Pancreatic cancer remains a major challenge in oncology due to its poor prognosis as it is symptomatically dormant and is found in later intractable stages. This study aims to validate the robustness and versatility of a diagnostic framework combining Probe Electrospray Ionization Mass Spectrometry (PESI-MS) and machine learning models for early PDAC detection across different ethnicities. Building on our previous study that demonstrated high sensitivity and specificity in a Taiwanese PDAC high-risk and PDAC patient cohort, we used those prebuilt models on an independent cohort of 38 Japanese patients diagnosed with pancreatic cancer. The model assessed sustained its performance on the Japanese cohort, correctly identifying 97% of all cancer cases, indicating robustness to demographic differences. Moreover, enhancing the original model with dimensionality reduction achieved 100% sensitivity, correctly detecting every cancer case. These findings underscore the potential of PESI-MS and machine learning as universal diagnostic tools for PDAC, with significant implications for early detection that improves patient outcomes. The findings advocate for further validation in larger, multi-ethnic studies to confirm the clinical implementation of this approach and its integration into global screening strategies for high-risk populations.

Background & aims: Metabolic dysfunction–associated steatotic liver disease (MASLD) leads to liver cirrhosis and is therefore a major public health concern worldwide. Although plasma/serum phospholipids are proposed non-invasive biomarkers of MASLD progression, they have not been put into clinical practice, in part because the mechanism underlying their efficacy remains unknown. We therefore evaluated serum phospholipid profiles to develop a novel biomarker for assessing the extent of liver fibrosis in MASLD patients and elucidate the underlying mechanism in this cross-sectional study. Approach & results: Liquid chromatography–tandem mass spectrometry was used to comprehensively analyze serum phospholipid profiles in 100 patients with clinically diagnosed MASLD. Phospholipid profiles were associated with laboratory data and fibrosis grade in liver biopsy. MASLD patients with liver fibrosis exhibited distinct changes in serum phospholipids, characterized by reduced sphingomyelin and phosphatidylcholine levels and elevated phosphatidylethanolamine levels. Based on these phospholipid changes, we developed a fibrosis prediction model that outperformed other serum biomarkers. We also elucidated the underlying mechanism of these phospholipid changes in relation to serum lipoproteins and liver transcriptomics. Specifically, a significant correlation between serum sphingomyelin and LDL-cholesterol levels was identified. Reduced serum LDL-cholesterol levels could be attributed to fibrotic liver and down-regulated expression of LIPC, which encodes the hepatic lipase that catalyzes LDL-cholesterol synthesis. Conclusions: Serum phospholipid profiles represent an effective biomarker of liver fibrosis and help enhance understanding of the pathology of MASLD.

Choroid plexus epithelial cells (CPECs) contribute to the production of cerebrospinal fluid (CSF), which plays an important role in maintaining the milieu intérieur of the central nervous system. To elucidate the function of CPECs, in vitro primary culture is an ideal system as the choroid plexus (CP) is situated deep in the brain ventricular system in situ. This location makes detailed analysis of these cells difficult. Moreover, its highly undulating nature prevents quantitative study using molecular and cell biological tools. The protocols herein describe primary culture of CPECs in a differentiated state, in a well-integrated monolayer sheet that recapitulates the in vivo blood-cerebrospinal fluid barrier, to enable study of fluid transcytosis through the cytoplasm.

Most discussions about discrimination and bias in anatomical research papers have been limited to terminology relating to race/ethnicity and gender/sex. However, as editors of anatomical journals, the authors of this article have frequently observed broader instances of potential discrimination and bias within anatomical research. These often stem from differences among authors' backgrounds, traditions, cultures, religions, provenance/origins, and workplace affiliations. In view of the limited discourse on this topic, we seek in this article to establish a consensus among editors of anatomical journals and to propose new Guidelines Against Discrimination and Bias in Anatomical Research Papers (GDBARP). We have identified multiple factors that can contribute to discrimination and bias, underscoring the need for greater awareness and proactive measures. It is imperative in anatomical research to respect authors, reviewers, and editors regardless of their background, culture, traditions, sex, ethnicity, language, religion, or ethical perspectives.

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.

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.

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.

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 β (TGF-β) 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-β 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.

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.

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.