Perfusion System for Modification of Luminal Contents of Human Intestinal Organoids and Realtime Imaging Analysis of Microbial Populations

Intestinal organoids are 3D cell structures that replicate some aspects of organ function and are organized with a polarized epithelium facing a central lumen. To enable more applications, new technologies are needed to access the luminal cavity and apical cell surface of organoids. We developed a perfusion system utilizing a double-barrel glass capillary with a pressure-based pump to access and modify the luminal contents of a human intestinal organoid for extended periods of time while applying cyclic cellular strain. Cyclic injection and withdrawal of fluorescent FITC-Dextran coupled with real-time measurement of fluorescence intensity showed discrete changes of intensity correlating with perfusion cycles. The perfusion system was also used to modify the lumen of organoids injected with GFP-expressing E. coli. Due to the low concentration and fluorescence of the E. coli, a novel imaging analysis method utilizing bacteria enumeration and image flattening was developed to monitor E. coli within the organoid. Collectively, this work shows that a double-barrel perfusion system provides constant luminal access and allows regulation of luminal contents and luminal mixing.

Structure Based Innovative Approach to Analyze Aptaprobe-GPC3 Complexes in Hepatocellular Carcinoma

Background Glypican-3 (GPC3), a membrane-bound heparan sulfate proteoglycan, is a biomarker of hepatocellular carcinoma (HCC) progression. Aptamers specifically binding to target biomolecules have recently emerged as clinical disease diagnosis targets. Here, we describe 3D structure-based aptaprobe platforms for detecting GPC3, such as aptablotting, aptaprobe-based sandwich assay (ALISA), and aptaoptical imaging analysis. Results For preparing the aptaprobe–GPC3 platforms, we obtained 12 high affinity aptamer candidates (GPC3_1 to GPC3_12) that specifically bind to target GPC3 molecules. Structure-based molecular interactions identified distinct aptatopic residues responsible for binding to the paratopic nucleotide sequences (nt-paratope) of GPC3 aptaprobes. Sandwichable and overlapped aptaprobes were selected through structural analysis. The aptaprobe specificity for using in HCC diagnostics were verified through Aptablotting and ALISA. Moreover, Aptaoptical imaging showed that the binding property of GPC3_3 and their GPC3 specificity were maintained in HCC xenograft models, which may indicate a new HCC imaging diagnosis.Conclusion Aptaprobe has the potential to be used as an affinity reagent to detect the target in vivo and in vitro diagnosing system.

Fluorescent probe for the detection of hypochlorous acid in water samples and cell models

A new fluorescence probe was successfully applied to test strips and imaging analysis of exogenous and endogenous hypochlorite in living cells.

Falcotentorial meningiomas: Optimal surgical planning and intraoperative challenges – case report

Meningiomas arising from the falcotentorial junction are rare, and the selection of the optimal surgical approach is essential. We report a 41-year-old man presented with progressive left paresis in the lower limbs. An MRI showed a solid mass inside the third ventricle in contact with the falcotentorial dural junction. The tumor was removed by the transtentorial/transfalcine occipital approach, performed with the patient in the three-quarter prone position. The tumor was devascularized from the tentorium, then debulked and finally dissected. The affected falx and tentorium were resected, but all of patent dural venous sinuses were preserved. The tumor was a subtotal resect. Choosing the surgical approach is essential for the safe and effective removal of an FTM and preoperative imaging analysis should identify the tumor’s anatomical relations and guide toward the least disruptive route that preserves the neurovascular structures. This article aims to report a successfully treated FTM.

Mass Spectrometry Imaging Analysis of Metabolic Changes in Green and Red Tomato Fruits Exposed to Drought Stress

Plant metabolism is altered in response to various environmental changes. In vegetable crops such as tomato (Solanum lycopersicum), the metabolic composition of fruits varies depending on the variety or cultivar as well as the cultivation method used. Few studies have examined the metabolic fluctuations in fruits under stress conditions, such as drought. We previously examined the metabolomes of mature green tomato fruits, which undergo drastic changes in chemical composition during ripening, and mature red fruits in response to drought stress. We detected or predicted fluctuations in the levels of fatty acids and phospholipid constituents, such as inositol and ethanolamine. In this study, we determined the localizations of these metabolites in fruits using mass spectrometry imaging. The accumulation patterns of stearic acid and palmitic acid were similar, but unlike these fatty acids, oleic acid accumulated to high levels in the placenta. Inositol is involved in various physiological processes; under drought conditions, this metabolite is synthesized by a different pathway compared to under normal conditions. The biosynthesis of pectin, a component of the gel surrounding the seeds, was suppressed under drought stress but increased in seeds. We propose that under drought conditions, a shift to phospholipid biosynthesis occurs that protects seeds from dehydration.

Methodological quality of machine learning-based quantitative imaging analysis studies in esophageal cancer: a systematic review of clinical outcome prediction after concurrent chemoradiotherapy

Purpose Studies based on machine learning-based quantitative imaging techniques have gained much interest in cancer research. The aim of this review is to critically appraise the existing machine learning-based quantitative imaging analysis studies predicting outcomes of esophageal cancer after concurrent chemoradiotherapy in accordance with PRISMA guidelines. Methods A systematic review was conducted in accordance with PRISMA guidelines. The citation search was performed via PubMed and Embase Ovid databases for literature published before April 2021. From each full-text article, study characteristics and model information were summarized. We proposed an appraisal matrix with 13 items to assess the methodological quality of each study based on recommended best-practices pertaining to quality. Results Out of 244 identified records, 37 studies met the inclusion criteria. Study endpoints included prognosis, treatment response, and toxicity after concurrent chemoradiotherapy with reported discrimination metrics in validation datasets between 0.6 and 0.9, with wide variation in quality. A total of 30 studies published within the last 5 years were evaluated for methodological quality and we found 11 studies with at least 6 “good” item ratings. Conclusion A substantial number of studies lacked prospective registration, external validation, model calibration, and support for use in clinic. To further improve the predictive power of machine learning-based models and translate into real clinical applications in cancer research, appropriate methodologies, prospective registration, and multi-institution validation are recommended.