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Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain.

FOLFOX (5-fluorouracil, leucovorin, and oxaliplatin), a 5-fluorouracil (5-FU)-based chemotherapy regimen, is one of most common therapeutic regimens for colorectal cancer. However, intestinal mucositis is a common adverse effect for which no effective preventive strategies exist. Moreover, the efficacy and the safety of fecal microbiota transplants (FMT) in cancer patients treated with anti-neoplastic agents are still scant. We investigated the effect of FMT on FOLFOX-induced mucosal injury. BALB/c mice implanted with syngeneic CT26 colorectal adenocarcinoma cells were orally administered FMT daily during and two days after five-day injection of FOLFOX regimen for seven days. Administration of FOLFOX significantly induced marked levels of diarrhea and intestinal injury. FMT reduced the severity of diarrhea and intestinal mucositis. Additionally, the number of goblet cells and zonula occludens-1 decreased, while apoptotic and NF-κB-positive cells increased following FOLFOX treatment. The expression of toll-like receptors (TLRs), MyD88, and serum IL-6 were upregulated following FOLFOX treatment. These responses were attenuated following FMT. The disrupted fecal gut microbiota composition was also restored by FMT after FOLFOX treatment. Importantly, FMT did not cause bacteremia and safely alleviated FOLFOX-induced intestinal mucositis in colorectal cancer-bearing mice. The putative mechanism may involve the gut microbiota TLR-MyD88-NF-κB signaling pathway in mice with implanted colorectal carcinoma cells.

Background Although previous research showed that telehealth services can reduce the misuse of resources and urban–rural disparities, most healthcare insurers do not include telehealth services in their health insurance schemes. Therefore, no target variable exists for the classification approaches to learn from or train with. The problem of identifying the potential recipients of telehealth services when introducing telehealth services into health welfare or health insurance schemes becomes an unsupervised classification problem without a target variable. Methods We propose a HDTTCA approach, which is a systematic approach (the main process of HDTTCA involves (1) data set preprocessing, (2) decision tree model building, and (3) predicting and explaining of the most important attributes in the data set for patients who qualify for telehealth service) to identify those who are eligible for telehealth services. Results This work uses data from the NHIRD provided by the NHIA in Taiwan in 2012 as our research scope, which consist of 55,389 distinct hospitals and 653,209 distinct patients with 15,882,153 outpatient and 135,775 inpatient records. After HDTTCA produces the final version of the decision tree, the rules can be used to assign the values of the target variables in the entire NHIRD. Our data indicate that 3.56% (23,262 out of 653,209) of the patients are eligible for telehealth services in 2012. This study verifies the efficiency and validity of HDTTCA by using a large data set from the NHI of Taiwan. Conclusion This study conducts a series of experiments 30 times to compare the HDTTCA results with the logistic regression findings by measuring their average performance and determining which model addresses the telehealth patient classification problem better. Four important metrics are used to compare the results. In terms of sensitivity, the decision trees generated by HDTTCA and the logistic regression model are on equal grounds. In terms of accuracy, specificity, and precision, the decision tree generated by HDTTCA provides a better performance than that of the logistic regression model. When HDTTCA is applied, the decision tree model generates a competitive performance and provides clear, easily understandable rules. Therefore, HDTTCA is a suitable choice in solving telehealth service classification problems.

Background Intermittent theta burst stimulation (iTBS) is a form of repetitive transcranial stimulation that has been used to enhance upper limb (UL) motor recovery. However, only limited studies have examined its efficacy in patients with chronic stroke and therefore it remains controversial. Methods This was a randomized controlled trial that enrolled patients from a rehabilitation department. Twenty-two patients with first-ever chronic and unilateral cerebral stroke, aged 30–70 years, were randomly assigned to the iTBS or control group. All patients received 1 session per day for 10 days of either iTBS or sham stimulation over the ipsilesional primary motor cortex in addition to conventional neurorehabilitation. Outcome measures were assessed before and immediately after the intervention period: Modified Ashworth Scale (MAS), Fugl-Meyer Assessment Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), Box and Block test (BBT), and Motor Activity Log (MAL). Analysis of covariance was adopted to compare the treatment effects between groups. Results The iTBS group had greater improvement in the MAS and FMA than the control group ( η 2  = 0.151–0.233; p  < 0.05), as well as in the ARAT and BBT ( η 2  = 0.161–0.460; p  < 0.05) with large effect size. Both groups showed an improvement in the BBT, and there were no significant between-group differences in MAL changes. Conclusions The iTBS induced greater gains in spasticity decrease and UL function improvement, especially in fine motor function, than sham TBS. This is a promising finding because patients with chronic stroke have a relatively low potential for fine motor function recovery. Overall, iTBS may be a beneficial adjunct therapy to neurorehabilitation for enhancing UL function. Further larger-scale study is warranted to confirm the findings and its long-term effect. Trial registration This trial was registered under ClinicalTrials.gov ID No. NCT01947413 on September 20, 2013.

Activation of the Nod-like receptor 3 (NLRP3) inflammasome is important for activation of innate immune responses, but improper and excessive activation can cause inflammatory disease. We previously showed that glycolysis, a metabolic pathway that converts glucose into pyruvate, is essential for NLRP3 inflammasome activation in macrophages. Here, we investigated the role of metabolic pathways downstream glycolysis – lactic acid fermentation and pyruvate oxidation—in activation of the NLRP3 inflammasome. Using pharmacological or genetic approaches, we show that decreasing lactic acid fermentation by inhibiting lactate dehydrogenase reduced caspase-1 activation and IL-1β maturation in response to various NLRP3 inflammasome agonists such as nigericin, ATP, monosodium urate (MSU) crystals, or alum, indicating that lactic acid fermentation is required for NLRP3 inflammasome activation. Inhibition of lactate dehydrogenase with GSK2837808A reduced lactate production and activity of the NLRP3 inflammasome regulator, phosphorylated protein kinase R (PKR), but did not reduce the common trigger of NLRP3 inflammasome, potassium efflux, or reactive oxygen species (ROS) production. By contrast, decreasing the activity of pyruvate oxidation by depletion of either mitochondrial pyruvate carrier 2 (MPC2) or pyruvate dehydrogenase E1 subunit alpha 1 (PDHA1) enhanced NLRP3 inflammasome activation, suggesting that inhibition of mitochondrial pyruvate transport enhanced lactic acid fermentation. Moreover, treatment with GSK2837808A reduced MSU-mediated peritonitis in mice, a disease model used for studying the consequences of NLRP3 inflammasome activation. Our results suggest that lactic acid fermentation is important for NLRP3 inflammasome activation, while pyruvate oxidation is not. Thus, reprograming pyruvate metabolism in mitochondria and in the cytoplasm should be considered as a novel strategy for the treatment of NLRP3 inflammasome-associated diseases.

Microporous activated carbon fibers (ACFs) were developed for CO2 capture based on potassium hydroxide (KOH) activation and tetraethylenepentamine (TEPA) amination. The material properties of the modified ACFs were characterized using several techniques. The adsorption breakthrough curves of CO2 were measured and the effect of relative humidity in the carrier gas was determined. The KOH activation at high temperature generated additional pore networks and the intercalation of metallic K into the carbon matrix, leading to the production of mesopore and micropore volumes and providing access to the active sites in the micropores. However, this treatment also resulted in the loss of nitrogen functionalities. The TEPA amination has successfully introduced nitrogen functionalities onto the fiber surface, but its long-chain structure blocked parts of the micropores and, thus, made the available surface area and pore volume limited. Introduction of the power of time into the Wheeler equation was required to fit the data well. The relative humidity within the studied range had almost no effects on the breakthrough curves. It was expected that the concentration of CO2 was high enough so that the impact on CO2 adsorption capacity lessened due to increased relative humidity.

Most people with motor disabilities use a joystick to control an electric wheelchair. However, those who suffer from multiple sclerosis or amyotrophic lateral sclerosis may require other methods to control an electric wheelchair. This study implements an electroencephalography (EEG)-based brain–computer interface (BCI) system and a steady-state visual evoked potential (SSVEP) to manipulate an electric wheelchair. While operating the human–machine interface, three types of SSVEP scenarios involving a real-time virtual stimulus are displayed on a monitor or mixed reality (MR) goggles to produce the EEG signals. Canonical correlation analysis (CCA) is used to classify the EEG signals into the corresponding class of command and the information transfer rate (ITR) is used to determine the effect. The experimental results show that the proposed SSVEP stimulus generates the EEG signals because of the high classification accuracy of CCA. This is used to control an electric wheelchair along a specific path. Simultaneous localization and mapping (SLAM) is the mapping method that is available in the robotic operating software (ROS) platform that is used for the wheelchair system for this study.

Background Sarcopenia is commonly observed in patients with advanced‐stage epithelial ovarian cancer (EOC). However, the effect of body composition changes—during primary debulking surgery (PDS) and adjuvant platinum‐based chemotherapy—on outcomes of patients with advanced‐stage EOC is unknown. This study aimed to evaluate the association between body composition changes and outcomes of patients with stage III EOC treated with PDS and adjuvant platinum‐based chemotherapy. Methods Pre‐treatment and post‐treatment computed tomography (CT) images of 139 patients with stage III EOC were analysed. All CT images were contrast‐enhanced scans and were acquired according to a standardized protocol. The skeletal muscle index (SMI), skeletal muscle radiodensity (SMD), and total adipose tissue index were measured using CT images obtained at the L3 vertebral level. Predictors of overall survival were identified using Cox regression models. Results The median follow‐up was 37.9 months. The median duration between pre‐treatment and post‐treatment CT was 182 days (interquartile range: 161–225 days). Patients experienced an average SMI loss of 1.8%/180 days (95% confidence interval: −3.1 to −0.4; P = 0.01) and SMD loss of 1.7%/180 days (95% confidence interval: −3.3 to −0.03; P = 0.046). SMI and SMD changes were weakly correlated with body mass index changes (Spearman ρ for SMI, 0.15, P = 0.07; ρ for SMD, 0.02, P = 0.82). The modified Glasgow prognostic score was associated with SMI loss (odds ratio: 2.42, 95% confidence interval: 1.03–5.69; P = 0.04). The median time to disease recurrence was significantly shorter in patients with SMI loss ≥5% after treatment than in those with SMI loss <5% or gain (5.4 vs. 11.2 months, P = 0.01). Pre‐treatment SMI (1 cm2/m2 decrease; hazard ratio: 1.08, 95% confidence interval: 1.03–1.11; P = 0.002) and SMI change (1%/180 days decrease; hazard ratio: 1.04, 95% confidence interval: 1.01–1.08; P = 0.002) were independently associated with poorer overall survival. SMD, body mass index, and total adipose tissue index at baseline and changes were not associated with overall survival. Conclusions Skeletal muscle index decreased significantly during treatment and was independently associated with poor overall survival in patients with stage III EOC treated with PDS and adjuvant platinum‐based chemotherapy. The modified Glasgow prognostic score might be a predictor of SMI loss during treatment.

The effect of dispersing multiwalled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) in the matrix on the low-velocity impact resistance and post-impact residual tensile strength of the carbon fiber reinforced epoxy composite laminates has been experimentally analyzed in this study. The composite specimens with the matrix reinforced by different nanoparticle types and various nanoparticle concentrations (0.1, 0.3, and 0.5 wt.%) were prepared and impacted. The post-impact tensile quasi-static and fatigue tests were performed on the specimens with different configurations to study the influence of aforementioned factors on the impact resistance and damage tolerance. Experimental results show that adding nanoparticles in the matrix increases the maximum impact force, reduces the damage area, and alleviates the dent depth of the laminates remarkedly. Moreover, the improvement in these impact resistances increases with the applied nanoparticle concentrations. The nano-modified composite laminates present higher post-impact static strength and longer fatigue life than the specimens with a neat epoxy matrix. Furthermore, both the post-impact static tensile strength and fatigue life increase with the applied nanoparticle concentrations. The damage areas measured using infrared thermography were found to increase linearly with the applied fatigue cycles for all the studied specimens with various configurations. The damage area growth rates of nano-modified composite laminates decrease significantly as the applied nanoparticle concentrations increase. The MWCNTs present better performance than GNPs in improving post-impact static strength and extending the residual fatigue life, however the effect of applied nanoparticle type on the fatigue damage growth rate is slight.

Zinc oxide nanoparticles (ZnO-NPs) are increasingly used in sunscreens, food additives, pigments, rubber manufacture, and electronic materials. Several studies have shown that ZnO-NPs inhibit cell growth and induce apoptosis by the production of oxidative stress in a variety of human cancer cells. However, the anti-cancer property and molecular mechanism of ZnO-NPs in human gingival squamous cell carcinoma (GSCC) are not fully understood. In this study, we found that ZnO-NPs induced growth inhibition of GSCC (Ca9-22 and OECM-1 cells), but no damage in human normal keratinocytes (HaCaT cells) and gingival fibroblasts (HGF-1 cells). ZnO-NPs caused apoptotic cell death of GSCC in a concentration-dependent manner by the quantitative assessment of oligonucleosomal DNA fragmentation. Flow cytometric analysis of cell cycle progression revealed that sub-G1 phase accumulation was dramatically induced by ZnO-NPs. In addition, ZnO-NPs increased the intracellular reactive oxygen species and specifically superoxide levels, and also decreased the mitochondrial membrane potential. ZnO-NPs further activated apoptotic cell death via the caspase cascades. Importantly, anti-oxidant and caspase inhibitor clearly prevented ZnO-NP-induced cell death, indicating the fact that superoxide-induced mitochondrial dysfunction is associated with the ZnO-NP-mediated caspase-dependent apoptosis in human GSCC. Moreover, ZnO-NPs significantly inhibited the phosphorylation of ribosomal protein S6 kinase (p70S6K kinase). In a corollary in vivo study, our results demonstrated that ZnO-NPs possessed an anti-cancer effect in a zebrafish xenograft model. Collectively, these results suggest that ZnO-NPs induce apoptosis through the mitochondrial oxidative damage and p70S6K signaling pathway in human GSCC. The present study may provide an experimental basis for ZnO-NPs to be considered as a promising novel anti-tumor agent for the treatment of gingival cancer.