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The issue of Electroencephalogram (EEG)-based emotion recognition has great academic and practical significance. Currently, there are numerous researches trying to address this issue in the literature. Particularly, transfer learning has gradually become a new methodological trend for the issue in company with the popularity of deep learning. Motivated by capturing the research panorama, summarizing the technological essence, and forecasting the advancement tendency of transfer learning for EEG-based emotion recognition, this paper contributes a review work. This work mainly includes five aspects: a) introducing the issue of EEG-based emotion recognition and expounding the importance of transfer learning for it; b) analyzing the transfer learning framework and comparing it with the traditional ones; c) elucidating the issue difficulties and explaining the suitability and capability of transfer learning for this issue; d) summarizing, categorizing and exemplifying the typical transfer learning methods for this issue; e) clarifying the methodological merits, discussing the challenging problems, and predicting the prospective development of transfer learning for the issue. We expect these contributions can inspire innovation and reformation of the transfer learning methodology for EEG-based emotion recognition as well as other relevant topics in the not-so-far future.

It has been widely recognized that the efficient training of neural networks (NNs) is crucial to classification performance. While a series of gradient-based approaches have been extensively developed, they are criticized for the ease of trapping into local optima and sensitivity to hyperparameters. Due to the high robustness and wide applicability, evolutionary algorithms (EAs) have been regarded as a promising alternative for training NNs in recent years. However, EAs suffer from the curse of dimensionality and are inefficient in training deep NNs (DNNs). By inheriting the advantages of both the gradient-based approaches and EAs, this article proposes a gradient-guided evolutionary approach to train DNNs. The proposed approach suggests a novel genetic operator to optimize the weights in the search space, where the search direction is determined by the gradient of weights. Moreover, the network sparsity is considered in the proposed approach, which highly reduces the network complexity and alleviates overfitting. Experimental results on single-layer NNs, deep-layer NNs, recurrent NNs, and convolutional NNs (CNNs) demonstrate the effectiveness of the proposed approach. In short, this work not only introduces a novel approach for training DNNs but also enhances the performance of EAs in solving large-scale optimization problems.

With the development of neural architecture search, the performance of deep neural networks has been considerably enhanced with less human expertise. While the existing work mainly focuses on the development of optimizers, the design of encoding scheme is still in its infancy. This article thus proposes a novel encoding scheme for neural architecture search, termed action command encoding (ACEncoding). Inspired by the gene expression process, ACEncoding defines several action commands to indicate the addition and clone of layers, connections, and local modules, where an architecture grows from empty according to multiple action commands. ACEncoding provides a compact and rich search space that can be explored by various optimizers efficiently. Furthermore, a surrogate-assisted performance evaluator is tailored for ACEncoding, termed sequence-to-rank (Seq2Rank). By integrating the Seq2Seq model with RankNet, Seq2Rank embeds the variable-length encoding of ACEncoding into a continuous space, and then predicts the rankings of architectures based on the continuous representation. In the experiments, ACEncoding brings improvement to neural architecture search with existing encoding schemes and Seq2Rank shows better accuracy than existing performance evaluators. The neural architectures obtained by ACEncoding and Seq2Rank have competitive test errors and complexities on image classification tasks, and also show high transferability between different data sets.

PurposeA disconnect often exists between those with the expertise to manage and analyze complex, multi-source data sets, and the clinical, social services, advocacy, and public health professionals who can pose the most relevant questions and best apply the answers. We describe development and implementation of a cancer informatics infrastructure aimed at broadening the usability of community cancer data to inform cancer control research and practice; and we share lessons learned. MethodsWe built a multi-level database known as The Ohio Cancer Assessment and Surveillance Engine (OH-CASE) to link data from Ohio’s cancer registry with community data from the U.S. Census and other sources. Space- and place-based characteristics were assigned to individuals according to residential address. Stakeholder input informed development of an interface for generating queries based on geographic, demographic, and disease inputs and for outputting results aggregated at the state, county, municipality, or zip code levels. ResultsOH-CASE contains 723,410 patient records for Ohioans diagnosed with cancer from 1/1/2006 – 12/31/2017 across 88 counties containing 1215 municipalities and 1197 zip codes. Stakeholder feedback from cancer center community outreach teams, advocacy organizations, public health, and researchers suggests a broad range of uses of such multi-level data resources accessible via a user interface. ConclusionOH-CASE represents a prototype of a transportable model for curating and synthesizing data to understand cancer burden across communities. Beyond supporting collaborative research, this infrastructure can serve the clinical, social services, public health, and advocacy communities by enabling targeting of outreach, funding, and interventions to narrow cancer disparities.

Surgical management of patients with comorbid long-term myasthenia gravis (MG) is particularly challenging and MG thus represents an independent risk factor for perioperative complications. However, few studies have reported on the perioperative assessment, prevention measures, and risks in MG patients undergoing major surgery, especially for anterior cervical spine surgery. We herein report the rare case of a 62-year-old man with a 20-year history of MG, who was admitted to our hospital with diagnosis of degenerative cervical spondylosis. He safely underwent anterior cervical corpectomy of C4, discectomy of C5-6, and fusion of C3-6. Intraoperative motor evoked potential was recorded to detect significant improvement after decompression. However, the patient suffered from progressive dysphagia, bucking, and hyperpyrexia 20 days after the initial operation. Imaging revealed titanium cage sliding and graft dislodgement. Secondary surgery was performed for posterior internal fixation from C2-7 and anterior revision from C3-6 after Halo-Vest traction, antibiotic treatment, and immunoglobulin therapy. He underwent a series of postoperative treatments, including cervicothoracolumbosacral orthosis, atomization inhalation, chest physiotherapy, antibiotics, and nutritional support. His condition improved markedly and he had no recurrence of symptoms during the 6-month follow-up. It is the rare reported case of anterior cervical spinal surgery in a patient with MG. This rare case indicates a relative contraindication to anterior-only approaches especially with multiple levels for MG patients with cervical spondylosis. Posterior approach, intraoperative monitoring, osteoporosis, postoperative strong brace protection, and supportive management should be considered for patients who were on large doses of steroids for long duration of time, given the lack of sufficient bone mineral density.

Pedestrian positioning with wearable devices is a significant application of attitude tracking. It tracks the attitude (with heading angle being the most important part) of the device in real time and provides positioning services for users based on the information of step length provided by Pedestrian Dead-Reckon (PDR), which is a cheap and efficient positioning method at present. However, amid a train of positioning methods, the joint estimate of tracking is given by a train of methods based on the direction of gravity and the earths magnetic field direction. Considering the measurement of gravity that the gravity accelerometer is exposed to heavy noise due to the complex movement of human body during walking with uniform swing arm posture and forward speed, this paper proposed a novel estimate method based on the Kalman filter with multi-state constraints and the usage of low-cost sensors, which fulfills the estimation with the sequential observation of magnetic field. Compared with other related work, this method proposed in this paper eliminates the dependence on gravity direction, avoiding the influence of heavy noise caused by additional linear acceleration in motion state, and reduces the influence of insufficient observation when using magnetic field observation alone. The performance of the proposed method is evaluated by real-world experimentation results.

Background Hand foot and mouth disease (HFMD) is a public health concern. Studies on air pollution and the lengths of hospital stay (LOS) of HFMD are scarce. Methods We characterized the clinic demographic features of 5135 hospitalized HFMD in Nanjing, China from 2012 to 2017, and analyzed the association between short-term exposure to PM2.5 as well as its components (OM, BC, SO42−, NH4+, NIT, SOIL and SS) and the LOS of HFMD. Results Among them 98.62% were aged 0–6 years old, and 3772 (73.46%) were hospitalized for seven days or less. The LOS of HFMD children was different in different ages, illness onset years and illness onset seasons (P2.5 concentrations, LOS of HFMD increased by 0.52(0.33, 0.71), 0.50 (95% CI, 0.31–0.69) and 0.46 (95% CI, 0.28–0.65) day in adjusted models at lag 3 days, lag 7days and lag 14 days, respectively. In addition, per IQR increase of BC, SO42−, NH4+, NIT and SOIL were also significantly associated with the LOS of HFMD. Conclusions Our findings corroborated the hypothesis that short-term PM2.5 exposure was associated with increased the LOS of HFMD, and its components (BC, SO42−, NH4+, NIT and SOIL) of PM2.5 might play a key role in the prolonged LOS of HFMD.

Objectives Intervertebral disc (IVD) degeneration is an important disease with no efficient biological therapy identified. Autophagy, a wildly known therapeutic target for human disease, has been demonstrated to be activated under hypoxia, with underlying mechanism remains elusive. Thus, this study aims to specify the role of autophagy in IVD degeneration, the regulating mechanism of hypoxia-inducing autophagy, and the therapeutic value of autophagy for IVD degeneration. Methods RNA-seq was used to screen the primary pathway affected in NP cells under hypoxia, the specific link between hypoxia and autophagy were investigated using ChIP-seq and dual luciferase reporter assay. Conditional ATG7 knockout mice (ATG7-/-) were constructed for assessing the effect of autophagy on IVD degeneration, and puncture induced mice model of IVD degeneration were used for intradiscal injection to evaluate the therapeutic value of autophagy. Results We demonstrated that hypoxia induces autophagy by transcriptional activation of autophagic gene LC3B and ATG7, which is controlled by PERK signaling. Then, we observed that inhibiting autophagy or PERK signaling leads to impaired NP cell viability and function, furthermore, using ATG7 knockout (ATG7-/-) mice, we identified the protective role of autophagy in IVD. Furthermore, we found that intradiscal injection of PERK signaling agonist, CCT020312, significantly restores the degeneration level of needle punctured mice IVD. Conclusion We showed that the activation of PERK signaling upon hypoxia serves as a vital mechanism to induce autophagy and identified the therapeutic value of PERK signaling agonist for IVD degeneration treatment.

Based on the hole-drilling strain sensing method, a ring Fiber Bragg Grating (FBG) array is proposed to realize comprehensive and convenient measurement of residual stress for homogeneous or inhomogeneous materials. All FBG sensors are arranged tangentially along the edge of the ring. With the ring array around the drilled hole, more detailed information of the residual stress can be obtained such as the location and the degree of inhomogeneity. The tangential arrangement of FBG sensors can achieve comparable measurement results to the radial arrangement but it brings convenience for the drilling process without any overlap upon the hole position. This method promotes the application of the FBG sensors in the residual stress measurement field.

The optimal cutoff point for evaluating the prognosis of localized renal cell carcinoma (LRCC) remains unclear. This study aimed to verify the efficacy of tumor diameter in the 2010 American Joint Committee on Cancer (AJCC) TNM staging system and contribute to the modification of TNM staging on the prognosis of this disease. A total of 3748 patients with LRCC were enrolled and grouped according to the 2010 AJCC TNM staging system. COX analysis was used to stratify the prognosis. The optimal cutoff point of the tumor diameter in the T1 and T2 prognosis was explored. There were 3330 (88.9%) patients in stage T1 and 418 (11.1%) in stage T2. The cancer-specific mortality rate was 2.7% (100/3748). The mean follow-up was 49.8 months. A tumor diameter of 7 cm can determine the prognosis of patients at stages T1 and T2; however, 4.5 cm and 11 cm as the cutoff points for T1 and T2 sub-classification of patients with LRCC might show better recognition ability than 4 cm and 10 cm, respectively. The 2010 AJCC TNM stage can predict the prognosis of LRCC in stages T1 and T2. In addition, a tumor diameter of 4.5 cm and 11 cm might be the optimal cutoff points for the sub-classification of stages T1 and T2.

Background The correlation between modified bladder outlet obstruction index (MBOOI) and surgical efficacy still remains unknown. The purpose of the study was to investigate the clinical value of the MBOOI and its use in predicting surgical efficacy in men receiving transurethral resection of the prostate (TURP). Methods A total of 403 patients with benign prostate hyperplasia (BPH) were included in this study. The International Prostate Symptom Score (IPSS), quality of life (QoL) index, transrectal ultrasonography, and pressure flow study were conducted for all patients. The bladder outlet obstruction index (BOOI) (PdetQmax–2Qmax) and MBOOI (Pves–2Qmax) were calculated. All patients underwent TURP, and surgical efficacy was accessed by the improvements in IPSS, QoL, and Qmax 6 months after surgery. The association between surgical efficacy and baseline factors was statistically analyzed. Results A comparison of effective and ineffective groups based on the overall efficacy showed that significant differences were observed in PSA, Pves, PdetQmax, Pabd, BOOI, MBOOI, TZV, TZI, IPSS-t, IPSS-v, IPSS-s, Qmax, and PVR at baseline (p max, and the overall efficacy. Additionally, the ROC analysis further verified that MBOOI was more optimal than BOOI, TZV and TZI in predicting the surgical efficacy. Conclusion Although both MBOOI and BOOI can predict the clinical symptoms and surgical efficacy of BPH patients to a certain extent, however, compared to BOOI, MBOOI may be a more useful factor that can be used to predict the surgical efficacy of TURP. Trial registration retrospectively registered.

High permittivity materials for a gigahertz (GHz) communication technology have been actively sought for some time. Unfortunately, in most materials, the dielectric constant starts to drop as frequencies increase through the megahertz (MHz) range. In this work, we report a large dielectric constant of ∼800 observed in defect-mediated rutile SnO2 ceramics, which is nearly frequency and temperature independent over the frequency range of 1 mHz to 35 GHz and temperature range of 50-450 K. Experimental and theoretical investigations demonstrate that the origin of the high dielectric constant can be attributed to the formation of locally well-defined Zn2+-Nb4+ defect clusters, which create hole-pinned defect dipoles. We believe that this work provides a promising strategy to advance dipole polarization theory and opens up a direction for the design and development of high frequency, broadband dielectric materials for use in future communication technology.

Purpose To develop an end-to-end deep learning solution for quickly reconstructing radial simultaneous multi-slice (SMS) myocardial perfusion datasets with comparable quality to the pixel tracking spatiotemporal constrained reconstruction (PT-STCR) method. Methods Dynamic contrast enhanced (DCE) radial SMS myocardial perfusion data were obtained from 20 subjects who were scanned at rest and/or stress with or without ECG gating using a saturation recovery radial CAIPI turboFLASH sequence. Input to the networks consisted of complex coil combined images reconstructed using the inverse Fourier transform of undersampled radial SMS k-space data. Ground truth images were reconstructed using the PT-STCR pipeline. The performance of the residual booster 3D U-Net was tested by comparing it to state-of-the-art network architectures including MoDL, CRNN-MRI, and other U-Net variants. Results Results demonstrate significant improvements in speed requiring approximately 8 seconds to reconstruct one radial SMS dataset which is approximately 200 times faster than the PT-STCR method. Images reconstructed with the residual booster 3D U-Net retain quality of ground truth PT-STCR images (0.963 SSIM/40.238 PSNR/0.147 NRMSE). The residual booster 3D U-Net has superior performance compared to existing network architectures in terms of image quality, temporal dynamics, and reconstruction time. Conclusion Residual and booster learning combined with the 3D U-Net architecture was shown to be an effective network for reconstructing high-quality images from undersampled radial SMS datasets while bypassing the reconstruction time of the PT-STCR method.

The construction of large and medium-sized hydropower projects involves multiple stakeholders. The way various parties interact affects the construction and management of a project. As the construction of hydropower projects has progressed, the governance of the coordination relationship among stakeholders has become a more pressing and troublesome issue in project management research. We propose an Entropy-TOPSIS measurement method for hydropower project coordination stakeholders, and we use it to assess the degree of coordination among various stakeholders in the Sichuan JL. The results show that the owner, the supervision unit, and the subcontractor have good overall coordination, with a coordinated development degree of over 0.519. With an average coordinated development degree of over 0.361, the design unit and the supplier are next. The overall coordination of the general contractor is the worst, with a coordinated development degree of only 0.201. As a result, in this case, it is necessary to improve the general contractor's project management capabilities so that they can manage other stakeholders in a targeted and coordinated manner.

Based on magnetic medium theory, a newly invited magnetic corrosion detector (MCD) showed great potential in quantitative monitoring the corrosion process of steel rebar in concrete. To furtherly explore the application performance of MCD, a numerical model was established to simulate the magnetic induction intensity variation caused by corrosion of steel rebar. And the influence of the length and the positioning variance of steel rebar on the measurement were discussed based on experimental and numerical investigation. The research results indicate that the numerical simulation is a valid approach to reveal the essential performance of MCD in measuring the corrosion ratio of steel rebar in concrete. Based on the geometric and physical properties of MCD, the corrosion ratio of the steel rebar can be effectively measured. And the positioning variance of steel rebar has significant influence on the precision and sensitivity of MCD. It is suggested that the steel rebar should be placed right at the center of the test area during the measurement to achieve a high accuracy.

Background We have recently showed that atorvastatin (ATO) combined with low dose of dexamethasone (DEX) was more efficacious in treating patients with chronic subdural haematoma (CSDH) than ATO monotherapy. This study was designed to investigate the underlying mechanisms of the improved efficacy of this combined therapy. Methods Mass spectrometry was performed to quantitatively detect drugs in haematoma fluids and serum samples from CSDH patients and also in cultured macrophages after treatment with either ATO alone or in combination with DEX. The differentiation and apoptosis of macrophages were evaluated using flow cytometry. The expression of cytokines, chemokines and angiogenesis-related proteins was evaluated using proteome profile arrays, immunoblots and ELISA, respectively. Results ATO was detected in haematoma fluids and serum samples, whose levels were increased significantly in samples collected from patients treated with both ATO and DEX. ATO was also increased in cultured macrophages treated with ATO and DEX. The numbers of M1-polarized macrophages were higher than the M2 phenotype in the haematoma fluids of patients. Cultured macrophages treated with ATO and DEX had reduced numbers of M1-polarized macrophages, increased numbers of M2-polarized macrophages as compared to monotherapies, and decreased rate of apoptosis induced by high-dose DEX. DEX enhanced the anti-inflammatory and anti-angiogenic activity of ATO by suppressing VEGFA and other inflammatory angiogenic factors. Consistent with the finding, patients responded well to the drug treatments had lower serum levels of VEGFA. Conclusions We have shown for the first time that ATO given orally was detected in CSDH haematoma fluids. DEX enhances the anti-inflammatory and anti-angiogenic effects of ATO, primarily by increasing the presence of ATO in haematoma and macrophages and by regulating the functions of macrophages.

Enolase 1 (ENO1) is a moonlighting protein, function as a glycolysis enzyme, a plasminogen receptor and a DNA binding protein. ENO1 play an important role in the process of cancer development. The transcription, translation, post-translational modifying activities and the immunoregulatory role of ENO1 at the cancer development is receiving increasing attention. Some function model studies have shown that ENO1 is a potential target for cancer treatment. In this review, we provide a comprehensive overview of the characterization, function, related transduction cascades of ENO1 and its roles in the pathophysiology of cancers, which is a consequence of ENO1 signaling dysregulation. And the development of novels anticancer agents that targets ENO1 may provide a more attractive option for the treatment of cancers. The data of sarcoma and functional cancer models indicates that ENO1 may become a new potential target for anticancer therapy.

Synthetic aperture radar automatic target recognition (SAR-ATR) is a hotspot in the field of remote sensing, which has been widely used in disaster monitoring, environmental monitoring, resource exploration, and crop yield estimates. In recent years, deep convolutional neural networks (DCNNs) have achieved promising performance among a variety of supervised classification methods under the condition of sufficiently labeled samples. However, it is expensive and time-consuming to collect large amounts of labeled samples suitable for DCNNs in SAR domains. To reduce the dependence of SAR-ATR on labeled samples, in this work, a consistency regularization teacher–student semi-supervised (CRTS) method for SAR-ATR is proposed, in which consistency regularization is applied to analyze and divide unlabeled samples and the teacher–student structure is introduced to generate pseudo-labels for the divided unlabeled samples. Firstly, by using consistent pseudo-label prediction, unlabeled samples are divided into consistent unlabeled samples and confident unlabeled samples. Then, in order to improve the quality of pseudo-labeled labels, the student model is used to generate a pseudo-label for consistent unlabeled samples, and the teacher model which is ensembled by the other two student models labels the confident unlabeled samples. Finally, these pseudo-label unlabeled samples are mixed with the labeled samples and trained together to improve recognition performance. Experiments are conducted on the MSTAR dataset, and the results demonstrate the effectiveness of the proposed method. As compared with several state-of-the-art methods, the recognition accuracy shows the superiority of the proposed method, especially when the training dataset is limited.

Objective We focus on providing the first comprehensive national dataset on the incidence, injury aetiology and mortality of TSCI in China. Methods A multi-stage stratified cluster sampling method was used. We included TSCI cases from all hospitals in three regions, nine provinces and 27 cities in China via search of electronic medical records and retrospectively analysed the characteristics of TSCI in China from 2009 to 2018. We estimated the incidence of TSCI in the total population and subgroups. Results There were 5954 actual cases in 2009, corresponding to a total estimated TSCI incidence of 45.1 cases per million population (95% CI, 44.0–46.3). There were 10,074 actual cases in 2018, corresponding to a total estimated TSCI incidence of 66.5 cases per million population (95% CI, 65.2–67.8) (P P Conclusions The TSCI incidence increased significantly from 2009 to 2018. The incidence in the elderly populations was consistently high and continues to increase over time. The mortality of TSCI patients in hospitals is relatively low and continues to decrease each year, but elderly individuals remain at a high risk of hospital death.

After decades of research, it has been widely recognized that complex diseases are caused by the dysfunction of biological systems induced by disease-associated genes. To understand the molecular basis of complex diseases, many efforts have been devoted to the identification of disease-related gene modules in the last two decades, by means of exploring the interaction networks constructed based on heterogeneous information. However, many existing approaches ignore the personalized features of disease samples and cannot identify a dense module having strong association with the disease. In this paper, an evolutionary multi-objective optimization based approach is proposed for disease module identification. The proposed approach constructs a sample-specific network for each disease sample to involve their personalized features, then optimizes both the association of the module with the disease and the intra-link density of the module by using a multi-objective genetic algorithm. According to the experimental results on the asthma gene expression dataset, the proposed approach is superior over some state-of-the-art disease module identification approaches. Furthermore, the identified disease module is used in the classification of disease and control samples, which obtains lower classification error rate than existing approaches.

Objective: The aim of this study is to validate the efficacy and reliability of two predictive models for postoperative fever after retrograde intrarenal surgery (RIRS) in pediatric patients Materi...

Due to the complexity of the real world, effective consideration of the ambiguity and reliability of information is a challenge that must be addressed by the correct decision of the expert system. Z-number provides us with a good idea because it describes the probability of the random variable and the possibility measure. Recently, Yager presented a soft likelihood function that effectively combines probabilistic evidence to deal with the conflict information. This article generalizes Yager's soft likelihood function based on Z-numbers and proposes a Z-numbers soft likelihood function (ZSLF) decision model. The application examples show the rationality and effectiveness of the method. The comparison and discussion further show the advantages of the ZSLF decision model.

Aim This study aims to evaluate the feasibility and advantages of immediate urinary catheter removal compared with prolonged indwelling catheterization in lung cancer lobectomy. Design This study was designed as a prospective, single‐centre, randomized and open‐label clinical study. Methods People with lung cancer undergoing lobectomy/pneumonectomy were recruited and randomly allocated to two groups. One group had their urinary catheter removed immediately while the other group had it removed 48 hr after surgery. Results No significant difference in the incidence of postoperative urinary retention (POUR) was observed between the two groups. However, the incidence of postoperative catheter‐associated urinary tract infection (CAUTI) in the immediate removal group (6.7%) was lower than the control group (17.2%) (p = .030). Furthermore, the incidence of catheter‐associated emergence agitation (CAEA) in the control group (25.3%) was higher than the immediate removal group (8.9%) (p = .007). The average length of hospital stay of the immediate removal group [6.51(4–11) days] was shorter than the control group [7.20(5–12) days] (p = .002). Immediate removal of urinary catheter appeared to have fewer complications and shorter hospital stay than delayed removal.

Incentive-based travel demand management (IBTDM) strategies utilize rewards to redistribute travel demand across space and time. Such congestion-alleviation solutions are usually managed by small private companies with constraint budgets. Aside from spending money on incentives, running promotional campaigns to achieve the gains in market share is essential for maintaining the financial health of IBTDM programs. Therefore, the budget allocation between the two counterparts—incentive and marketing expenditure—needs to be wisely determined. Based on the bottleneck model, this paper proposes an optimal budget allocation scheme considering the impact of a budget constraint and market penetration. It was found that the constraint budget should be prioritized to attract those with lower marketing costs in general. In situations with an insufficient budget and when marketing costs were lower for attracting lower-income individuals, IBTDM decision-makers should focus on those lower-income individuals at first. This mitigates inequity issues to some extent. Therefore, policy makers or planners should pay more attention to marketing cost when developing a marketing plan and try to reduce marketing cost to make full use of incentive budget.

An increasing demand for natural food preservatives is raised by consumers. For Nordic berry species, abundance of phenolic compounds and potent activities of anti-oxidation and anti-bacteria enables a great potential as food preservatives. This review provides a systematic examination of current literature on phenolic profiles, anti-oxidative and anti-bacterial activities of various extracts of Nordic berry species, as well as the impact of various structure features of phenolics on the bioactivities. Special attention is placed on exploitation of leaves of berry species and pomaces after juice-pressing as side-streams of berry production and processing. The current progress and challenges in application of Nordic berry species as food preservatives are discussed. To fully explore the potential application of Nordic berry species in food industry and especially to valorize the side-streams of berry cultivation (leaves) and juice-pressing industry (pomaces), it is crucial to obtain extracts and fractions with targeted phenolic composition, which have high food preserving efficacy and minimal impact on sensory qualities of food products.

Liang Gu,1,2 Yangchen Liu,2 Hongxue Ye,2 Fei Gao,2 Xiaoxiang Yin,2 Ying Zhao,2 Ye Tian1 1Department of Radiation Oncology, The Second Affiliated Hospital of Soochow University, Su Zhou, 215004, Jiang Su Province, People’s Republic of China; 2Department of Radiation Oncology, Taixing People’s Hospital, Tai Xing, 225400, Jiang Su Province, People’s Republic of ChinaCorrespondence: Ye TianDepartment of Radiation Oncology, The Second Affiliated Hospital of Soochow University, 1005 Sanxiang Road, Su Zhou, 215004, Jiang Su Province, People’s Republic of ChinaEmail dryetian@126.comBackground: There are no standard therapeutic strategies for local lymph node (LN) recurrence after radical resection of oesophageal squamous cell carcinoma (ESCC), and prognostic risk factors remain controversial. We assessed clinical outcomes and prognostic factors of chemoradiotherapy (CRT) or radiotherapy (RT) for LN recurrence of ESCC after curative resection.Methods: A total of 117 ESCC patients with LN recurrence after radical resection receiving salvage treatment at our hospital were retrospectively reviewed from 2014 to 2017. Overall survival (OS) was estimated using the Kaplan–Meier method; clinical characteristics were assessed using the Log rank test in the univariate analysis. Multivariate prognostic analysis was performed using the Cox proportional hazard model.Results: With a median follow-up of 19 months, the 1-, 2- and 3-year OS rates were 75.2%, 40.2% and 27.4%, respectively. The median survival time (MST) was 19.0 months. On univariate analysis for OS, pathological TNM stage, number of LN metastasis, LN maximum (Max) diameter, salvage treatment mode and tumor response were significantly associated with OS (P = 0.0074, P = 0.015, P = 0.0011, P = 0.028, P < 0.000, respectively). On multivariate analysis, tumor response [Response vs No-response hazard ratio (HR), 2.43; 95% confidence interval (CI), 1.53– 3.90, P < 0.000] and LN Max diameter (≤ 28 mm vs > 28 mm HR, 2.07; 95% CI, 1.33– 3.32, P = 0.012) were independent prognostic factors.Conclusion: Salvage CRT or RT was safe and effective for treating LN recurrence after radical resection in ESCC. Patients with the small LN Max diameter (≤ 28 mm) and obtained response after salvage therapy appeared to achieve long-term OS.Keywords: oesophageal cancer, lymph node recurrence, chemoradiotherapy

Semi-Supervised Learning (SSL) has attracted much attention in the field of machine learning and data mining. As an extension of Support Vector Machine (SVM), the Semi-Supervised Support Vector Mac...

Background and Purpose: Whether imaging parameters would independently predict stroke recurrence in low-risk minor ischemic stroke (MIS) or transient ischemic attack (TIA) according to traditional score system (such as ABCD 2 score, which was termed on the basis of the initials of the five factors: age, blood pressure, clinical features, duration, diabetes) remains unclear. We sought to evaluate the association between imaging parameters and 1-year stroke recurrence in patients with TIA or MIS in different risk stratum stratified by ABCD 2 score. Methods: We included patients with TIA and MIS (National Institutes of Health Stroke Scale score ≤3) with complete baseline vessel and brain imaging data from the Third China National Stroke Registry III. Patients were categorized into different risk groups based on ABCD 2 score (low risk, 0–3; moderate risk, 4–5; and high risk, 6–7). The primary outcome was stroke recurrence within 1 year. Multivariable Cox proportional-hazards regression models were used to assess whether imaging parameters (large artery stenosis, infarction number) were independently associated with stroke recurrence. Results: Of the 7140 patients included, 584 patients experienced stroke recurrence within 1 year. According to the ABCD 2 score, large artery stenosis was associated with higher stroke recurrence in both low-risk (adjusted hazard ratio, 1.746 [95% CI, 1.200–2.540]) and moderate-risk group (adjusted hazard ratio, 1.326 [95% CI, 1.042–1.687]) but not in the high-risk group ( P >0.05). Patients with multiple acute infarctions or single acute infarction had a higher risk of recurrent stroke than those with no infarction in both low- and moderate-risk groups, but not in the high-risk group. Conclusions: Large artery stenosis and infarction number were independent predictors of 1-year stroke recurrence in low-moderate risk but not in high-risk patients with TIA or MIS stratified by ABCD 2 score. This finding emphasizes the importance of early brain and vascular imaging evaluation for risk stratification in patients with TIA or MIS.

Background The study of plant phenotype by deep learning has received increased interest in recent years, which impressive progress has been made in the fields of plant breeding. Deep learning extremely relies on a large amount of training data to extract and recognize target features in the field of plant phenotype classification and recognition tasks. However, for some flower cultivars identification tasks with a huge number of cultivars, it is difficult for traditional deep learning methods to achieve better recognition results with limited sample data. Thus, a method based on metric learning for flower cultivars identification is proposed to solve this problem. Results We added center loss to the classification network to make inter-class samples disperse and intra-class samples compact, the script of ResNet18, ResNet50, and DenseNet121 were used for feature extraction. To evaluate the effectiveness of the proposed method, a public dataset Oxford 102 Flowers dataset and two novel datasets constructed by us are chosen. For the method of joint supervision of center loss and L2-softmax loss, the test accuracy rate is 91.88%, 97.34%, and 99.82% across three datasets, respectively. Feature distribution observed by T-distributed stochastic neighbor embedding (T-SNE) verifies the effectiveness of the method presented above. Conclusions An efficient metric learning method has been described for flower cultivars identification task, which not only provides high recognition rates but also makes the feature extracted from the recognition network interpretable. This study demonstrated that the proposed method provides new ideas for the application of a small amount of data in the field of identification, and has important reference significance for the flower cultivars identification research.

Pituitary adenylate cyclase-activating polypeptide (PACAP) has beneficial effects in learning and memory. However, the mechanism by which PACAP improves cognitive impairment of vascular dementia (VaD) is not clear. We established a VaD model by bilateral common carotid stenosis (BCAS) to investigate the molecular mechanism of cognitive impairment. Protein levels of PACAP, Sirtuin 3 (Sirt3), brain-derived neurotrophic factor (BDNF), and postsynaptic density 95 (PSD-95) were assessed by Western blot. In vitro, oxygen glucose deprivation (OGD) was used to simulate the ischemia/hypoxia state. HT22 cells were transfected with Sirt3 knockdown and overexpression to study the relationship between PACAP, Sirt3, and BDNF. In vivo, PACAP was administered intranasally to assess its protective effects on BCAS. The study showed that the levels of PACAP, Sirt3, BDNF, and PSD-95 were decreased in the BCAS model of VaD. PACAP increased the protein levels of Sirt3, BDNF, PSD-95, Bcl-2, and Bax under OGD condition in vitro. Sirt3 regulated BDNF and synaptic plasticity. Intranasal PACAP increased the protein levels of PAC1, Sirt3, BDNF, and PSD-95 in vivo. This study provides evidence that PACAP regulates synaptic plasticity and plays an antiapoptotic role through Sirt3.

At present, the study of upper-limb posture recognition is still in the primary stage; due to the diversity of the objective environment and the complexity of the human body posture, the upper-limb posture has no public dataset. In this paper, an upper extremity data acquisition system is designed, with a three-channel data acquisition mode, collect acceleration signal, and gyroscope signal as sample data. The datasets were preprocessed with deweighting, interpolation, and feature extraction. With the goal of recognizing human posture, experiments with KNN, logistic regression, and random gradient descent algorithms were conducted. In order to verify the superiority of each algorithm, the data window was adjusted to compare the recognition speed, computation time, and accuracy of each classifier. For the problem of improving the accuracy of human posture recognition, a neural network model based on full connectivity is developed. In addition, this paper proposes a finite state machine- (FSM-) based FES control model for controlling the upper limb to perform a range of functional tasks. In the process of constructing the network model, the effects of different hidden layers, activation functions, and optimizers on the recognition rate were experimental for the comparative analysis; the softplus activation function with better recognition performance and the adagrad optimizer are selected. Finally, by comparing the comprehensive recognition accuracy and time efficiency with other classification models, the fully connected neural network is verified in the human posture superiority in identification.

Background Satellite cells (SCs) are critical to skeletal muscle regeneration. Inactivation of SCs is linked to skeletal muscle loss. Transferrin receptor 1 (Tfr1) is associated with muscular dysfunction as muscle‐specific deletion of Tfr1 results in growth retardation, metabolic disorder, and lethality, shedding light on the importance of Tfr1 in muscle physiology. However, its physiological function regarding skeletal muscle ageing and regeneration remains unexplored. Methods RNA sequencing is applied to skeletal muscles of different ages to identify Tfr1 associated to skeletal muscle ageing. Mice with conditional SC ablation of Tfr1 were generated. Between Tfr1 SC/WT and Tfr1 SC/KO (n = 6–8 mice per group), cardiotoxin was intramuscularly injected, and transverse abdominal muscle was dissected, weighted, and cryosectioned, followed by immunostaining, haematoxylin and eosin staining, and Masson staining. These phenotypical analyses were followed with functional analysis such as flow cytometry, tread mill, Prussian blue staining, and transmission electron microscopy to identify pathological pathways that contribute to regeneration defects. Results By comparing gene expression between young (2 weeks old, n = 3) and aged (80 weeks old, n = 3) mice among four types of muscles, we identified that Tfr1 expression is declined in muscles of aged mice (~80% reduction, P

Incentive-Based Traffic Demand Management (IBTDM) provides monetary incentives to encourage commuters to alter their departures spatially or temporary with the goal of alleviating congestion. With the proliferation of smartphone technology, mobility apps have become ideal platforms for carrying out IBTDM. Tremendous amounts of empirical app usage data have been collected, but research into the behavioral insights of IBTDM remains limited. It is unclear who IBTDM's target users should be, and which users are the most likely to be stable (actively use the app) and behaviorally sustainable (willing to contribute to congestion alleviation). This study aims to profile the socio-demographics of such favored users based on behavioral and socio-demographic data collected by the Metropia app. The Ensemble Empirical Mode Decomposition (EEMD) method was used for usage trend detection. The detected usage trends were then used in pattern classification to identify stable and sustainable users. Next, binary logistic regression was adopted to explore the socio-demographic characteristics of each category of users. It was found that factors including home work days, household annual income, household size and schedule flexibility played important roles in users' usage patterns and departure time decisions. Specifically, home work days and household annual income co-influenced app usage patterns. Household size and schedule flexibility were the main determinants of departure time behavior. The findings of this research can be used to guide administrators of budget-constrained IBTDM programs who need to wisely allocate their marketing budget to increase penetration among favored users as to maximize the utility of the program.

Background The identification of NTRK fusions in tumours has become critically important due to the actionable events predictive of response to TRK inhibitor. It is not clear whether the NTRK breakpoint location is different for response to targeted therapy and NTRK fusions affects the efficacy of immunotherapy. Case presentation Here we reported a 60-year-old female diagnosed with advanced lung adenocarcinoma. NGS-based molecular profiling identified a novel NCOR2-NTRK1 fusion and high tumor mutational burden (TMB) (58.58 mutations/Mb) in this case. Additionally, program death-ligand 1 (PD-L1) expression was detected in 20–30% of the tumor cells by immunohistochemical (IHC) staining. The patient received treatment with anti-PD-1 immune checkpoint inhibitor of camrelizumab. After two cycles of treatment, the CT scan showed some tumor nodules were still enlarged, indicating disease progression. She was then changed to TRK inhibitor larotrectinib. One month later, the CT scan showed the volume of some lesions started to decrease, and no metastasis lesions were found. The patient then continued the administration of larotrectinib, and some lesion sizes were significantly reduced or even disappeared in the next few months. Currently, this patient is still alive. Conclusions Altogether, this report provided a new driver of lung adenocarcinoma expanded the mutational spectrum of NTRK1 fusion variants and suggested using larotrectinib as the targeted therapy is more effective than anti-PD-1 inhibitor in lung adenocarcinoma harboring with NTRK fusion, positive PD-L1 expression, and high TMB simultaneously.

Background: Neuron-specific enolase (NSE) is one of the biomarkers of neuroendocrine neoplasms (NEN). Its level of evidence is significantly lower than some other biomarkers. However, the ratio of NSE serum concentration (NSE ratio) before and after the treatment cycle may be a good tool for evaluating the therapeutic effect of metastatic neuroendocrine neoplasms of the liver (MNENOL). Methods: We collected clinical cases of NEN with liver metastases, calculating the ratio of NSE in each case before and after the treatment cycle, using thin-slice computed tomography or magnetic resonance imaging as a reference to evaluate the therapeutic effect. We analyzed the correlation between NSE ratio and NSE serum concentration and curative effect, and then compared the evaluation performance of the two. Results: We found that increase in the NSE ratio is a risk factor for the progression of MNENOL. Compared with NSE, NSE ratio has a greater advantage in evaluating the effect of MNENOL. NSE ratio is related to the curative effect of NEN, and the correlation is better than that of NSE. When judging whether NEN has new metastasis, the NSE ratio shows a similar effect to NSE, and there is no significant difference between the two. Conclusion: NSE ratio is more effective than NSE in evaluating the therapeutic effect of MNENOL, but it is not significantly different from NSE in terms of predicting new metastases.

Purpose To mitigate a common artifact in spiral real-time MRI, caused by aliasing of signal outside the desired FOV. This artifact frequently occurs in midsagittal speech real-time MRI. Methods Simulations were performed to determine the likely origin of the artifact. Two methods to mitigate the artifact are proposed. The first approach, denoted as "large FOV" (LF), keeps an FOV that is large enough to include the artifact signal source during reconstruction. The second approach, denoted as "estimation-subtraction" (ES), estimates the artifact signal source before subtracting a synthetic signal representing that source in multicoil k-space raw data. Twenty-five midsagittal speech-production real-time MRI data sets were used to evaluate both of the proposed methods. Reconstructions without and with corrections were evaluated by two expert readers using a 5-level Likert scale assessing artifact severity. Reconstruction time was also compared. Results The origin of the artifact was found to be a combination of gradient nonlinearity and imperfect anti-aliasing in spiral sampling. The LF and ES methods were both able to substantially reduce the artifact, with an averaged qualitative score improvement of 1.25 and 1.35 Likert levels for LF correction and ES correction, respectively. Average reconstruction time without correction, with LF correction, and with ES correction were 160.69 ± 1.56, 526.43 ± 5.17, and 171.47 ± 1.71 ms/frame. Conclusion Both proposed methods were able to reduce the spiral aliasing artifacts, with the ES-reduction method being more effective and more time efficient.

Enterovirus 71 (EV71) infection is more likely to cause hand, foot and mouth disease (HFMD) in children, which can lead to neurogenic complications and higher mortality. As a commonly used clinical medicine, Reduning injection (RDN) helps to shorten the symptoms of patients with HFMD and facilitate the early recovery of children. However, the regulatory mechanism of RDN on the HFMD immune system disorder caused by EV71 remains to be discussed. This study collected detailed treatment data of 56 children with HFMD who entered the affiliated Children's Hospital of Nanjing Medical University during 2019. Retrospective analysis of clinical data showed that the symptoms of the RDN treatment group were improved compared with the untreated group. To explore its mechanism, the relevant detection indicators were detected by flow cytometry, enzyme-linked immunosorbent assay and real-time quantitative PCR. It was found that the number and function of innate immune (ILCs) and adaptive immunity (Th1, Th2 and secreted cytokines) were reduced, suggesting that RDN plays a role by regulating cellular immunity. The in vitro differentiation inhibition test further confirmed that RDN affected Th1 differentiation by inhibiting the expression of transcription factors on the basis of Th1 cell differentiation in vitro.

Objective: To evaluate the outcomes and explore the risk factors for survival of lung cancer patients with brain metastases (BMs) who were treated with whole brain radiotherapy (WBRT) and to identify the significance of the risk factors. Methods: A retrospective analysis was carried out for lung cancer patients with BMs who were treated with WBRT in the Second Affiliated Hospital of Soochow University from January 2014 to December 2017. Their survival time was calculated using the Kaplan-Meier method. Meanwhile, the neutrophil-lymphocyte ratio (NLR) cutoff values were defined using the receiver operating characteristic (ROC) curve analysis, and the characteristics of different NLR groups were compared using the Wilcoxon Rank Sum Test. Results: A total of 179 patients were assessed. Their median overall survival (OS) was 9.9 (95% CI 7.08–12.72) months. As shown by univariate analyses, their OS was significantly affected by histology (P ​

Background: Small, totally endophytic renal masses present a technical challenge for surgical extirpation due to poor identifiability during surgery. The method for the precise localization of totally endophytic tumours before nephron-sparing surgery could be optimized. Case presentation: An asymptomatic 70-year-old male presented with a right-sided, 16-mm, totally endophytic renal mass on computed tomography (CT). CT-guided percutaneous microcoil localization was carried out prior to laparoscopy to provide a direction for partial nephrectomy. During the 25 minutes of the localization procedure, the patient underwent five local CT scans, and his cumulative effective radiation dosage was 5.1 mSv. The span between localization and the start of the operation was 15 hours. The laparoscopic operation time was 105 minutes, and the ischaemia time was 25 minutes. The postoperative recovery was smooth, and no perioperative complications occurred. Pathology showed the mass to be renal clear cell carcinoma, WHO/ISUP grade 2, with a 2-mm, clear surgical margin. The patient remained free of recurrence on follow-up for eleven months. To our knowledge, this application of microcoil implantation prior to laparoscopic partial nephrectomy towards an intrarenal mass could be an early reported attempt for the localized method applied in renal surgery. Conclusions: The percutaneous microcoil localization of endophytic renal tumours is potentially safe and effective prior to laparoscopic partial nephrectomy.

Unraveling the morphology of the sensing material is of paramount in realizing the better sensitivity. For this purpose, the Bi2Ti2O7:Yb3+/Er3+ nanofibers (0:1, 4:1, 8:1, 15:1, 20:1) and nanoparticles were synthesized via an electrospinning and sol–gel route, respectively. Subsequently, the temperature sensing properties based on the fluorescence intensity ration were studied within Bi2Ti2O7:Yb3+/Er3+ nanofibers and particles in the range of 298–538 K. The maximum relative sensitivity value was 1.53% at 298 K for Bi2Ti2O7:Yb3+/Er3+ (4:1) nanofibers. As was expected, Bi2Ti2O7:Yb3+/Er3+ nanofibers demonstrated an enhanced temperature sensitivity than that of the individual nanoparticles, exhibiting the champion values among all the reported Yb–Er pairs. To exploit the potential for practical application, the Bi2Ti2O7:Yb3+/Er3+ nanofibers were utilized to measure the surface temperature of a heating object. An improved surface temperature resolution was realized compare with the infrared thermal camera. All the presented results confirmed that the novel upconversion Bi2Ti2O7:Yb3+/Er3+ nanofibers could be an outstanding candidate for temperature sensors. Our work has proven to be a reliable alternative for exploring contactless temperature sensing at a higher resolution.

Inflammation is actively involved in the clinical manifestation of peripheral artery disease (PAD). Sonodynamic therapy (SDT), a novel non-invasive, plaque-based, macrophage-targeted anti-inflammatory regimen for atherosclerosis has the potential to improve walking performance by reducing plaque inflammation.This phase-2, randomized, sham-controlled, double-blind clinical trial enrolled 32 participants with symptomatic femoropopliteal PAD. The primary outcome was the 30-day change in the target-to-background ratio (TBR) within the most diseased segment (MDS) of the femoropopliteal artery assessed through positron emission tomography/computed tomography (PET/CT). The secondary outcomes were changes in walking performance, limb perfusion, lesional morphology and quality of life measurements.The mean age was 64.7 years and 63% were male. Thirty-one completed follow-up. SDT significantly decreased the MDS TBR by 0.53 (95% CI, -0.70 to -0.36, P 0.001) compared with control. Furthermore, SDT increased peak walking time by 118.6 s (95% CI, 74.3 to 163.0, P 0.001), increased ankle-brachial index by 0.11 (95% CI, 0.07 to 0.14, P 0.001), decreased lesional diameter and area stenosis by 7.2% (95% CI, -8.6 to -4.5, P 0.001) and 9.6% (95% CI, -24.5 to -5.3, P = 0.005), respectively, and increased the walking speed score of the Walking Impairment Questionnaire by 16.1 (95% CI, 2.6 to 29.5, P = 0.021) and the physical functioning score of the 36-item Short-Form Health Survey by 10.0 (95% CI, 5.0 to 20.0, P = 0.003) compared with control. These improvements were maintained in the SDT group up to 6-month.SDT rapidly reduced plaque inflammation and improved walking performance among patients with symptomatic PAD.Clinical Trials NCT03457662.

With the advancement of national policies and the rise of Internet of things (IoT) technology, smart meters, smart home appliances, and other energy monitoring systems continue to appear, but due to the fixed application scenarios, it is difficult to apply to different equipment monitoring. At the same time, the limited computing resources of sensing devices make it difficult to guarantee the security in the transmission process. In order to help users better understand the energy consumption of different devices in different scenarios, we designed a nonintrusive load management based on distributed edge and secure key agreement, which uses narrowband Internet of things (NB-IoT) for transmission and uses edge devices to forward node data to provide real-time power monitoring for users. At the same time, we measured the changes of server power under different behaviors to prepare for further analysis of the relationship between server operating state and energy consumption.

Purpose To perform a placebo-controlled trial to evaluate the efficacy and safety of Serenoa repens extract (SRE) for the treatment of chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Methods We conducted a double-blind, randomized, placebo-controlled, multicenter, clinical phase 4 study of 221 patients with CP/CPPS across 11 centers. Participants were randomly assigned in a 2:1 ratio to receive SRE or placebo for 12 weeks. The primary efficacy endpoint was the change in total score on the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI). Secondary efficacy endpoints included improvements within each domain of NIH-CPSI, clinical response rate, and International Index of Erectile Function 5 items (IIEF-5). Results In total, 226 patients were enrolled and randomized between January 2017 and June 2018. Of these 221 patients were included in the intent-to-treat analysis: 148 in the SRE group and 73 patients in the placebo group. Compared to the placebo, SRE led to statistically significant improvements in the NIH-CPSI total score and sub-scores. The significant improvements of NIH-CPSI scores were established after 2 weeks from the first dose, and continued to the end of the treatment. Furthermore, a significantly higher rate of patients achieved a clinical response in the SRE group compared with that in the placebo group (73.0% vs 32.9%, P Conclusions SRE was effective, safe, and clinically superior to placebo for the treatment of CP/CPPS. ChiCTR-IPR-16010196, December 21, 2016 retrospectively registered

PurposeThe purpose of this paper evaluates the effects of the Great Western Development (GWD) policy on agricultural intensification, land use, agricultural production and rural poverty in western China.Design/methodology/approachThe authors collect county-level data on land use, input application, grain crop production, income, poverty and geophysical characteristics for 1996–2005 and use a quasi-natural experimental design of difference-in-differences (DD) in the empirical analysis.FindingsResults suggest that the GWD policy significantly increased the grain crop production in western China. This increase resulted from higher yield, with increased fertilizer use and agricultural electricity consumption per hectare, and more land allocated to grow grain crops. The policy also increased land-use concentration, reduced crop diversity and alleviated rural poverty in western China.Originality/valueThis paper makes three contributions. First, the authors add to the growing literature on the GWD policy by evaluating its effects on farm household decisions and exploring the mechanisms and broad socioeconomic impacts in western China. Second, the authors take advantage of a quasi-natural experimental design to improve the identification strategy where input use, land allocation, production and off-farm labor participation are all endogenous in a farm household. Third, the authors explore a long list of variables within one integrated dataset to present a comprehensive picture of the impact of the GWD policy.

Photothermal therapy (PTT) achieves substantive therapeutic progress in certain tumor types without exogenous agents but is hampered by the over-activated inflammatory response or tumor recurrence in some cases. Herein, we technically developed the metal-polyphenolic nanosystem with precise NIR-II fluorescence-imaging guidance for combining hafnium (Hf)-sensitized radiotherapy with PTT to regress tumor growth.