Soft-bodied adaptive multimodal locomotion strategies in fluid-filled confined spaces

Soft-bodied locomotion in fluid-filled confined spaces is critical for future wireless medical robots operating inside vessels, tubes, channels, and cavities of the human body, which are filled with stagnant or flowing biological fluids. However, the active soft-bodied locomotion is challenging to achieve when the robot size is comparable with the cross-sectional dimension of these confined spaces. Here, we propose various control and performance enhancement strategies to let the sheet-shaped soft millirobots achieve multimodal locomotion, including rolling, undulatory crawling, undulatory swimming, and helical surface crawling depending on different fluid-filled confined environments. With these locomotion modes, the sheet-shaped soft robot can navigate through straight or bent gaps with varying sizes, tortuous channels, and tubes with a flowing fluid inside. Such soft robot design along with its control and performance enhancement strategies are promising to be applied in future wireless soft medical robots inside various fluid-filled tight regions of the human body

Bioinspired cilia arrays with programmable nonreciprocal motion and metachronal coordination

Coordinated nonreciprocal dynamics in biological cilia is essential to many living systems, where the emergentmetachronal waves of cilia have been hypothesized to enhance net fluid flows at low Reynolds numbers (Re). Experimental investigation of this hypothesis is critical but remains challenging. Here, we report soft miniature devices with both ciliary nonreciprocal motion and metachronal coordination and use them to investigate the quantitative relationship between metachronal coordination and the induced fluid flow. We found that only antiplectic metachronal waves with specific wave vectors could enhance fluid flows compared with the synchronized case. These findings further enable various bioinspired cilia arrays with unique functionalities of pumping and mixing viscous synthetic and biological complex fluids at low Re. Our design method and developed soft miniature devices provide unprecedented opportunities for studying ciliary biomechanics and creating cilia-inspired wireless microfluidic pumping, object manipulation and lab- and organ-on-a-chip devices, mobile microrobots, and bioengineering systems.ISSN:2375-254

The older the better: The characteristic of localized prostate cancer in Chinese men

AbstractObjectiveTo assess the clinicopathological features and overall survival between two groups of Chinese patients older or younger than 70 years after retropubic radical prostatectomy.MethodsFrom January 2001 to February 2010, 390 patients receive dretropubic radical prostatectomy. After excluding 89 patients with adjuvant or neoadjuvant hormonal therapy or radiotherapy, a total of 301 patients were included in this study. We arbitrarily divided these patients into younger age group (<70 years, 140 cases, 46.5%) and older age group (≥70 years, 161 cases, 53.5%). The differences in serum prostate specific antigen (PSA), Gleason score, clinical tumor stage, and biochemical-free survival were analyzed between the two groups.ResultsThere were not significant differences between the two groups in high Gleason score rate and clinical tumor stage. However, older patients had significantly lower biochemical recurrence rate than those of younger patients, and had significantly higher PSA levels. Multivariate analysis showed that older age, PSA level and clinical tumor stage were significantly associated with biochemical recurrence free survival.ConclusionIn Chinese men, older age (≥70 years) is associated with better outcome. If the physical condition permits, older age alone should not exclude patients from radical prostatectomy

A novel approach for automatic segmentation of prostate and its lesion regions on magnetic resonance imaging

ObjectiveTo develop an accurate and automatic segmentation model based on convolution neural network to segment the prostate and its lesion regions.MethodsOf all 180 subjects, 122 healthy individuals and 58 patients with prostate cancer were included. For each subject, all slices of the prostate were comprised in the DWIs. A novel DCNN is proposed to automatically segment the prostate and its lesion regions. This model is inspired by the U-Net model with the encoding-decoding path as the backbone, importing dense block, attention mechanism techniques, and group norm-Atrous Spatial Pyramidal Pooling. Data augmentation was used to avoid overfitting in training. In the experimental phase, the data set was randomly divided into a training (70%), testing set (30%). four-fold cross-validation methods were used to obtain results for each metric.ResultsThe proposed model achieved in terms of Iou, Dice score, accuracy, sensitivity, 95% Hausdorff Distance, 86.82%,93.90%, 94.11%, 93.8%,7.84 for the prostate, 79.2%, 89.51%, 88.43%,89.31%,8.39 for lesion region in segmentation. Compared to the state-of-the-art models, FCN, U-Net, U-Net++, and ResU-Net, the segmentation model achieved more promising results.ConclusionThe proposed model yielded excellent performance in accurate and automatic segmentation of the prostate and lesion regions, revealing that the novel deep convolutional neural network could be used in clinical disease treatment and diagnosis

Regulation of serotonin production by specific microbes from piglet gut

Abstract Background Serotonin is an important signaling molecule that regulates secretory and sensory functions in the gut. Gut microbiota has been demonstrated to affect serotonin synthesis in rodent models. However, how gut microbes regulate intestinal serotonin production in piglets remains vague. To investigate the relationship between microbiota and serotonin specifically in the colon, microbial composition and serotonin concentration were analyzed in ileum-cannulated piglets subjected to antibiotic infusion from the ileum when comparing with saline infusion. Microbes that correlated positively with serotonin production were isolated from piglet colon and were further used to investigate the regulation mechanisms on serotonin production in IPEC-J2 and a putative enterochromaffin cell line RIN-14B cells. Results Antibiotic infusion increased quantities of Lactobacillus amylovorus (LA) that positively correlated with increased serotonin concentrations in the colon, while no effects observed for Limosilactobacillus reuteri (LR). To understand how microbes regulate serotonin, representative strains of LA, LR, and Streptococcus alactolyticus (SA, enriched in feces from prior observation) were selected for cell culture studies. Compared to the control group, LA, LR and SA supernatants significantly up-regulated tryptophan hydroxylase 1 (TPH1) expression and promoted serotonin production in IPEC-J2 cells, while in RIN-14B cells only LA exerted similar action. To investigate potential mechanisms mediated by microbe-derived molecules, microbial metabolites including lactate, acetate, glutamine, and γ-aminobutyric acid were selected for cell treatment based on computational and metabolite profiling in bacterial supernatant. Among these metabolites, acetate upregulated the expression of free fatty acid receptor 3 and TPH1 while downregulated indoleamine 2,3-dioxygenase 1. Similar effects were also recapitulated when treating the cells with AR420626, an agonist targeting free fatty acid receptor 3. Conclusions Overall, these results suggest that Lactobacillus amylovorus showed a positive correlation with serotonin production in the pig gut and exhibited a remarkable ability to regulate serotonin production in cell cultures. These findings provide evidence that microbial metabolites mediate the dialogue between microbes and host, which reveals a potential approach using microbial manipulation to regulate intestinal serotonin biosynthesis

Longevity is determined by ETS transcription factors in multiple tissues and diverse species

Ageing populations pose one of the main public health crises of our time. Reprogramming gene expression by altering the activities of sequence-specific transcription factors (TFs) can ameliorate deleterious effects of age. Here we explore how a circuit of TFs coordinates pro-longevity transcriptional outcomes, which reveals a multi-tissue and multi-species role for an entire protein family: the E-twenty-six (ETS) TFs. In Drosophila, reduced insulin/IGF signalling (IIS) extends lifespan by coordinating activation of Aop, an ETS transcriptional repressor, and Foxo, a Forkhead transcriptional activator. Aop and Foxo bind the same genomic loci, and we show that, individually, they effect similar transcriptional programmes in vivo. In combination, Aop can both moderate or synergise with Foxo, dependent on promoter context. Moreover, Foxo and Aop oppose the gene-regulatory activity of Pnt, an ETS transcriptional activator. Directly knocking down Pnt recapitulates aspects of the Aop/Foxo transcriptional programme and is sufficient to extend lifespan. The lifespan-limiting role of Pnt appears to be balanced by a requirement for metabolic regulation in young flies, in which the Aop-Pnt-Foxo circuit determines expression of metabolic genes, and Pnt regulates lipolysis and responses to nutrient stress. Molecular functions are often conserved amongst ETS TFs, prompting us to examine whether other Drosophila ETS-coding genes may also affect ageing. We show that five out of eight Drosophila ETS TFs play a role in fly ageing, acting from a range of organs and cells including the intestine, adipose and neurons. We expand the repertoire of lifespan-limiting ETS TFs in C. elegans, confirming their conserved function in ageing and revealing that the roles of ETS TFs in physiology and lifespan are conserved throughout the family, both within and between species

Multi-state gene cluster switches determine the adaptive mitochondrial and metabolic landscape of breast cancer

Adaptive metabolic switches are proposed to underlie conversions between cellular states during normal development as well as in cancer evolution. Metabolic adaptations represent important therapeutic targets in tumors, highlighting the need to characterize the full spectrum, characteristics, and regulation of the metabolic switches. To investigate the hypothesis that metabolic switches associated with specific metabolic states can be recognized by locating large alternating gene expression patterns, we developed a method to identify interspersed gene sets by massive correlated biclustering (MCbiclust) and to predict their metabolic wiring. Testing the method on breast cancer transcriptome datasets revealed a series of gene sets with switch-like behavior that could be used to predict mitochondrial content, metabolic activity, and central carbon flux in tumors. The predictions were experimentally validated by bioenergetic profiling and metabolic flux analysis of 13C-labelled substrates. The metabolic switch positions also distinguished between cellular states, correlating with tumor pathology, prognosis, and chemosensitivity. The method is applicable to any large and heterogeneous transcriptome dataset to discover metabolic and associated pathophysiological states