Fusobacterium nucleatum confers chemoresistance by modulating autophagy in oesophageal squamous cell carcinoma

Background Fusobacterium nucleatum (F. nucleatum) is a gut microbe implicated in gastrointestinal tumorigenesis. Predicting the chemotherapeutic response is critical to developing personalised therapeutic strategies for oesophageal cancer patients. The present study investigated the relationship between F. nucleatum and chemotherapeutic resistance in oesophageal squamous cell carcinoma (ESCC).Methods We examined the relationship between F. nucleatum and chemotherapy response in 120 ESCC resected specimens and 30 pre-treatment biopsy specimens. In vitro studies using ESCC cell lines and co-culture assays further uncovered the mechanism underlying chemotherapeutic resistance.Results ESCC patients with F. nucleatum infection displayed lesser chemotherapeutic response. The infiltration and subsistence of F. nucleatum in the ESCC cells were observed by transmission electron microscopy and laser scanning confocal microscopy. We also observed that F. nucleatum modulates the endogenous LC3 and ATG7 expression, as well as autophagosome formation to induce chemoresistance against 5-FU, CDDP, and Docetaxel. ATG7 knockdown resulted in reversal of F. nucleatum-induced chemoresistance. In addition, immunohistochemical studies confirmed the correlation between F. nucleatum infection and ATG7 expression in 284 ESCC specimens.Conclusions F. nucleatum confers chemoresistance to ESCC cells by modulating autophagy. These findings suggest that targeting F. nucleatum, during chemotherapy, could result in variable therapeutic outcomes for ESCC patients.Subject terms: Tumour biomarkers, Oesophageal cancer     

Left ventricular oozing rupture following acute myocardial infarction

We describe the case of an 85-year-old woman in whom pericardiocentesis, prolonged bed rest and blood pressure control were performed without surgery to successfully treat an oozing-type myocardial rupture due to myocardial infarction.     

Responses of upper airway muscles to gastrocnemius muscle contraction in dogs

We studied electromyographic (EMG) responses of the alae nasi (AN) and the posterior cricoarytenoid (PCA) muscles, which act as upper airway dilators, during contraction of gastrocnemius muscle in six chest-intact anesthetized dogs with spontaneous breathing and in four thoracotomized, phrenicotomized and mechanically ventilated dogs with right thoracic and left cervical vagotomy. Muscle contraction was phasically induced by electrical stimulation of the intact gastrocnemius nerve or the distal cut end of this nerve for 20-30 sec. Stimulation intensity was determined as twice the motor threshold in each dog. In chest-intact animals, phasic contraction induced by intact nerve stimulation produced initial rapid increases in upper airway muscle activity, but stimulation of the distal cut end of the nerve did not show the rapid increase in upper airway muscle activity. Furthermore, stimulation of the proximal cut end did not produce any transient response with the stimulation intensity used in this study. In chest-open and vagotomized animals with artificial ventilation, responses of the upper airway muscles to contraction during the intact nerve stimulation were observed. These results suggest that the contraction of the gastrocnemius muscle activates upper airway dilating muscles via reflex mechanisms.     

Randomized controlled trial: PPI-based triple therapy containing metronidazole versus clarithromycin as first-line treatment for Helicobacter pylori in adolescents and young adults in Japan

Background/Aims

Treating Helicobacter pylori infection in young people is effective for preventing gastric cancer. This study compares the efficacy of triple therapies in adolescents and young adults in Japan.

Breathing 30 per cent oxygen attenuates bronchial responsiveness to methacholine in asthmatic patients

The effect of breathing 30% oxygen on bronchial responsiveness to inhaled methacholine was studied in 30 asthmatic patients using a direct graphical recording method. An aerosol of methacholine solution was inhaled during tidal breathing by measuring respiratory resistance (Rrs) continuously, and dose-response curves were obtained on two separate days during air and 30% oxygen inhalation. Oxygen inhalations for 20 min caused no change in baseline Rrs. The threshold dose of methacholine, the dose which increased Rrs from the baseline value while breathing 30% oxygen, increased significantly compared with that while breathing air (p less than 0.01). No significant difference was found between the mean values of the slopes of the dose-response curves of the two groups. End-expiratory oxygen concentration (FETO2) during air breathing decreased significantly from 13.7% to 12.0% at the point where methacholine dosage reached threshold. This study suggests that hyperoxia attenuates the bronchial responsiveness to methacholine in asthmatic patients.     

A Robust and Accurate Deep-learning-based Method for the Segmentation of Subcortical Brain: Cross-dataset Evaluation of Generalization Performance

Purpose:To analyze subcortical brain volume more reliably, we propose a deep learning segmentation method of subcortical brain based on magnetic resonance imaging (MRI) having high generalization performance, accuracy, and robustness.Methods:First, local images of three-dimensional (3D) bounding boxes were extracted for seven subcortical structures (thalamus, putamen, caudate, pallidum, hippocampus, amygdala, and accumbens) from a whole brain MR image as inputs to the neural network. Second, dilated convolution layers, which input information of variable scope, were introduced to the blocks that make up the neural network. These blocks were connected in parallel to simultaneously process global and local information obtained by the dilated convolution layers. To evaluate generalization performance, different datasets were used for training and testing sessions (cross-dataset evaluation) because subcortical brain segmentation in clinical analysis is assumed to be applied to unknown datasets.Results:The proposed method showed better generalization performance that can obtain stable accuracy for all structures, whereas the state-of-the-art deep learning method obtained extremely low accuracy for some structures. The proposed method performed segmentation for all samples without failing with significantly higher accuracy (P < 0.005) than conventional methods such as 3D U-Net, FreeSurfer, and Functional Magnetic Resonance Imaging of the Brain’s (FMRIB’s) Integrated Registration and Segmentation Tool in the FMRIB Software Library (FSL-FIRST). Moreover, when applying this proposed method to larger datasets, segmentation was robustly performed for all samples without producing segmentation results on the areas that were apparently different from anatomically relevant areas. On the other hand, FSL-FIRST produced segmentation results on the area that were apparently and largely different from the anatomically relevant area for about one-third to one-fourth of the datasets.Conclusion:The cross-dataset evaluation showed that the proposed method is superior to existing methods in terms of generalization performance, accuracy, and robustness.