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In this paper, sparse autoencoder in deep learning is integrated into the compressed sensing (CS) theory, and a reconstruction algorithm is designed based on the biological mechanism of human brain synaptic connections. The compressive sampling process is modeled as a neural network model. Then a biological mechanism-inspired stacked Long Short-Term Memory (LSTM) network model is proposed as a reconstruction algorithm of CS theory. Consequently, a compressed sensing network (ComsensNet) model is introduced, by integrating the compressive sampling process and reconstruction algorithm. ComsensNet can provide a bridge between sparse autoencoder in deep learning, synapses in human brain neurons and the CS theory. A deep neural network is designed based on the synaptic biological mechanism of human brain neurons, and then combine with the theory of compressed sensing. The effectiveness of ComsensNet is investigated by using acquired pressure data from the human body model. Experimental results demonstrate that the biological mechanisminspired stacked LSTM network in ComsensNet can improve the reconstruction accuracy compared to other reconstruction algorithms.

Many CNN-based segmentation methods have been applied in lane marking detection recently and gain excellent success for a strong ability in modeling semantic information. Although the accuracy of lane line prediction is getting better and better, lane markings' localization ability is relatively weak, especially when the lane marking point is remote. Traditional lane detection methods usually utilize highly specialized handcrafted features and carefully designed postprocessing to detect the lanes. However, these methods are based on strong assumptions and, thus, are prone to scalability. In this work, we propose a novel multitask method that: 1) integrates the ability to model semantic information of CNN and the strong localization ability provided by handcrafted features and 2) predicts the position of vanishing line. A novel lane fitting method based on vanishing line prediction is also proposed for sharp curves and nonflat road in this article. By integrating segmentation, specialized handcrafted features, and fitting, the accuracy of location and the convergence speed of networks are improved. Extensive experimental results on four-lane marking detection data sets show that our method achieves state-of-the-art performance.

Cable current detection plays a vital role in power grids toward improving transmission efficiency, relieving power congestion, and ensuring grid reliability. However, the sensors in existing current detection systems either are wired with measurement instruments or are wireless yet require batteries, which is inconvenient for monitoring overhead powerlines. Inspired by RF sensing tags, which are widely used for applications such as temperature and humidity measurements, in this article, we propose a distinctive cable current detection system that can avoid the constraint of wires and batteries. By detecting the ambient magnetic field produced by ac current flowing through a cable, the proposed system realizes a minimal measurement range of 5–17.5 A at 50/60 Hz with a maximum wireless distance of 5.2 m. This prototype can detect cable current with an extendable measurement range, providing a promising strategy for passive and wireless current detection.

The adoption of IoT for smart health applications is a relevant tool for distributed and intelligent automatic diagnostic systems. This work proposes the development of an integrated solution to monitor maternal and fetal signals for high-risk pregnancies based on IoT sensors, feature extraction based on data analytics, and an intelligent diagnostic aid system based on a 1-D convolutional neural network (CNN) classifier. The fetal heart rate and a group of maternal clinical indicators, such as the uterine tonus activity, blood pressure, heart rate, temperature, and oxygen saturation are monitored. Multiple data sources generate a significant amount of data in different formats and rates. An emergency diagnostic subsystem is proposed based on a fog computing layer and the best accuracy was 92.59% for both maternal and fetal emergency. A smart health analytics system is proposed for multiple feature extraction and the calculation of linear and nonlinear measures. Finally, a classification technique is proposed as a prediction system for maternal, fetal, and simultaneous health status classification, considering six possible outputs. Different classifiers are evaluated and a proposed CNN presented the best results, with the F1-score ranging from 0.74 to 0.91. The results are validated based on the diagnosis provided by two specialists. The results show that the proposed system is a viable solution for maternal and fetal ambulatory monitoring based on IoT.

Stroke is among the first pathologies that kill the most in the world, ranking second in deaths from illness. Each year, around 16 million people worldwide are victims of this disease, with approximately 38 % of cases brought to death. Computed Tomography (CT) is a super effective method to aid the medical diagnosis of stroke. But the analysis is subject to variations in the perception of specialists about its characteristics. Faced with the challenge of diagnosing stroke on CT images, this study proposes a fully automatic system based on Health of Things capable of classifying CT images of the skull through deep learning networks, classifying them into (Uninjured or Hemorrhagic stroke). After the image classification, Mask R-CNN segments the stroke through a learning transfer process, combined with machine learning methods. Our innovative method selected excellent results, both for classification with 100 % accuracy, and for segmentation in our best model (Mask + kNN) that reached 99.93% specificity and 99.73 accuracy, with segmentation time of 4.00 seconds, surpassing literature methods based on automatic models.

Dementia causes a substantial global economic burden, but effective treatment is lacking. Recently, studies have revealed that gamma-band waves of electrical brain activity, particularly 40 Hz oscillations, are closely associated with high-order cognitive functions and can activate microglia to clear amyloid-β deposition. Here, we found that compared with sham stimulation, applying 40-Hz high-frequency repetitive transcranial magnetic stimulation (rTMS) over the bilateral angular gyrus in patients with probable Alzheimer’s disease (AD; n = 37) resulted in up to 8 weeks of significantly improved cognitive function. Power spectral density analysis of the resting-state electroencephalography (EEG) demonstrated that 40-Hz rTMS modulated gamma-band oscillations in the left posterior temporoparietal region. Further testing with magnetic resonance imaging and TMS-EEG revealed the following: 40-Hz rTMS 1) prevented gray matter volume loss, 2) enhanced local functional integration within bilateral angular gyrus, as well as global functional integration in bilateral angular gyrus and the left middle frontal gyrus, 3) strengthened information flow from the left posterior temporoparietal region to the frontal areas and strengthened the dynamic connectivity between anterior and posterior brain regions. These findings demonstrate that modulating gamma-band oscillations effectively improves cognitive function in patients with probable AD by promoting local, long-range, and dynamic connectivity within the brain.

In this paper, the effect of harmonic voltage on partial discharge properties of LN2/PPLP (Liquid nitrogen/ Polypropylene-Laminated-Paper) insulation system for high-temperature superconducting (HTS) DC cable is studied. The harmonic components with a frequency from 50 to 350 Hz are superimposed on the DC voltage to analyze the mechanism of the harmonic amplitude and order on partial discharge (PD). The experimental results show that when the V rms of the composite voltage remains consistent, the increase in the proportion of the harmonic amplitude will cause the enhancement of partial discharge amplitude, discharge counts and pulse repetition rate, especially as the amplitude of harmonic component exceeds that of DC voltage. The increase of the harmonic order results in variation of the derivative of the applied voltage with time (dv/dt) along the phase, which further causes the pulse repetition rate to increase. It is concluded that the harmonic components superimposed on DC voltage promote the occurrence of PD, which poses a significant threat to the insulation of superconducting DC cable.

Backgrounds Neutrophil-to-lymphocyte ratio (NLR), a surrogate marker of systemic response to physiological stress, is used for prognosis prediction in many diseases. However, the usefulness of this marker for predicting acute kidney injury (AKI) progression is unclear. Methods This retrospective study was based on the Chang Gung Research Database. Patients admitted to the intensive care unit with a diagnosis of stage 1 or 2 AKI were identified. The primary outcome was a composite of progression to stage 3 AKI, requirement of renal replacement therapy, or 14-day in-hospital mortality. The association between NLR and the primary outcome was examined using a logistic regression model and multivariable analysis. The nonlinearity and cutoff points of this relationship were determined using a restricted cubic spline model. Results A total of 10,441 patients were enrolled. NLR level at the time of stage 1–2 AKI diagnosis was a marker of adverse outcomes. After adjustment for confounders, NLR was independently associated with the composite outcome of AKI progression, renal replacement therapy, or mortality. The restricted cubic spline model revealed a J-shaped curve, with the lowest odds ratio for an NLR between 7 and 38. Subgroup analysis revealed linear and J-shaped relationships between NLR and the primary outcome in patients admitted to the intensive care unit for medical reasons and for cardiovascular surgery, respectively. Conclusions NLR is an independent marker of AKI progression and in-hospital mortality. Because it is readily available in daily practice, it might be used for risk stratification in the AKI population. Graphic abstract Supplementary Information The online version contains supplementary material available at 10.1007/s40620-021-01162-3.

Background Restless legs syndrome (RLS) is common among patients with end-stage kidney disease (ESKD) and is associated with poor outcomes. Several recently published studies had focused on pharmacological and non-pharmacological treatments of RLS, but an updated meta-analysis has not been conducted. Methods The study population was adult ESKD patients on dialysis with RLS. Randomized controlled trials (RCTs) were selected. The primary outcome was reduction in RLS severity. The secondary outcomes were improvement in sleep quality and treatment-related adverse events. Frequentist standard network meta-analysis (NMA) and additive component NMA were performed. The evidence certainty was assessed using the Confidence in NMA (CINeMA) framework. Results A total of 24 RCTs with 1252 participants were enrolled and 14 interventions were compared. Cool dialysate produced the largest RLS severity score reduction {mean difference [MD] 16.82 [95% confidence interval (CI) 10.635–23.02]} and a high level of confidence. Other potential non-pharmacological interventions include intradialytic stretching exercise [MD 12.00 (95% CI 7.04–16.97)] and aromatherapy massage [MD 10.91 (95% CI 6.96–14.85)], but all with limited confidence of evidence. Among the pharmacological interventions, gabapentin was the most effective [MD 8.95 (95% CI 1.95–15.85)], which also improved sleep quality [standardized MD 2.00 (95% CI 0.47–3.53)]. No statically significant adverse events were detected. Conclusions The NMA supports that cool dialysate is appropriate to treat patients with ESKD and RLS. Gabapentin is the most effective pharmacological intervention and also might improve sleep quality. Further parallel RCTs with sufficient sample sizes are required to evaluate these potential interventions and long-term effects.

The outcomes of patients with incident kidney failure who start hemodialysis are influenced by several factors. Whether hemodialysis facility characteristics are associated with patient outcomes is unclear. We included adults diagnosed as having kidney failure requiring hemodialysis during January 1, 2001 to December 31, 2013 from the Taiwan National Health Insurance Research Database to perform this retrospective cohort study. The exposures included different sizes and levels of hemodialysis facilities. The outcomes were all-cause mortality, cardiovascular death, infection-related death, hospitalization, and kidney transplantation. During 2001–2013, we identified 74,406 patients and divided them in to three groups according to the facilities where they receive hemodialysis: medical center (n = 8263), non-center hospital (n = 40,008), and clinic (n = 26,135). The multivariable Cox model demonstrated that a larger facility size was associated with a low mortality risk (hazard ratio [HR] 0.991, 95% confidence interval [95% CI] 0.984–0.998; every 20 beds per facility). Compared with medical centers, patients in non-center hospitals and clinics had higher mortality risks (HR 1.13, 95% CI 1.09–1.17 and HR 1.11, 95% CI 1.06–1.15, respectively). Patients in medical centers and non-center hospitals had higher risk of hospitalization (subdistribution HR [SHR] 1.11, 95% CI 1.10–1.12 and SHR 1.22, 95% CI 1.21–1.23, respectively). Patients in medical centers had the highest rate of kidney transplantation among the three groups. In patients with incident kidney failure, a larger hemodialysis facility size was associated with lower mortality. Overall, medical center patients had a lower mortality rate and higher transplantation rate, whereas clinic patients had a lower hospitalization risk.

Background Pradefovir is a liver-targeted prodrug of adefovir, a nucleoside/nucleotide analogue with antiviral activity against hepatitis B virus (HBV) DNA polymerase. This phase 2 study compared the efficacy and safety of oral pradefovir (30, 45, 60, or 75 mg) versus tenofovir disoproxil fumarate (TDF; 300 mg) and aimed to identify the most appropriate dose of pradefovir for the forthcoming phase 3 study. Methods Treatment-naive and experienced (not on treatment >6 months) patients with chronic hepatitis B were eligible. Results A total of 240 participants were randomized and treated in the study (48 per group). Approximately 80% were hepatitis B e antigen (HBeAg) positive, and 10% had liver cirrhosis. The reductions from baseline in HBV DNA levels achieved at week 24 were 5.40, 5.34, 5.33, and 5.40 log10 IU/mL, with pradefovir doses of 30-, 45-, 60-, and 75-mg, respectively, compared with 5.12 log10 IU/mL with TDF. However, HBeAg loss was attained by more participants who received 45-, 60-, or 75-mg pradefovir than by those receiving TDF (12%, 6%, and 9% vs 3%). The TDF group exhibited a more significant increase in serum creatinine than the pradefovir 30- and 45-mg groups, and serum phosphate levels were comparable among all groups. Most adverse events (AEs) were mild (grade 1). No treatment-related severe AEs were reported. Overall, AEs and laboratory abnormalities were comparable to those in the TDF group. Conclusions Pradefovir and TDF exhibited comparable reductions in HBV DNA levels. All treatments were safe and well tolerated. Clinical Trials registration NCT00230503 and China Drug Trials CTR2018042

Li-Hong Lu, Yu-Qing Song, Qi-Ming Wu, Zhao Wang, Yong-Fu Chen, Qian Dong, Xiao-Tao Han Department of Cardiology, Beijing Ditan Hospital, Capital Medical University, Beijing, 100015, People’s Republic of ChinaCorrespondence: Qi-Ming WuDepartment of Cardiology, Beijing Ditan Hospital, Capital Medical University, No. 8 of Jingshun Street, Chaoyang District, Beijing, 100015, People’s Republic of ChinaTel +86 138 0100 9058Fax +86 10-84322988Email lulihong1954@163.comObjective: To improve our knowledge of cardiac manifestations caused by brucellosis through analyzing abnormal electrocardiograms of patients infected with brucella.Methods: A total of 108 cases were enrolled, and their electrocardiograms were analyzed and summarized retrospectively.Results: Among 108 cases, 77 (71.3%) had a normal electrocardiogram, and 31 (28.7%) had an abnormal electrocardiogram. There were 13 cases with nodal tachycardia (12%), 9 cases with sinus bradycardia (8%), 7 cases with sinus arrhythmia (6%), 8 cases with left ventricular high voltage (7%), 13 cases with abnormal ST segment and T wave (12%), 2 cases with abnormal Q wave (1.85%), 3 cases with complete right bundle branch block (2.78%), 3 cases with ventricular premature beat (2.78%), 1 case with left anterior fascicular block (0.9%), 1 case with first degree a-v block (0.9%), 1 case with QT internal prolongation (0.9%), 1 case with poor R wave progression (0.9%), and 1 case with short PR interval (0.9%).Conclusion: The cardiac manifestations of brucellosis were rare, but the mortality was high. Patients with abnormal electrocardiogram should have improved echocardiography in time. Early detection of the abnormal electrocardiogram could give a hint of cardiac damage to avoid the serious consequences.Keywords: brucella, brucellosis, ECG, manifestations, cardiac manifestations

To identify buried assets, this article presents a novel design of surface acoustic wave (SAW) tag to enhance its underground penetration capacity. A penetration depth model for a SAW tag buried in materials is established to investigate the depth of detection and guide the design of the SAW tag. Multipulse position with all reflectors in two groups (MPP-ART) coding scheme is proposed to reduce the insertion loss of the SAW chip. A novel embedded monopole microstrip tag antenna is investigated with a stable frequency performance when embedded in diverse types of materials. Furthermore, a linear frequency modulation pulse compression transceiver based on software defined radio is implemented to enhance the penetration depth. The insertion loss of the SAW chip at 920 MHz with the MPP-ART coding scheme, is reduced to 26.58 dB. Through experiments, the penetration depth of the SAW radio frequency identification prototype has reached 0.75 m in river water, 0.8 m in tap water, 1.5 m in wet sand, and 3 m in dry sand, respectively. The experimental results demonstrate that the SAW tag can work in various materials with good penetration depth, relatively immune to electromagnetic interference with adjacent metallic objects, making it suitable for the identification of buried assets for industrial applications.

Introduction Acute-on-chronic liver failure (ACLF) patients are susceptible to invasive fungal infections. We evaluated the prognosis and antifungal options in ACLF patients with invasive pulmonary aspergillosis (IPA). Methods ACLF patients with IPA from 15 hospitals were retrospectively screened from 2011 to 2018, and 383 ACLF patients without lung infections were included from a prospective cohort (NCT02457637). Demographic, laboratory, clinical data, and 28-day outcomes were documented in the two cohorts. Results ACLF patients with probable IPA (n = 145) had greater 28-day mortality (33.6% vs. 15.7%, p

Background With the advancement of hepatocellular carcinoma (HCC) treatment technology, the treatment options for HCC patients have increased. However, due to high heterogeneity, among other reasons, the five-year survival rate of patients is still very low. Currently, gene expression prognostic models can suggest more appropriate strategies for the treatment of HCC. This study investigates the role of FAT10 in hepatocarcinogenesis and its underlying mechanism. Methods The expression of FAT10 was detected by immunohistochemical method using tissue arrays containing 4 specimens of patients with digestive cancer. The expression of FAT10 was determined by a tissue microarray which included 286 pairs of HCC samples and corresponding normal mucosae and was further confirmed by real-time polymerase chain reaction (PCR) and western blot. The Kaplan-Meier survival curve was used to determine the correlation of FAT10 expression with patients' recurrence and overall survival (OS) rate. In vivo, liver fibrosis, cirrhosis, and HCC models were established to assess the FAT10 expression. Moreover, FAT10 over-expressing cell lines were used to determine the molecular mechanism underlying the FAT10-induced cell proliferation and hepatocarcinogenesis by reporter gene measure, real-time PCR, and western blot. Based on TCGA database, signal pathways associated with FAT10 and HCC invasion and metastasis were analyzed by KEGG enrichment analyze. Results Overexpression of FAT10 in HCC was observed in this study compared with its expression in other digestive tumors. Clinicopathological analysis revealed that FAT10 expression levels were closely associated with tumor diameters and poor prognosis of HCC. This study also confirmed through in vivo experiments that the expression of FAT10 in liver fibrosis, cirrhosis, and HCC gradually increases. Further study revealed that forced FAT10 expression enhanced the growth ability of HCC cells and mediated the degradation of the critical anti-cancer protein p53, which led to carcinogenesis. Finally, 9 signal pathways related to HCC metastasis were obtained through bioinformatics analysis. Conclusions FAT10 may act as a proto-oncogene that facilitates HCC carcinogenesis by mediating p53 degradation, and the expression of FAT10 is negatively correlated with the prognosis of HCC patients. FAT10 is expected to become a potential combined target and prognostic warning marker for HCC treatment.

BACKGROUND: The high prevalence and incidence of non-alcoholic fatty liver disease (NAFLD) have become a global medical concern. Compared with obesity, metabolic abnormalities may be more critical. Currently, there is lack of relevant data for nutritional status and energy metabolic characteristics in patients with obese and lean NAFLD. METHODS: All the enrolled NAFLD patients were divided into 2 groups: the obese group (205 patients with body mass index (BMI) ≥ 25 kg/m(2)) and the lean group (73 patients with BMI < 25 kg/m(2)). Using a body composition analyzer, we analyzed their nutritional status including skeletal muscle, body fat, protein content, and visceral fat area (VFA). Energy metabolic characteristics including resting energy expenditure (REE), respiratory quotient, and oxidation rate of 3 major nutrients (carbohydrate, CHO%, fat, FAT%, and protein, PRO%) were analyzed by metabolic cart. RESULTS: The lean NAFLD patients’ LDL-c and UA even increased significantly than the obese patients (P = .001 and .006, respectively). Compared with the control group, VFA and REE were significantly higher in the lean NAFLD group (P = .008, P < .001 respectively). CHO%, FAT%, and PRO% in the lean NAFLD group were 29.31 ± 7.07%, 55.59 ± 12.09%, and 15.10 ± 4.07%, respectively, and there was no significant difference compared to the control. However, compared to the obese NAFLD group, their CHO% increased, whereas FAT% decreased (both P < .001). CONCLUSION: NAFLD patients suffer from nutritional imbalances and energy metabolic abnormalities, regardless of whether they are associated with obesity. LDL, UA, VFA, and REE can be used as good evaluation indicators.

Commercial cellulosic biofuel operation requires a reliable, low-cost, and stable feedstock logistic system. One great challenge is its long-term storage at least for one harvest cycle (1 year for ...

In organic photodetectors, photomultiplication is mainly originated from interfacial and/or bulk charge traps, which induces slow response due to the slow release of trapped charges and strongly limits the optimization of the overall performance. This study has exhibited a remarkable case that the gain (>1) and response speed of the lateral photodetectors are promoted simultaneously and effectively by increasing the trap ratio. For lateral photodetectors with silver nanoparticles and PDPPBTT:PC61BM bulk heterojunction, the gain increases from 12.7 to 19.8 and the fall time decreases from 313.4 to 172.9 ms as the PC61BM ratio increases from 5:1 to 1:1. The lateral photodetector structure with a long electrode distance has been testified to play the key role for simultaneous promotion compared with vertical photodiodes, allowing the charges to trap well in the PC61BM-rich phase at a high PC61BM ratio and accumulation of multiple built-in electric fields. The long channel distance and silver nanoparticles also effectively restrain the increment of dark current with PC61BM loading, resulting in a high detectivity of 1.7 × 1012 Jones under 0.031 mW cm-2 @ 820 nm. It is of great theoretical and practical value for the high-performance photodetectors with simultaneous high photomultiplication and quick response.

Electric machines with high specific power are crucial for the more electric aircraft propulsion. However, the harsh operating environment such as low air pressure and high temperature will challenge the motor’s insulation system and cause partial discharge (PD), which threatens the reliability of the machine. This article proposes a PD-free stator winding design regarding an air-core high-frequency permanent magnet synchronous machine for aircraft propulsion. The experiment and simulation are performed under sinusoidal voltage due to the power quality requirement by the standard for aircraft. PD inception voltage (PDIV) with respect to air pressure and temperature was obtained experimentally for form-wound windings and was analyzed to derive the PD-free criteria. A 3-D stator model was built and used to simulate the electric field and temperature distributions with a finite-element method. In addition, the effect of voids and delamination on electric field distortion was also taken into consideration to allow for a safety margin and meet the PD-free requirement. To achieve high-specific-power requirement and PD-free requirement simultaneously, a multiobjective genetic algorithm was adopted to perform the optimization and obtain the Pareto fronts at various air pressures. Finally, the PDIV value of the designed winding was measured to verify the PD-free design. The main purpose is to combine the experimental results and the simulation tool to obtain an acceptable PD-free design in the meantime achieving high power density, which may provide helpful guidance on motor insulation design for the more electric aircraft propulsion.

Introduction and aim It is difficult to distinguish between non-functioning pituitary macroadenomas (NFPMAs) and sellar meningiomas because of their overlapping imaging manifestations on routine MRI, especially in cases of meningiomas growing into the saddle. Here, we aimed to differentiate between these two tumors using apparent diffusion coefficient (ADC) values and MRI characteristics. Methods A total of 60 NFPMA and 52 sellar meningioma cases confirmed by the pathological analysis were retrospectively reviewed. All patients were examined via routine MRI and diffusion-weighted imaging (DWI) before undergoing surgery. The clinical characteristics, MRI characteristics, and max ADC (ADCmax), average ADC (ADCmean), and minimum ADC (ADCmin) values were compared between the two tumors via Chi-square test and two sample t-tests. Receiver operating characteristic (ROC) curve and binary logistic regression analyses were conducted to determine the discrimination ability. Results The ADCmax, ADCmean, and ADCmin values were significantly higher in NFPMAs compared to sellar meningiomas (P < 0.001 for all). Among ADC values, ADCmax demonstrated good performance with an AUC of 0.896 (95% CI, 0.823–0.969) and accuracy of 88.7%. A cut-off value of 0.97 × 10−3 mm2/s was used for ADCmax for differentiation between tumors. A combination of ADCmax values and clinicoradiological features showed the best discrimination ability for differential diagnosis between the two tumors, with an AUC of 0.981 (95% CI, 0.958–1.000) and accuracy of 96.9%. Conclusion A combination of ADCmax and clinicoradiological features demonstrates good discrimination ability and high accuracy for differentiation between NFPMAs and sellar meningiomas, and is a potential quantitative tool to aid in the selection of surgical techniques.

The tumor microenvironment (TME) significantly influences cancer evolution and therapeutic efficacy. Targeting biofunctional molecules to the TME has long been appreciated as a means of raising local drug concentrations and reducing systemic toxicities. The booming nanotechnology field has realized the importance of cathepsin B to derive a variety of intelligent enzyme-responsive nanosized drug delivery systems (nanoDDS) to improve treatment responses and clinical outcomes. In this tutorial review, after introducing the molecular structure and physiological/pathological functions of cathepsin B, the outstanding achievements of cathepsin B-responsive nanoplatforms in the precise diagnosis, targeted therapy, and synergistic theranostics of malignant tumors are systematically described. Finally, the challenges of enzyme-substrate incompatibility, low diagnostic sensitivity, mass production and biocompatibility of multifunctional nanoDDS are considered in order to successfully promote them to clinical applications

Background Breast cancer is one of the most significant causes of death in women around the world. Circular RNAs (circRNAs), which are a novel class of conserved RNA molecules, are involved in the occurrence and development of various diseases, especially malignancies; however, researchers rarely report their roles in human breast cancer. Methods In the present study, the differentially expressed levels of circRNAs in human breast cancer tissues and paired noncancerous tissues were screened by circRNA microarray. Hsa_circ_0043278 was downregulated 43-fold in breast cancer and was selected for further analysis. The expression of hsa_circ_0043278 was verified in breast cancer specimens and paired noncancerous tissues by quantitative reverse transcription polymerized chain reaction (qRT-PCR) technique. The relationship between the expression of hsa_circ_0043278 and the clinicopathological features was analyzed. Results Among the 520 differentially expressed circRNAs, 292 significantly upregulated circRNAs and 228 downregulated circRNAs in the breast cancer tissues compared with the paired noncancerous tissues. The area under the receiver operating characteristic (ROC) curve of hsa_circ_0043278 was 0.690. The results of the bioinformatics prediction showed five target miRNAs that might be sponged by hsa_circ_0043278. The expression of hsa_circ_0043278 was associated with lymph node metastasis and histological type of the patient. Patients with lymph node metastasis have tumors with significantly downregulated expression of hsa_circ_0043278 (P=0.0201). Conclusions Our results suggest that hsa_circ_0043278 is downregulated and may play a key role in human breast cancer.

Background To determine the safety and efficacy of different doses of tolvaptan for treating Chinese cirrhotic patients with or without hyponatraemia who still had ascites after routine therapy with diuretics. Methods In the present placebo-controlled, randomized, double-blinded, multicentre clinical trial, patients with cirrhotic ascites who failed to adequately respond to a combination of an aldosterone antagonist plus an orally administered loop diuretic were randomly placed at a 4:2:1 ratio into 3 groups [the 15 mg/day tolvaptan group (N = 301), 7.5 mg/day tolvaptan group (N = 153) and placebo group (N = 76)] for 7 days of treatment. The effects and safety were evaluated on days 4 and 7. A change in body weight from baseline on day 7 of treatment was the primary endpoint. Results The administration of 7.5 or 15 mg/day tolvaptan significantly decreased body weight from baseline on day 7 of treatment compared to that with placebo treatment (P = 0.026; P = 0.001). For the secondary endpoints, changes in abdominal circumference from baseline and improvements in ascites were markedly different in the treatment groups and the placebo group on day 7 (P7.5 = 0.05, P15.0 = 0.002 and P7.5 = 0.037, P15.0 = 0.003), but there was no difference between the 7.5 mg/day and 15 mg/day dosage groups. The 24-h cumulative urine volume was higher in the 7.5 mg/day and 15 mg/day tolvaptan groups than the placebo group (P = 0.002, P P = 0.004). Sodium serum concentrations were higher in patients with hyponatraemia after tolvaptan treatment, with no significant difference between the two dosage groups. The incidence of serious adverse drug reactions was not different between the groups (P = 0.543). Conclusions Tolvaptan treatment at 7.5 mg per day might be a good therapeutic choice for Chinese cirrhotic patients with ascites who did not achieve satisfactory clinical responses to previous treatment regimens with combination therapy with an aldosterone antagonist and an orally administered loop diuretic. Trial registration NCT01349348. Retrospectively registered May 2011.

Form‐wound windings in electric machines designed for electric aircraft propulsion face reliability challenges due to the severe operating environment, such as high temperature and low pressure. This study proposes a forewarning method for insulation condition monitoring of form‐wound windings based on partial discharge (PD) and deep learning neural network. Three PD features are extracted from the PD profile, which provides information about physics‐of‐failure and reflects the degree of insulation degradation. An algorithm fusion extracted from auto‐encoder and long short‐term recurrent neural network is proposed to synthesize one failure precursor from these three features and make multi‐time‐step prediction through historical data to provide forewarning. An electrical and thermal accelerated ageing test is performed on the form‐wound windings at 0.2 atm to simulate working environment of electric aircraft. The proposed method is validated on the accelerated ageing dataset and shows better prediction accuracy than some existing time‐series prediction methods, indicating the advantages of the proposed method. Moreover, an on‐line hardware setup using a deep learning processor is recommended to implement the forewarning method. The proposed approach has the potential to be widely applied to other insulation systems and contribute to work on condition monitoring.

Phonon polaritons in van der Waals materials show the strong electric confinement and low energy loss. Combining with the materials hexagonal boron nitride, hyperbolic phonon polaritons can be excited in two RS bands, which changes a lot in electric field distribution and transmission characteristics. In order to increase the tunability of hyperbolic phonon polaritons, a structure based on graphene/h-BN heterostructure has been formed in previous studies. In this paper, the electric field distribution and transmissivity characteristics are calculated and discussed based on grapheme–h-BN–graphene heterostructure. The results illustrate the excellent transmissivity tunability in 780 cm−1 incident wavenumber of type-I band and poor transmissivity tunability in 1368 cm−1 of type-II band. In addition, superior field-enhanced characteristic (115.76% transmissivity in 6 V external voltage) is shown in the structure. These excellent properties make such structure a promising component in future optoelectronic devices design.

Background: In neonatal mice, sevoflurane, inspired through the nasal cavity to act as anesthesia, triggers neuronal apoptosis, inflammation and oxidative injury that can hamper cognitive functions in the growth of the central nervous system in the later stages of life. Objective: Our study aimed to explore the potential neuroprotective effects of protocatechuic acid (PCA) to ameliorate neonatal sevoflurane-induced neurotoxicity. Methods: Male mice were pretreated with PCA (10 or 20 mg/kg) for half an hour before continuous treatment for 6 h with 3 % sevoflurane. TUNEL staining was performed to examine the apoptotic cells to record their count. ELISA was performed to evaluate the expressions of the proteins - IL-1β, IL-18 and TNF-α. Analysis of the Western blot and test of the Morris maze was determined and the results analyzed. Results: TUNEL findings assay showed a significant reduction with sevoflurane in neuronal apoptosis treated with PCA at 20 mg/kg. The expression of protein Caspase-3 showed significant changes in the group SEV + PCA (20 mg/kg). ELISA analysis showed that the levels of IL-18 and TNF-α were significantly reduced in the SEV + PCA (20 mg/kg) group as compared to SEV + PCA (10 mg/kg) group. MDA, ROS and SOD levels were noted to decrease significantly only in the SEV + PCA group (20 mg/kg) while IL-1β levels decreased in both SEV + PCA groups (10 or 20 mg/kg) respectively. Conclusions: Our findings imply that apoptosis, inflammation, and oxidative stress in the hippocampal region of neonatal mouse brain were significantly reduced by pre-treatment with PCA before sevoflurane exposure. Therefore, suggesting a role for PCA as a novel therapeutic agent in the treatment of sevoflurane anesthesia-induced neurobehavioral dysfunction.

OBJECTIVES To validate the operational and diagnostic performances of a new device for transient elastography (TE), FibroTouch, for liver fibrosis in patients with chronic hepatitis B (CHB). METHODS In this prospective multicenter study, adult patients with CHB and valid liver pathological results were recruited to validate the operational and diagnostic performance of a TE device by FibroTouch for staging liver fibrosis. RESULTS In total, 517 patients with histologically proven CHB were enrolled. All had achieved at least 10 successful liver stiffness measurements (LSM), resulting in a success rate of 99.1% and reliable evaluations of 95.2%. Altogether 412 patients were included to analyze the diagnostic performance of FibroTouch. The area under the receiver operating characteristic curve for the LSM was 0.846 (95% confidence interval [CI] 0.808-0.880) for fibrosis stage ≥ F1, 0.850 (95% CI 0.811-0.883) for ≥ F2, 0.908 (95% CI 0.876-0.934) for ≥ F3 and 0.874 (95% CI 0.836-0.903) for F4. The diagnostic accuracy of LSM was superior to that of gamma-glutamyl transpeptidase-to-platelet ratio (GPR), aminotransferase-to-platelet ratio index (APRI), or fibrosis index based on 4 factors (FIB-4) index in staging fibrosis F2-F4 (P = 0.007 to

This paper deals with the fixed-time group consensus problem for multi-agent systems (MASs) subjected to exogenous disturbances. Firstly, two pinning control algorithms are constructed for MASs, which not only reduce the number of controllers but also achieve expected tracking consensus. Secondly, fixed-time group consensus is ensured by utilizing the algebraic graph theory, Lyapunov stability and fixed-time control technique. Finally, simulations are finally given for demonstrate the availability of the derived results.

Purpose Research dynamics have long been a research interest. It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject. A micro perspective of research dynamics, however, concerning a single researcher or a highly cited paper in terms of their citations and “citations of citations” (forward chaining) remains unexplored. Design/methodology/approach In this paper, we use a cross-collection topic model to reveal the research dynamics of topic disappearance topic inheritance, and topic innovation in each generation of forward chaining. Findings For highly cited work, scientific influence exists in indirect citations. Topic modeling can reveal how long this influence exists in forward chaining, as well as its influence. Research limitations This paper measures scientific influence and indirect scientific influence only if the relevant words or phrases are borrowed or used in direct or indirect citations. Paraphrasing or semantically similar concept may be neglected in this research. Practical implications This paper demonstrates that a scientific influence exists in indirect citations through its analysis of forward chaining. This can serve as an inspiration on how to adequately evaluate research influence. Originality The main contributions of this paper are the following three aspects. First, besides research dynamics of topic inheritance and topic innovation, we model topic disappearance by using a cross-collection topic model. Second, we explore the length and character of the research impact through “citations of citations” content analysis. Finally, we analyze the research dynamics of artificial intelligence researcher Geoffrey Hinton's publications and the topic dynamics of forward chaining.

Background and Aims: Recent accumulating evidence indicates the biological actions of autotaxin (ATX) in liver disease. However, the relationship between ATX and liver failure has not been reported. The present study aimed to examine alterations of serum ATX in acute-on-chronic liver failure (ACLF) and evaluate whether serum ATX could be useful as an early warning biomarker of ACLF. Methods: Serum ATX was measured in 50 patients with hepatitis B-related ACLF, 14 patients with alcohol-related ACLF, 11 patients with hepatitis B-related pre-ACLF, 11 patients with alcohol-related Child-Pugh A cirrhosis, 39 patients with hepatitis B-related Child-Pugh A cirrhosis, 26 patients with chronic hepatitis B, and 38 healthy volunteers by enzyme-linked immunosorbent assay. Results: Serum ATX level was significantly higher in the pre-ACLF group than in the Child-Pugh A cirrhosis and chronic hepatitis B groups but lower than in the ACLF group; furthermore, patients with pre-ACLF deteriorated to ACLF had significantly higher serum ATX levels than pre-ACLF patients that did not progress to ACLF. Serum ATX levels were significantly higher among male ACLF patients with preclinical infection, spontaneous bacterial peritonitis or pneumonia, as compared to patients with ACLF but no spontaneous bacterial peritonitis or pneumonia. Serum ATX levels were well correlated with serum biochemical parameters of liver function and model for end-stage liver disease score. Serum ATX ≥ 584.1 ng/mL was a poor prognostic factor for ACLF (hazard ratio of 4.750, 95% confidence interval of 1.106-20.392, p=0.036). Conclusions: Serum ATX level may be a useful early warning biomarker for ACLF.

The absence of cardiac chambers, holes in the heart and abnormal connections cause the death of hundreds of people every year. The clinical team involved in the diagnosis and treatment decisions for congenital heart disease (CHD) must be consistent in their choices. Therefore, in cases of CHD there is a need for a system that is capable of segmenting the whole heart and large blood vessels in 3D efficiently, quickly, and accurately. This article proposes to fill this need by using Cascaded Volumetric Fully Convolutional Networks. The approach proposes the use of two Volumetric Fully Convolution Networks (V-Net) in sequence. The first network aims at locating the cardiac region, while the second segment the substructures of the cardiac area and the great vessels. Both networks are trained with the 2016 data set from the MICCAI Workshop on Whole-Heart and Great Vessel Segmentation of 3D Cardiovascular MRI in Congenital Heart Disease (HVSMR). The experimental results show that the proposed method has a promising potential in decision-making in CHD cases (from MR images). The approach obtained on average 98.15% for Accuracy, 94.89% for Precision, 98.81% for Specificity Coefficient, 94.27% for Sensitivity Coefficient, 93.24% for Matthews Coefficient, 80.65% for Jaccard Index, 94.20% for Dice Coefficient, and 1.61 for the Hausdorff Distance. The proposed method enables the visualization and iteration of the segmented volume in 3D so that the doctor can analyze the entire structure of the heart along with the circulatory network.

Backgrounds The 2 isoforms of paired-related homeobox 1 (PRRX1), PRRX1A and PRRX1B, are critical in regulating several kinds of cancers, and figure prominently in the maintenance of stemness and progression of epithelial-mesenchymal transition (EMT). However their differential expression in non-small cell lung cancer (NSCLC) clinical samples and exact regulatory roles in cancer stem-like cells (CSCs) remain unknown. Methods In vitro and in vivo experiments were employed to investigate the molecular mechanism. Using CSCs, mouse models, and clinical tissues, we obtained a general picture of the relatively higher level of PRRX1A compared to PRRX1B, and PRRX1A thus promoting EMT and maintaining stemness of CSCs. Results PRRX1A but not PRRX1B was upregulated in lung cancer tissues and was positively correlated with TGF-β expression. In CSCs, overexpressed PRRX1A promoted malignant behaviors via transcriptional activation of TGF-β depending on TGF-β/TGF-βR signaling pathway. PRRX1A knockdown decreased self-renewal capacity accompanied by a decrease in stemness factor expression independent of the TGF-β/TGF-βR signaling pathway. Furthermore, PRRX1A was found to tightly bind to and stabilize SOX2. PRRX1A promoted sphere formation not only by enhancing stemness via stabilizing SOX2 but also by promoting cell proliferation. Conclusions PRRX1A, but not PRRX1B, was demonstrated to have important roles in the regulation of the stemness and metastatic potential of lung cancer, which suggests the potential application of PRRX1A in cancer treatment.

Background Hereditary hemorrhagic telangiectasia (HHT) often involves the liver, and belongs to abnormal blood vessel disease. The etiology of Budd–Chiari syndrome (BCS) is not clear, but congenital vascular dysplasia is considered to be one of the causes. Liver cirrhosis due to hepatic hereditary hemorrhagic telangiectasia concomitant with BCS has not been reported. Here, we report a case of cirrhosis with hepatic hereditary hemorrhagic telangiectasia (HHHT) and BCS. Case presentation A 58-year-old woman with hepatic hereditary hemorrhagic telangiectasia showed decompensated liver cirrhosis, and abdominal imaging revealed Budd–Chiari syndrome. Disease has progressed considerably during 2.5 years after hospital discharge despite subsequent transjugular intrahepatic portosystemic shunting (TIPS). One hypothesis that might explain the coexistence of hepatic hereditary hemorrhagic telangiectasia and Budd–Chiari syndrome in this patient is ischemia and thrombosis of hepatic veins. Conclusions Further studies are required to evaluate the relationship between HHHT and BCS. Our observations already challenged the TIPS therapeutic strategy in BCS secondary to HHHT patients.

Zhundong coalfield is a super-large coal reserve, with high-alkali feature exacerbating ash deposition. Oxy-fuel combustion technology could propel the clean utilization of Zhundong high-alkali coal. While the ash deposition behavior of high-alkali coal under oxy-fuel condition has yet to be sufficiently investigated. The present study compared the differences of ash deposits between oxy-fuel and air combustion, and also examined the effects of oxygen content on ash deposition mechanism, employing a drop-tube furnace equipped with a specially designed sampling probe and some analysis methods, such as X—ray diffraction equipment, simultaneous thermal analyzer, etc. Experimental results indicated that ash deposition was weaker, with fewer contents of sodium chloride, calcium sulphate and less agglomeration ash in oxy-fuel atmosphere compared to the air case with same oxygen content. The content of the ash particle distributed in the range of 0–40 μm was up to 60% under oxy-fuel condition. The first weight loss of ash deposits, around 850 °C, was put down to the decomposition of carbonate and the second one, about 1150 °C, was ascribed to the decomposition of the sulphate minerals in the thermal process. Ash deposition worsened with more large particles (>120 μm), as the oxygen content rose. Sodium chloride content reached 9.7% with 50% oxygen content. The present study not only focuses on the morphology and chemical components, but also probes into the thermal volatility of ash deposits, which benefits the further understanding of the ash deposition mechanism and utilization of Zhundong high-alkali coal during oxy-fuel combustion.

Unlike autonomous ground vehicles (AGVs), unmanned aerial vehicles (UAVs) have a higher dimensional configuration space, which makes the motion planning of multi-UAVs a challenging task. In addition, uncertainties and noises are more significant in UAV scenarios, which increases the difficulty of autonomous navigation for multi-UAV. In this letter, we proposed a two-stage reinforcement learning (RL) based multi-UAV collision avoidance approach without explicitly modeling the uncertainty and noise in the environment. Our goal is to train a policy to plan a collision-free trajectory by leveraging local noisy observations. However, the reinforcement learned collision avoidance policies usually suffer from high variance and low reproducibility, because unlike supervised learning, RL does not have a fixed training set with ground-truth labels. To address these issues, we introduced a two-stage training method for RL based collision avoidance. For the first stage, we optimize the policy using a supervised training method with a loss function that encourages the agent to follow the well-known reciprocal collision avoidance strategy. For the second stage, we use policy gradient to refine the policy. We validate our policy in a variety of simulated scenarios, and the extensive numerical simulations demonstrate that our policy can generate time-efficient and collision-free paths under imperfect sensing, and can well handle noisy local observations with unknown noise levels.

In this work, the authors propose and simulate a double L-shaped gate tunnel field-effect transistor (DLG-TFET) with the covered source-channel. The proposed structure improves the ON-state current by increasing the linear tunnelling area and has excellent subthreshold characteristics. The simulation focuses on the performance improvement of the device under different longitudinal gate length L g , interlayer silicon thickness T si , gate and source overlap length L ov , and covered source depth L s . For optimal parameters, the ON-state current of the proposed DLG-TFET increases up to 3.53 × 10 -5 A/μm, and the current switch ratio( I on / I off ) is 4.28 × 10 11 at room temperature, moreover, a minimum subthreshold swing (SSmin) and an average subthreshold swing (SSave) are as low as 32.2 and 52.9 mV/Dec, respectively. Meanwhile, this work uses mixed device-circuit simulations to predict the performance of the inverter circuit implemented with proposed DLG-TFET.

Background Neurophysiological and radiological studies provide accumulating evidence for the involvement of the brainstem in the pathogenesis of restless legs syndrome (RLS). The analysis of the various subregions of the brainstem may help us better understand the pathophysiological mechanisms underlying the disorder. In this study, we investigated the structural and functional changes in the various subregions of the brainstem in RLS patients. Methods The subregional changes in gray matter density and functional connectivity in the brainstem were analyzed in 20 drug-naive idiopathic RLS patients, as well as 18 normal control (NC) subjects for comparison. Correlation analyses and multivariate pattern analyses using linear support vector machine (SVM) were conducted. Results We found significantly increased gray matter density in two clusters in the pons (designated pons_1 and pons_2) and in one cluster in the midbrain in RLS patients compared with NC subjects. Further functional connectivity analyses revealed significantly decreased functional connectivity between the midbrain and the right middle occipital gyrus, between pons_1 and the right orbital part of the superior frontal gyrus, and between pons_2 and the right parahippocampus in RLS compared with NC. Moreover, the functional connectivity between pons_2 and the right supplementary motor area (SMA) was significantly increased in RLS compared with NC. This change in RLS was marginally correlated with RS_RLS scores in the RLS patients. SVM-based classification showed an AUC of 0.955 using gray matter density of pons_2, and functional connectivity between pons_2 and SMA as features. Conclusion Collectively, our findings suggest that changes in gray matter density and functional connectivity in the pons may play a pathologic role in RLS. Furthermore, these abnormal changes in the pons might help to discriminate RLS from healthy subjects.

Purpose The purpose of this conceptual paper is to encourage community college leaders to make greater use of the human resources organizational frame in understanding their organizations and implementing measures to support its students. Design/methodology/approach The methodological approach: Concepts are drawn from key texts examining human resources organizational frame analysis and community college leadership to locate areas of community college policy development and operations that resonate with tenets of this organizational frame. Findings Connections between some of the typical operations and policies of community colleges and the analytical tenets and concerns of the human resources frame are explored. Research limitations/implications More in-depth literature analysis could well lead to the discussion of additional measures animated by the human resources frame that can be taken to better support students and their learning. Practical implications These connections between the human resources frame and community college policy and methods of operation lead to the authors’ recommendation that community college leaders should make particular efforts think and act with the human resources frame in mind. Emerging issues that are consistent with the concerns and tenets of this frame can be highlighted and recognized for further use in leadership and management practice. Social implications Community colleges are critical in human capital development for all societal sectors. A human resources perspective puts people and human values at the center of organizational analysis. Originality/value We add emphasis to leading recommendations for understanding and practice of community colleges through multiple frames. We suggest that the concerns of the human resource organizational frame can help leaders provide thought and action that has additional relevance and possibility.

In recent years, action recognition has become a hot research topic in the computer vision and machine learning domain. Despite many well-designed action recognition approaches have been proposed, we point out that some limitations still exist including the separated fusion of different Spatio-temporal features and the reconstruction classification model, and the requirement of similar environmental conditions when capturing the training and testing data. Thus, research interest has shifted from traditional action recognition towards cross-domain action recognition. To solve these limitations, in this work, we propose a novel multimodal pairwise discrimination network (short for MPD) for cross-domain action recognition that is an end-to-end network architecture. In MPD, it can jointly fuse different Spatio-temporal features from the video, learn domain invariant features for different action domains (source and target domains), and build the classification model. To characterize the shift between these domains, subnetwork parameters in corresponding layers of MPD are required to be relevant, but not identical. Besides, the domain invariant feature discrimination needs to be improved. Extensive experimental results on two different public benchmarks including indoor environment and outdoor environment demonstrate that our MPD solution can significantly outperform state-of-the-art methods with a 4% to 20% improvement in average accuracy.

Unmanned Aerial Vehicles are constantly being using in professional activities that require higher precision in navigating and positioning the aircraft during operation. Advanced location technologies such as Global Navigation Satellite System and Real-Time Kinematic are widely used, however, they depend on an area with transmission coverage. In this approach, this article presents a visual navigation methodology based on topological maps. We compared the performance of consolidated classifiers such as Bayesian classifier, k-nearest neighbor, Multilayer Perceptron, Optimal Path Forest and Support Vector Machines (SVM). They are evaluated with attributes returned by last generation resource extractors such as Fourier, Gray Level Co-Occurrence and Local Binary Patterns (LBP). After analyzing the results we found that the combination of LBP and SVM obtained the best values in the evaluation metrics considered, among them, 99.99% Specificity and 99.98% Precision in the navigation process. SVM reached 5.49787 s in combination with LBP completes the training in 5.49787 s. Concerning the testing time, SVM achieving 80.91 ms in association with LBP.

The acceptor phase, which affects the free carrier transport by trapping the photogenerated minority carrier in the active layer, plays an important role in organic phototransistors (OPTs) based on a bulk heterojunction (BHJ). In this work, the FBT-Th4(1,4):PC61BM blend film with high mobility is selected as the active layer to construct the OPT. A model of the action of minority carrier movement on hole transmission is established by using the change rule of device performance under different donor/acceptor ratios. This model is tested and validated using PTB7:PC61BM-based OPT with low mobility. The results show that a continuous transmission channel of photogenerated minority carrier tends to form in the OPT under high concentration doping, which increases the probability that a minority carrier would recombine with the holes, leading to poor device performance. These results can provide practical guidance for the preparation of high-performance OPT devices. The optimized FBT-Th4(1,4) : PC61BM device with a low D/A ratio (∼10 : 1) obtained shows ultrahigh photoelectric detection performance (gain = 4.7 × 105, D* = 1.4 × 1016 Jones).

Laser diode (LD) lighting is highly luminescent and safe due to the replacement of traditional wires with optical fibers, and is suitable for museum lighting. However, the current LD lighting has a low color rendering index (CRI) that affects the visual splendor because of the lack of a red component in the spectra of the photoluminescent transparent ceramic (TC). In this study, a series of Lu2.98Al5−2xSixO12:0.02Ce3+, xMn2+ (x = 0–0.12) photoluminescent TCs with a transmittance of T = 48.5–78% and a spectrum adjustable from 500 to 800 nm are synthesized, which show excellent thermal stability. Their photoluminescence property is retained at 99% of the initial value at 425 K when the doping of Mn2+ is x = 0.01. The color rendering index of the LD system assembled with these photoluminescent TCs and high-power blue LDs reached 80.1, while the correlated-color temperature (CCT) is 3298 K. These characteristics shows the LD system is promising for application in museum lighting.

Multiple-operators (multi-OPs) spectrum sharing mechanism can effectively improve the spectrum utilization in fifth-generation (5G) wireless communication networks. The secondary users are introduced to opportunistically access the licensed spectrum of idle operators (OPs). However, the identity privacy and data security issues raise great concerns about the secure spectrum sharing among multi-OPs. To address these challenges, a permissioned blockchain trust framework is proposed for the spectrum sharing in multi-OPs wireless communication networks in this paper. The Multi-OPs Spectrum Sharing (MOSS) smart contract is designed on the constructed permissioned blockchain to implement the spectrum trading among multi-OPs. Without the need of trustless spectrum broker, the MOSS smart contract enforces multi-OPs to share the spectrum truthfully and designs a punishment mechanism to punish malicious OPs. The MOSS smart contract is tested on the Remix integrated development environment (IDE) and the gas costs of MOSS smart contract is estimated. The performance analysis of the proposed permissioned blockchain trust framework demonstrates that the privacy, openness and fairness of the proposed solution are better than traditional spectrum allocation solutions.

MicroRNAs (miRNAs) are involved in tumorigenesis, progression, recurrence, and drug resistance of hepatocellular carcinoma (HCC). However, few miRNAs have been identified and entered clinical practice. Herein, we report that microRNA (miR)-552 is upregulated in HCC tissues and has an important function in liver tumor-initiating cells (T-ICs). Functional studies revealed that a forced expression of miR-552 promotes liver T-IC self-renewal and tumorigenesis. Conversely, miR-552 knockdown inhibits liver T-IC self-renewal and tumorigenesis. Mechanistically, miR-552 downregulates phosphatase and tensin homolog (PTEN) via its mRNA 3′ UTR and activates protein kinase B (AKT) phosphorylation. Our clinical investigations elucidated the prognostic value of miR-552 in HCC patients. Furthermore, miR-552 expression determines the responses of hepatoma cells to sorafenib treatment. The analysis of patient cohorts and patient-derived xenografts (PDXs) further demonstrated that miR-552 may predict sorafenib benefits in HCC patients. In conclusion, our findings revealed the crucial role of the miR-552 in liver T-IC expansion and sorafenib response, rendering miR-552 an optimal target for the prevention and intervention in HCC.

Colorectal cancer (CRC) is the most common gastrointestinal tract cancer worldwide and is associated with high morbidity andmortality. The development of nanosized drug delivery systems has provided a new direction in CRC treatment. Among thesesystems, magnetic nanoparticle (MNP)-based multifunctional platforms provide a novel strategy for magnetic resonance imaging(MRI)-related cancer theranostics. At the beginning of this original review, the carcinogenesis and treatment status of CRC aresummarized. Then, diversified preparation and functionalization methods of MNPs are systematically analyzed, followed by MRIinvolvedtheranostic strategies. The latest progress in MRI-mediated multimode diagnosis and image-guided targeted therapy inCRC management is the main focus. Finally, the major challenges in promoting MRI-induced precise theranostics of CRC in clinicalpractice are discussed. Cite this article as: Li Y, Xin J, Sun Y, Han T, Zhang H, An F. Magnetic resonanceimaging-guided and targeted theranostics of colorectal cancer. Cancer BiolMed. 2020; 17: 307-327. doi: 10.20892/j.issn.2095-3941.2020.0072

The classification and segmentation of pathologies through intelligent systems is a significant challenge for medical image analysis and computer vision systems. Diseases, such as lung problems and strokes, have a serious effect on human health worldwide. Lung diseases are among the leading causes of death worldwide, lagging behind strokes that in 2016 became the second leading cause of death from illnesses. Computed tomography (CT) is one of the main clinical diagnostic exams, linked to Computerized Diagnostic Assistance Systems (CAD), which are becoming solutions for health technologies. In this work, we propose a method based on the health of things for the classification and segmentation of CT images of the lung and hemorrhagic stroke. The system called HTSCS - Medical Images: Health-of-Things System for the Classification and Segmentation of Medical Images, uses transfer learning between models based on deep learning combined with classical methods for fine-tuning. The proposed method obtained excellent results for the classification of hemorrhagic stroke and pulmonary regions, with values of up to 100% accuracy. The models also achieved outstanding performances for segmentation, with Accuracy above 99 % and Dice coefficient above 97% in the best cases with an average segmentation time between 0.095 and 1.7 seconds. To validate our approach, we compared our best models for the segmentation of lung and hemorrhagic stroke in CTs, with related works found in state of the art. Our method brings an innovative approach to classification and segmentation through the use of the Health of Things for different types of medical images with promising results for medical image analysis and computer vision fields.

With proliferation of smart devices and wireless applications, the recent few years have witnessed data surge. These massive data needs to be stored, transmitted, and processed in time to exploit their value for decision making. Conventional cloud computing requires transmission of massive amount of data in and out of core network, which can lead to longer service latency and potential traffic congestion. As a new platform, mobile edge computing (MEC) moves computation and storage resources to edge network in proximity to the data source. With MEC, data can be processed locally, and thus mitigate issues of latency and congestion. However, it is very challenging to reap the benefits of MEC everywhere due to geographic constraints, expensive deployment cost, and immoveable base stations. Because of easy deployment and high mobility of unmanned aerial vehicles (UAVs), air-ground integrated mobile edge networks (AGMEN) is proposed, where UAVs are employed to assist the MEC network. Such an AGMEN expects to provide MEC services ubiquitously and reliably. In this article, we first introduce the characteristics and components of UAV. Then, we will review the applications, key challenges, and current research technologies of AGMEN, from perspectives of communication, computation, and caching, respectively. Finally, we will discuss some essential research directions for AGMEN.