depleted cells exhibited actin nucleation and branching defects around the ciliary base. Taken together, our data demonstrate that the EHBP1L1-CD2AP/CIN85 axis negatively regulates ciliary length via actin network remodeling around the basal body.

New Diagnostic Modality Combining Mass Spectrometry and Machine Learning for the Discrimination of Malignant Intraductal Papillary Mucinous Neoplasms.

BACKGROUND: An intraductal papillary mucinous neoplasm (IPMN) is a pancreatic tumor with malignant potential. Although we anticipate a sensitive method to diagnose the malignant conversion of IPMN, an effective strategy has not yet been established. The combination of probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning provides a promising solution for this purpose. METHODS: We prospectively analyzed 42 serum samples obtained from IPMN patients who underwent pancreatic resection between 2020 and 2021. Based on the postoperative pathological diagnosis, patients were classified into two groups: IPMN-low grade dysplasia (n = 17) and advanced-IPMN (n = 25). Serum samples were analyzed by PESI-MS, and the obtained mass spectral data were converted into continuous variables. These variables were used to discriminate advanced-IPMN from IPMN-low grade dysplasia by partial least square regression or support vector machine analysis. The areas under receiver operating characteristics curves were obtained to visualize the difference between the two groups. RESULTS: Partial least square regression successfully discriminated the two disease classes. From another standpoint, we selected 130 parameters from the entire dataset by PESI-MS, which were fed into the support vector machine. The diagnostic accuracy was 88.1%, and the area under the receiver operating characteristics curve was 0.924 by this method. Approximately 10 min were required to perform each method. CONCLUSION: PESI-MS combined with machine learning is an easy-to-use tool with the advantage of rapid on-site analysis. Here, we show the great potential of our system to diagnose the malignant conversion of IPMN, which would be a promising diagnostic tool in clinical settings.

KIF3B promotes a PI3K signaling gradient causing changes in a Shh protein gradient and suppressing polydactyly in mice.

Digit determination in limb buds is driven by a posteriorizing Sonic hedgehog (Shh) protein gradient; however, the mechanism regulating this is unclear. Here, we propose a diffusion-and-trapping hypothesis for Shh gradient formation based on data from the preaxial polydactyly phenotype of KIF3B motor hypomorphic mice. In the limb buds of these mice, a distal-to-proximal gradient of fibroblast growth factor (FGF) and phosphatidylinositol 3-kinase (PI3K) signaling and a posterior-to-anterior gradient of Shh were disorganized. This phenotype was reproduced by transplanting FGF8b-soaked beads. At the subcellular level, KIF3B transported the phosphatase and tensin homolog (PTEN)-like phosphatase Talpid3 to terminate PI3K signaling. High and low PI3K signaling strengths differentially sorted endocytosed Shh toward exosome-like particles and cytonemal punctata, respectively. These results indicate that the Shh-containing particles undergo either the diffusional movement in the periphery or cytonemal trapping in the center and form a spatial gradient along the periphery of developing limb buds.

Probe electrospray ionization mass spectrometry-based rapid diagnosis of liver tumors.

BACKGROUND AND AIM: Prompt differential diagnosis of liver tumors is clinically important and sometimes difficult. A new diagnostic device that combines probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning may help provide the differential diagnosis of liver tumors. METHODS: We evaluated the diagnostic accuracy of this new PESI-MS device using tissues obtained and stored from previous surgically resected specimens. The following cancer tissues (with collection dates): hepatocellular carcinoma (HCC, 2016-2019), intrahepatic cholangiocellular carcinoma (ICC, 2014-2019), and colorectal liver metastasis (CRLM, 2014-2019) from patients who underwent hepatic resection were considered for use in this study. Non-cancerous liver tissues (NL) taken from CRLM cases were also incorporated into the analysis. Each mass spectrum provided by PESI-MS was tested using support vector machine, a type of machine learning, to evaluate the discriminatory ability of the device. RESULTS: In this study, we used samples from 91 of 139 patients with HCC, all 24 ICC samples, and 103 of 202 CRLM samples; 80 NL from CRLM cases were also used. Each mass spectrum was obtained by PESI-MS in a few minutes and was evaluated by machine learning. The sensitivity, specificity, and diagnostic accuracy of the PESI-MS device for discriminating HCC, ICC, and CRLM from among a mix of all three tumors and from NL were 98.9%, 98.1%, and 98.3%; 87.5%, 93.1%, and 92.6%; and 99.0%, 97.9%, and 98.3%, respectively. CONCLUSION: This study demonstrated that PESI-MS and machine learning could discriminate liver tumors accurately and rapidly.

Depletion of Ift88 in thymic epithelial cells affects thymic synapse and T-cell differentiation in aged mice.

Primary cilia are ubiquitous hair-like organelles, usually projecting from the cell surface. They are essential for the organogenesis and homeostasis of various physiological functions, and their dysfunction leads to a plethora of human diseases. However, there are few reports on the role of primary cilia in the immune system; therefore, we focused on their role in the thymus that nurtures immature lymphocytes to full-fledged T cells. We detected primary cilia on the thymic epithelial cell (TEC) expressing transforming growth factor ß (TGF-ß) receptor in the basal body, and established a line of an intraflagellar transport protein 88 (Ift88) knockout mice lacking primary cilia in TECs (Ift88-TEC null mutant) to clarify their precise role in thymic organogenesis and T-cell differentiation. The Ift88-TEC null mutant mice showed stunted cilia or lack of cilia in TECs. The intercellular contact between T cells and the "thymic synapse" of medullary TECs was slightly disorganized in Ift88-TEC null mutants. Notably, the CD4- and CD8-single positive thymocyte subsets increased significantly. The absence or disorganization of thymic cilia downregulated the TGF-ß signaling cascade, increasing the number of single positive thymocytes. To our knowledge, this is the first study reporting the physiological role of primary cilia and Ift88 in regulating the differentiation of the thymus and T cells.

Standardized statement for the ethical use of human cadaveric tissues in anatomy research papers: Recommendations from Anatomical Journal Editors-in-Chief.

Human cadaveric donors are essential for research in the anatomical sciences. However, many research papers in the anatomical sciences often omit a statement regarding the ethical use of the donor cadavers or, as no current standardized versions exist, use language that is extremely varied. To rectify this issue, 22 editors-in-chief of anatomical journals, representing 17 different countries, developed standardized and simplified language that can be used by authors of studies that use human cadaveric tissues. The goal of these editor recommendations is to standardize the writing approach by which the ethical use of cadaveric donors is acknowledged in anatomical studies that use donor human cadavers. Such sections in anatomical papers will help elevate our discipline and promote standardized language use in others non anatomy journals and also other media outlets that use cadaveric tissues.

New strategy for evaluating pancreatic tissue specimens from endoscopic ultrasound-guided fine needle aspiration and surgery.

BACKGROUND AND AIM: Preoperative histological evaluation of pancreatic neoplasms is important for guiding the resection strategy and preventing postoperative adverse events. However, conventional endoscopic methods have technical limitations that reduce the accuracy of the histopathological examination. Probe electrospray ionization mass spectrometry (PESI-MS) may be a useful technique for rapidly evaluating small specimens. METHODS: This single-center prospective study included patients with pancreatic neoplasms between October 2018 and December 2019. Pancreatic ductal adenocarcinoma (PDAC) specimens were obtained via endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) and non-neoplastic tissue was obtained via surgery. Specimens were subjected to PESI-MS and the mass spectra were analyzed using partial least squares regression-discriminant analysis. RESULTS: The study included 40 patients with 20 nonneoplastic specimens and 19 PDAC specimens (1 case of neuroendocrine carcinoma was omitted). All nonneoplastic specimens were sufficient for PESI-MS analysis, although only 7 of 19 PDAC specimens were sufficient for PESI-MS analysis because of poor sample quality or insufficient quantity (<1 mg). Among the 27 analyzed cases, the mass spectra clearly differentiated between the PDAC and nonneoplastic specimens. CONCLUSIONS: This study revealed that PESI-MS could differentiate between PDAC and nonneoplastic specimens, even in cases where EUS-FNA produced very small specimens.

Odontoblast differentiation is regulated by an interplay between primary cilia and the canonical Wnt pathway.

Primary cilium is a protruding cellular organelle that has various physiological functions, especially in sensory reception. While an avalanche of reports on primary cilia have been published, the function of primary cilia in dental cells remains to be investigated. In this study, we focused on the function of primary cilia in dentin-producing odontoblasts. Odontoblasts, like most other cell types, possess primary cilia, which disappear upon the knockdown of intraflagellar transport protein 88. In cilia-depleted cells, the expression of dentin sialoprotein, an odontoblastic marker, was elevated, while the deposition of minerals was slowed. This was recapitulated by the activation of canonical Wnt pathway, also decreased the ratio of ciliated cells. In dental pulp cells, as they differentiated into odontoblasts, the ratio of ciliated cells was increased, whereas the canonical Wnt signaling activity was repressed. Our results collectively underscore the roles of primary cilia in regulating odontoblastic differentiation through canonical Wnt signaling. This study implies the existence of a feedback loop between primary cilia and the canonical Wnt pathway.

Diagnostic significance of plasma lipid markers and machine learning-based algorithm for gastric cancer.

Biomarkers may be of value for the early detection of gastric cancer (GC) and the preoperative identification of tumor characteristics to guide treatment strategies. The present study analyzed the expression levels of phospholipids in plasma from patients with GC using liquid chromatography/electrospray ionization-mass spectrometry (LC/ESI-MS) to detect reliable biomarkers for GC. Furthermore, combining the results with a machine learning strategy, the present study attempted to establish a diagnostic system for GC. A total of 20 plasma samples from preoperative patients with GC and 16 plasma samples from tumor-free patients (controls) were selected from our biobank named 'SHINGEN (Yamanashi Biobank of Gastroenterological Cancers)', which includes a total of 1,592 plasma samples, and were analyzed by LC/ESI-MS. The obtained data were discriminated using a machine learning-based diagnostic algorithm, whose discriminant ability was confirmed through leave-one-out cross-validation. Using LC/ESI-MS, the levels of 236 lipid molecules were determined. Biomarker analysis revealed that a few lipids that were downregulated in the GC group could discriminate between the GC and control groups. Whole lipid composition analysis using partial least squares regression revealed good discrimination ability between the GC and control groups. Integrative analysis of all molecules using the aforementioned machine learning method exhibited a diagnostic accuracy of 94.4% (specificity, 93.8%; sensitivity, 95.0%). In conclusion, the outcomes of the present study suggested the potential future application of the aforementioned system in clinical settings. By accumulating more reliable data, the present system will be able to detect early-stage cancer and will be capable of predicting the efficacy of each therapeutic strategy.

A new rapid diagnostic system with ambient mass spectrometry and machine learning for colorectal liver metastasis.

BACKGROUND: Probe electrospray ionization-mass spectrometry (PESI-MS) can rapidly visualize mass spectra of small, surgically obtained tissue samples, and is a promising novel diagnostic tool when combined with machine learning which discriminates malignant spectrum patterns from others. The present study was performed to evaluate the utility of this device for rapid diagnosis of colorectal liver metastasis (CRLM). METHODS: A prospectively planned study using retrospectively obtained tissues was performed. In total, 103 CRLM samples and 80 non-cancer liver tissues cut from surgically extracted specimens were analyzed using PESI-MS. Mass spectra obtained by PESI-MS were classified into cancer or non-cancer groups by using logistic regression, a kind of machine learning. Next, to identify the exact molecules responsible for the difference between CRLM and non-cancerous tissues, we performed liquid chromatography-electrospray ionization-MS (LC-ESI-MS), which visualizes sample molecular composition in more detail. RESULTS: This diagnostic system distinguished CRLM from non-cancer liver parenchyma with an accuracy rate of 99.5%. The area under the receiver operating characteristic curve reached 0.9999. LC-ESI-MS analysis showed higher ion intensities of phosphatidylcholine and phosphatidylethanolamine in CRLM than in non-cancer liver parenchyma (P < 0.01, respectively). The proportion of phospholipids categorized as monounsaturated fatty acids was higher in CRLM (37.2%) than in non-cancer liver parenchyma (10.7%; P < 0.01). CONCLUSION: The combination of PESI-MS and machine learning distinguished CRLM from non-cancer tissue with high accuracy. Phospholipids categorized as monounsaturated fatty acids contributed to the difference between CRLM and normal parenchyma and might also be a useful diagnostic biomarker and therapeutic target for CRLM.

Natural Herbal Estrogen-Mimetics (Phytoestrogens) Promote the Differentiation of Fallopian Tube Epithelium into Multi-Ciliated Cells via Estrogen Receptor Beta.

Phytoestrogens are herbal polyphenolic compounds that exert various estrogen-like effects in animals and can be taken in easily from a foodstuff in daily life. The fallopian tube lumen, where transportation of the oocyte occurs, is lined with secretory cells and multi-ciliated epithelial cells. Recently, we showed that estrogen induces multi-ciliogenesis in the porcine fallopian tube epithelial cells (FTECs) through the activation of the estrogen receptor beta (ERß) pathway and simultaneous inhibition of the Notch pathway. Thus, ingested phytoestrogens may induce FTEC ciliogenesis and thereby affect the fecundity. To address this issue, we added isoflavones (genistein, daidzein, or glycitin) and coumestan (coumestrol) to primary culture FTECs under air-liquid interface conditions and assessed the effects of each compound. All phytoestrogens except glycitin induced multi-ciliated cell differentiation, which followed Notch signal downregulation. On the contrary, the differentiation of secretory cells decreased slightly. Furthermore, genistein and daidzein had a slight effect on the proportion of proliferating cells exhibited by Ki67 expression. Ciliated-cell differentiation is inhibited by the ERß antagonist, PHTPP. Thus, this study suggests that phytoestrogens can improve the fallopian tube epithelial sheet homeostasis by facilitating the genesis of multi-ciliated cells and this effect depends on the ERß-mediated pathway.

High-performance Collective Biomarker from Liquid Biopsy for Diagnosis of Pancreatic Cancer Based on Mass Spectrometry and Machine Learning.

Background: Most pancreatic cancers are found at progressive stages when they cannot be surgically removed. Therefore, a highly accurate early detection method is urgently needed. Methods: This study analyzed serum from Japanese patients who suffered from pancreatic ductal adenocarcinoma (PDAC) and aimed to establish a PDAC-diagnostic system with metabolites in serum. Two groups of metabolites, primary metabolites (PM) and phospholipids (PL), were analyzed using liquid chromatography/electrospray ionization mass spectrometry. A support vector machine was employed to establish a machine learning-based diagnostic algorithm. Results: Integrating PM and PL databases improved cancer diagnostic accuracy and the area under the receiver operating characteristic curve. It was more effective than the algorithm based on either PM or PL database, or single metabolites as a biomarker. Subsequently, 36 statistically significant metabolites were fed into the algorithm as a collective biomarker, which improved results by accomplishing 97.4% and was further validated by additional serum. Interestingly, specific clusters of metabolites from patients with preoperative neoadjuvant chemotherapy (NAC) showed different patterns from those without NAC and were somewhat comparable to those of the control. Conclusion: We propose an efficient screening system for PDAC with high accuracy by liquid biopsy and potential biomarkers useful for assessing NAC performance.