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Purpose Magnetoacoustic tomography with magnetic induction (MAT-MI) is a technique that utilizes the acoustic signals induced by magnetic stimulation to reconstruct the electrical impedance distribution in biological tissues. Most algorithms ignored the fact that acoustic properties in human tissues are heterogeneous, which lead to distortion and blurring of small reconstructed objects. In this study, a novel algorithm is proposed for exact reconstruction of the sound source distribution in acoustic heterogeneous tissues. Methods Based on the ring transducer array, we develop an algorithm which combines algebraic reconstruction technique (ART) and time reversal method. Different to existing reconstruction methods, the ultrasonic transmission tomography (UTT) and the MAT-MI can be completed in same system, which decreases the system complexity. The sound velocity distribution is reconstructed with the ART so that the propagation time of the magnetoacoustic signals in the heterogeneous tissue is corrected. And then, the sound source image is reconstructed based on the time reversal method from new sound pressure data. Both numerical simulations and phantom experiments are established to validate the proposed method. Results Compared with the results without consideration of the variation on acoustic speed, sound sources reconstructed by our method are more consistent with the model in terms of size and shape. Conclusions The novel algorithm can be used to reconstruct the high-accuracy image of MAT-MI sound source in the sound velocity inhomogeneous media. In addition, this method is applicable to scenarios that the prior knowledge of the imaging targets is unknown. The signal acquisition time of MAT-MI in acoustically heterogeneity media is greatly reduced due to the introduction of ring transducer array into the imaging system. Therefore, our method will promote the application of MAT-MI in noninvasive early diagnosis of tumor for preclinical study.

Rationale: Insufficient penetration and accumulation of theranostic payloads in solid tumors greatly challenge the clinical translation of cancer nanomedicines. To address this challenge, we synthesized natural melanin-cored and doxorubicin-loaded perfluoropentane nanodroplets with good biocompatibility and self-assembling ability. Methods: We used an opto-acoustic synergistic irradiation (OASI) method that was effective at lower energy levels than ultrasound- or laser-only irradiation to safely vaporize the nanodroplets and to cavitate the generated microbubbles for mechanically enhancing intratumoral delivery. The delivered melanin and doxorubicin inside the tumors mediated secondary chemo-photothermal therapy under laser irradiation to fully kill cancer cells. Results: In vivo animal experiments demonstrated direct mechanical disruption of tumor structures (H&E staining), enhanced intratumoral penetration of melanin (photoacoustic imaging), and efficient intratumoral accumulation of doxorubicin (fluorescent imaging). Anti-tumor experiments demonstrated that the nanodroplets combined with OASI treatment and subsequent laser irradiation could efficiently eliminate melanoma tumors. Conclusion: Melanin-cored and doxorubicin-loaded perfluoropentane nanodroplets hold great promise for translational sono-chemo-photothermal cancer therapy.

As the conductivities of healthy tissue and cancerous tissue are different, methods for detecting conductivity variations of biological tissue are potential medical imaging modalities for early diagnosis of cancer in the future. Magneto-acousto-electrical tomography (MAET) is a noninvasive and hybrid conductivity imaging technology that integrates the advantage of high contrast. It has been demonstrated to have an excellent capability to distinguish conductivity variations along the direction of acoustic propagation and extremely promising as an alternative medical imaging technology for early detection of cancer. However, the existing MAET has a low resolution, and the factors affecting the imaging resolution of MAET are rarely studied systematically. Therefore, we firstly designed an MAET detection system and performed several verification experiments. A B-scan algorithm was then proposed for enhancing the system resolution. Subsequently, two uniform phantoms with different intermediate gaps in the middle and a B-mode imaging experiment on pork tissue were used for testing the performance of detection resolution. Finally, comparative analyses were performed to verify whether the frequency, the cycle number of the excitation signal, and the B-scan algorithm can influence the detection resolution. We obtained the following results: 1) The longitudinal resolution of the conductivity B-scan image increases as the number of cycle excitation decreases. 2) Vertical resolution using a 2.5 MHz probe excitation is significantly better than using a 500 kHz probe excitation. 3) The B-scan algorithm can improve conductivity resolution, and it reveals that our proposed detection system’s longitudinal resolution can reach 1mm. 4) we obtained the conductivity profile of pork tissue. The results showed that our detection platform could accurately distinguish the target sample’s interfaces of conductivity variations, increasing the excitation frequency, reducing the cycle number, and adopting the B-mode imaging algorithm could improve its conductivity detection resolution, which laid the foundation for the design of a high-resolution MAET detection system.

Alzheimer's disease (AD) is a neurodegenerative and non-curable disease, with serious cognitive impairment, such as dementia. Clinically, it is critical to study the disease with multi-source data in order to capture a global picture of it. In this respect, an adaptive ensemble manifold learning (AEML) algorithm is proposed to retrieve multi-source neuroimaging data. Specifically, an objective function based on manifold learning is formulated to impose geometrical constraints by similarity learning. The complementary characteristics of various sources of brain disease data for disorder discovery are investigated by tuning weights from ensemble learning. In addition, a generalized norm is explicitly explored for adaptive sparseness degree control. The proposed AEML algorithm is evaluated by the public AD neuroimaging initiative database. Results obtained from the extensive experiments demonstrate that our algorithm outperforms the traditional methods.

Purpose The occurrence of presbyopia and cataract is closely related to changes in the mechanical properties of the crystalline lens. There are no established methods so far for in vivo assessment. By introducing ultrasound elastography, we proposed group velocity (Vg) of an induced shear wave as a new biomarker to characterize the mechanical properties of the lens in our previous study. Here, we investigated the effect of the ultrasound frequency on measurement accuracy and validated the results with a conventional ex vivo compression testing. We also demonstrated a change trend in Vg and its correlation with age in a rabbit model. Methods Eight New Zealand white rabbits were fed normally from the fourth to seventh month. An ultrasound elastography system was developed to measure Vg in vivo on every eye once per month. The performances when using a high-frequency (L22-11v) and low-frequency (L11-4v) probe were compared. Rabbits were sacrificed after in vivo measurements by the end of the seventh month and this was followed by ex vivo ultrasound measurements and conventional compression tests on the extracted lenses. Results The results demonstrated that there were no significance differences in Vg between measurements with high-frequency (USE-HF) and low-frequency (USE-LF) probes in the same month-age group. The mean Vg and the standard deviation of four rabbits that were 7 months old were 2.37 ± 0.24 m/s, 2.36 ± 0.25 m/s, 2.43 ± 0.26 m/s and 2.44 ± 0.38 m/s, with USE-HF for ex vivo and in vivo measurements and USE-LF for ex vivo and in vivo measurements, respectively. There were no significant differences (p > 0.05) and they were all in agreement with the results of compression tests, which was 16.16 ± 1.84 kPa in Young's modulus. The results also showed that Vg increased with age. In combination with the results of our previous study, Vg showed a relatively sharp increase from 2 to 5 months, while it had a slight increase from 5 to 7 months. Conclusions The USE-HF and USE-LF has comparable accuracy in Vg measurements while USE-HF had an advantage regarding better spatial resolution. The change trend of Vg was in accord with the growth phase of New Zealand white rabbits, which usually results in sexual maturity at 5 months old. This implies that Vg can be used as a biomarker parameter for evaluating the mechanical properties of the lens undergoing physiological changes.

Objective The interaction between tumor microenvironment and tumor cells plays a key role in tumor progression. However, the mechanisms by which this interaction promotes the transdifferentiation of normal fibroblasts (NFs) to cancer-associated fibroblasts (CAFs) are still unclear. The aim of this study was to investigate whether ovarian cancer (OvCa) cells-derived microRNAs were involved in the transition of resident fibroblasts to CAFs, and in promoting tumorigenesis. Methods CAFs and NFs were isolated from the same ovarian site in OvCa and noncancerous prophylactic oophorectomy specimens. The effect of exosomes on the motility of CAFs or NFs was analyzed by wound healing and Transwell assays. The expression of CAFs marker α-smooth muscle actin (α-SMA) and fibroblast activated protein (FAP) were determined by quantitative real-time PCR and Western blotting. A luciferase reporter assay was used to test the interaction between miR-124 and sphingosine kinase 1 (SPHK1). Results NFs with downregulated miR-124 displayed the characteristics of CAFs, including overexpression of α-SMA and FAP and increased migratory and invasive ability. Overexpression of miR-124 in CAFs reversed some traits of NFs. Human ovarian surface epithelial cells-secreted miR-124 could be transferred via exosomes to CAFs and resulted in decreased α-SMA and FAP expression and attenuated cell motility. Moreover, our finding showed that the expression of SPHK1, a potential target of miR-124, was significantly elevated in CAFs. Conclusions The present study provides important and novel perspective into OvCa CAF differentiation and extracellular matrix remodeling, which trigger the tumor progression.

Background As a functional imaging technology, magneto acoustic tomography (MAT) has broad application prospect in early tumor diagnosis and image monitoring during treatment. Method The influence on the acoustic field characteristics of the gradual change in conductivity was studied in magneto-acoustic tomography with current injection (MAT-CI) in this article. Result Theoretical analysis showed that the value of electro-acoustic conversion ratio (E-ACR) was different in different source frequencies under the same conductivity gradual-varying boundary. Conclusion The frequency characteristics of the acoustic pressure tend to shift towards the low frequency region. This conclusion provides a theoretical foundation for the MA signal detection and processing system optimization in the area of conductivity gradual-varying.

Non-obstructive azoospermia (NOA) is one of the most important causes of male infertility. It is mainly characterized by the absence of sperm in semen repeatedly or the number of sperm is small and not fully developed. At present, its pathogenesis remains largely unknown. The goal of this study is to identify hub genes that might affect biomarkers related to spermatogenesis. Using the clinically significant transcriptome and single-cell sequencing data sets on the Gene Expression Omnibus (GEO) database, we identified candidate hub genes related to spermatogenesis. Based on them, we performed Gene Ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses, protein-protein interaction (PPI) network analysis, principal component analysis (PCA), cell cluster analysis, and pseudo-chronological analysis. We identified a total of 430 differentially expressed genes, of which three have not been reported related to spermatogenesis (C22orf23, TSACC, and TTC25), and the expression of these three hub genes was different in each type of sperm cells. The results of the pseudo-chronological analysis of the three hub genes indicated that TTC25 was in a low expression state during the whole process of sperm development, while the expression of C22orf23 had two fluctuations in the differentiating spermatogonia and late primary spermatocyte stages, and TSACC showed an upward trend from the spermatogonial stem cell stage to the spermatogenesis stage. Our research found that the three hub genes were different in the trajectory of sperm development, indicating that they might play important roles in different sperm cells. This result is of great significance for revealing the pathogenic mechanism of NOA and further research.

Summary Obesity is characterized by the excessive accumulation of the white adipose tissue (WAT), but healthy expansion of WAT via adipocyte hyperplasia can offset the negative metabolic effects of obesity. Thus, identification of novel adipogenesis regulators that promote hyperplasia may lead to effective therapies for obesity-induced metabolic disorders. Using transcriptomic approaches, we identified transmembrane BAX inhibitor motif-containing 1 (TMBIM1) as an inhibitor of adipogenesis. Gain or loss of function of TMBIM1 in preadipocytes inhibited or promoted adipogenesis, respectively. In vivo, in response to caloric excess, adipocyte precursor (AP)-specific Tmbim1 knockout (KO) mice displayed WAT hyperplasia and improved systemic metabolic health, while overexpression of Tmbim1 in transgenic mice showed the opposite effects. Moreover, mature adipocyte-specific Tmbim1 KO did not affect WAT cellularity or nutrient homeostasis. Mechanistically, TMBIM1 binds to and promotes the autoubiquitination and degradation of NEDD4, which is an E3 ligase that stabilizes PPARγ. Our data show that TMBIM1 is a potent repressor of adipogenesis and a potential therapeutic target for obesity-related metabolic disease.

Background Nonalcoholic fatty liver disease (NAFLD) is rapidly becoming one of the most common liver diseases. Ultrasound elastography has been used for the diagnosis of NAFLD. However, clinical research on steatosis by elastography technology has mainly focused on steatosis with fibrosis or non-alcoholic steatohepatitis (NASH), while steatosis without fibrosis has been poorly studied. Moreover, the relationship between liver viscoelasticity and steatosis grade is not clear. In this study, we evaluated the degree of liver steatosis in a simple steatosis rat model using shear wave elastography (SWE). Results The viscoelasticity values of 69 rats with hepatic steatosis were measured quantitatively by SWE in vivo and validated by a dynamic mechanical analysis (DMA) test. Pathological sections were used to determine the steatosis grade for each rat. The results showed that the elasticity values µ obtained by the two methods followed the same trend, and µ is significantly correlated with liver steatosis. The Pearson’s correlation coefficients indicate that $$\mu$$ μ obtained by SWE is positively linear correlated with DMA (r = 0.628, p = 7.85 × 10–9). However, the viscosity values $$\eta$$ η obtained by SWE were relatively independent of those obtained by DMA with a correlation coefficient of − 0.01. The combined Voigt elasticity measurements have high validity in the prediction of steatosis (S0 vs. S1–S4), with an AUROC of 0.755 (95% CI 0.6175–0.8925, p Conclusion SWE might have the feasibility to be introduced as an auxiliary technique for NAFLD patients in clinical settings. However, the viscosity results measured by SWE and DMA are significantly different, because the two methods work in different frequency bands.

Magneto-acousto-electrical tomography (MAET) is designed to produce conductivity images with high spatial resolution for a conducting object. In a previous study, for an irregular conductor, transverse scanning and rotational methods with a focus transducer were combined to collect complete electrical information. This kind of method, however, is time-consuming because of the transverse scanning procedure. In this study, we proposed a novel imaging method based on plane ultrasound waves and a new aspect of projection in rotational MAET. In the proposed method, we achieved the projection in each rotation angle by using plane waves rather than mechanical scanning of the focus waves along the transverse direction. Thus, the imaging time was significantly saved. To verify the proposed method, we derived a measurement formula containing a lateral integration, which built the relationship between the measurement formula and the projection under each rotation angle. Next, we constructed two different numerical models to compute magneto-acousto-electrical signals by using a finite element method and reconstructed the corresponding conductivity parameter images based on a filtered back-projection algorithm. Then, simulated signals under different signal-to-ratios (6, 20, 40, and 60 dB) were generated to test the performance of the proposed algorithm. To improve the image quality, we further analysed the influence of the filters and the frequency scaling factors embedded in the filtered back-projection algorithm. Moreover, we computed the L2 norm of the error in case of different frequency scaling factors and measurement noises. Finally, we conducted a phantom experiment with a 64-element linear phased array transducer (center frequency of 2.7 MHz) and reconstructed the conductivity parameter images of the circular phantom with an elliptical hole. The experimental results demonstrated the feasibility and time-efficiency of the proposed rapid rotational MAET.

In clinical monitoring, thermodilution is seen to be the gold standard in assessment of patient's cardiac output, with using pulmonary artery catheter. However, this method requires injecting a certain amount of cold water into the patient's body, which may disrupt their internal environment balance and cause serious consequences, such as cardiopulmonary failure. In order to eliminate this drawback, we have proposed a novel dual-mode intravascular ultrasound catheter to replace the traditional thermodilution method. In this study, a catheter consists of an electromagnetic motor and two transducers in different orientations is developed. The center frequency of two transducers are 15 MHz and 30 MHz, respectively. The outer diameter of the whole catheter is 2 mm, and the motor has a maximal speed of 275 PRS.

Background Colorectal cancer is the third leading cause of cancer-related deaths worldwide. Sonodynamic therapy (SDT) is an emerging cancer therapy, and in contrast to photodynamic therapy, could non-invasively reach deep-seated tissues and locally activates a sonosensitizer preferentially accumulated in the tumor area to produce cytotoxicity effects. In comparison with traditional treatments, SDT may serve as an alternative strategy for human colon cancer treatment. Here, we investigated the sonodynamic effect using sinoporphyrin sodium (DVDMS) as a novel sonosensitizer on human colon cancer cells in vitro. Results The absorption spectra of DVDMS revealed maximum absorption at 363 nm wavelength and emission peak at 635 nm. Confocal microscopy images revealed the DVDMS was primarily localized in the cytoplasm, while no evident signal was detected within the nuclei. Flow cytometry analysis showed rapid intracellular uptake of DVDMS by two types of human colon cancer cells (HCT116 and RKO). Cell viability of HCT116 was tolerant with the concentration of DVDMS up to 20 µg/mL, while the case of RKO was 5 µg/mL. In comparison with the control group, the SDT-treated groups of these two types of human colon cancer cells showed significant increase in cellular apoptosis and necrosis ratio. Increased intracellular reactive oxygen species (ROS) production was detected, indicating the involvement of ROS in mediating SDT effects. Conclusion DVDMS results an effective sonosensitizer for the ultrasound-mediated cancer cell killing, and its anticancer effect seems to rely on its ability to produce ROS under ultrasound exposure.

Autophagy is a primary protective process that involves removing damaged organelles or dysfunctional proteins in eukaryotes. The autophagy pathway not only maintains cellular homeostasis, but also modulates the host’s cellular response to pathogen infection. Several studies have proved that autophagy plays a dominant role in plant fitness and immunity. As intracellular parasites, virus replication and spread entirely rely on the molecular machinery of the host cell, including the autophagy process. Plant viruses severely affect crop yields and quality. During infection, complex interactions exist between viral proteins and host factors in relation to plant defense and virus counter-defense. An increasing number of studies have demonstrated that plants use autophagy to eliminate and inhibit viruses; meanwhile, some viruses have been shown to manipulate the process of autophagy to promote their own replication and survival in plant cells. In this review, we summarize recent advances in plant autophagy, with an emphasis on the role of autophagy in plant virus infection.

Background: Salmonella is one of the main causes of diarrhea which causes substantial disease burden. To determine the prevalence, serotype distribution, and antimicrobial resistance profiles of clinical Salmonella isolates in Shenzhen, a 6-year surveillance study was conducted. Methods: Three sentinel hospitals were chosen and patients who visited the gastroenteritis clinics with acute diarrhea were enrolled. Salmonella isolates from the stool samples were subjected to serotyping, antimicrobial susceptibility testing to 24 antibiotics, and detection of resistance genes. Results: A total of 297 (5.7%) Salmonella isolates were recovered from stool samples from 5,239 patients. Among the 42 serovars identified, serovar Typhimurium was the most common serotype which represented 39.7% of the isolates (118), followed by serovar Enteritidis (71, 23.9%), London (12, 4.0%), 4, 5, 12: i: - (11, 3.7%), and Senftenberg (8, 2.7%). A high frequency of resistance was found in ampicillin (70.6%), piperacillin (64.5%), tetracycline (63.5%), and streptomycin (54.3%). Resistance to ampicillin and tetracycline was observed in 95.3% of S. Typhimurium isolates; and nalidixic acid in 93.1% of S. Enteritidis isolates. Resistance to 5 or more antimicrobial agents was identified in 78.8% of S. Typhimurium and 69.0% of S. Enteritidis isolates. Conclusions: Salmonella is an important cause of acute gastroenteritis and a broad range of serotypes are prevalent in Shenzhen, with Enteritidis and Typhimurium being the most common serovars. The high level of antibiotic resistance is a serious public health concern and ongoing monitoring coupled with rational use of antibiotics are recommended.Background: Salmonella is one of the main causes of diarrhea which causes substantial disease burden. To determine the prevalence, serotype distribution, and antimicrobial resistance profiles of clinical Salmonella isolates in Shenzhen, a 6-year surveillance study was conducted. Methods: Three sentinel hospitals were chosen and patients who visited the gastroenteritis clinics with acute diarrhea were enrolled. Salmonella isolates from the stool samples were subjected to serotyping, antimicrobial susceptibility testing to 24 antibiotics, and detection of resistance genes. Results: A total of 297 (5.7%) Salmonella isolates were recovered from stool samples from 5,239 patients. Among the 42 serovars identified, serovar Typhimurium was the most common serotype which represented 39.7% of the isolates (118), followed by serovar Enteritidis (71, 23.9%), London (12, 4.0%), 4, 5, 12: i: - (11, 3.7%), and Senftenberg (8, 2.7%). A high frequency of resistance was found in ampicillin (70.6%), piperacillin (64.5%), tetracycline (63.5%), and streptomycin (54.3%). Resistance to ampicillin and tetracycline was observed in 95.3% of S. Typhimurium isolates; and nalidixic acid in 93.1% of S. Enteritidis isolates. Resistance to 5 or more antimicrobial agents was identified in 78.8% of S. Typhimurium and 69.0% of S. Enteritidis isolates. Conclusions: Salmonella is an important cause of acute gastroenteritis and a broad range of serotypes are prevalent in Shenzhen, with Enteritidis and Typhimurium being the most common serovars. The high level of antibiotic resistance is a serious public health concern and ongoing monitoring coupled with rational use of antibiotics are recommended.

Alzheimer's disease (AD) is a progressive neurodegenerative disease manifested by cognitive impairment. As a unique approach to open the blood-brain barrier (BBB) noninvasively and temporarily, a growing number of studies showed that low-intensity focused ultrasound in combination with microbubbles (FUS/MB), in the absence of therapeutic agents, is capable of ameliorating amyloid or tau pathology, concurrent with improving memory deficits of AD animal models. However, the effects of FUS/MB on both the two pathologies simultaneously, as well as the memory behaviors, have not been reported so far. Methods: In this study, female triple transgenic AD (3×Tg-AD) mice at eight months of age with both amyloid-β (Aβ) deposits and tau phosphorylation were treated by repeated FUS/MB in the unilateral hippocampus twice per week for six weeks. The memory behaviors were investigated by the Y maze, the Morris water maze and the step-down passive avoidance test following repeated FUS/MB treatments. Afterwards, the involvement of Aβ and tau pathology were assessed by immunohistochemical analysis. Neuronal health and phagocytosis of Aβ deposits by microglia in the hippocampus were examined by confocal microscopy. Further, hippocampal proteomic alterations were analyzed by employing two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) combined with mass spectrometry. Results: The three independent memory tasks were indicative of evident learning and memory impairments in eight-month-old 3×Tg-AD mice, which developed intraneuronal Aβ, extracellular diffuse Aβ deposits and phosphorylated tau in the hippocampus and amygdala. Following repeated FUS/MB treatments, significant improvement in learning and memory ability of the 3×Tg-AD mice was achieved. Amelioration in both Aβ deposits and phosphorylated tau in the sonicated hemisphere was induced in FUS/MB-treated 3×Tg-AD mice. Albeit without increase in neuron density, enhancement in axonal neurofilaments emerged from the FUS/MB treatment. Confocal microscopy revealed activated microglia engulfing Aβ deposits in the FUS/MB-treated hippocampus. Further, proteomic analysis revealed 20 differentially expressed proteins, associated with glycolysis, neuron projection, mitochondrial pathways, metabolic process and ubiquitin binding etc., in the hippocampus between FUS/MB-treated and sham-treated 3×Tg-AD mice. Conclusions: Our findings reinforce the positive therapeutic effects on AD models with both Aβ and tau pathology induced by FUS/MB-mediated BBB opening, further supporting the potential of this treatment regime for clinical applications.

Acoustic radiation force impulse (ARFI) elastography is a non-invasive method for performing liver assessment via liver shear wave velocity (SWV) measurements. The aim of this study was to evaluate the performance of the ARFI technique in the diagnosis of nonalcoholic steatohepatitis (NASH) and fibrosis and to investigate the effect of steatosis and inflammation on liver fibrosis SWV measurements in a rat model of nonalcoholic fatty liver disease (NAFLD). The ex vivo right liver lobes from 110 rats were processed and embedded in a fabricated gelatin phantom, and the other lobes were used for histologic assessment. The SWV induced by acoustic radiation force was derived to evaluate liver stiffness. The experimental results showed that the liver SWV value could be used to differentiate non-NASH rats from NASH-presenting rats and NASH from cirrhosis, and these comparisons showed areas under the receiver operating characteristic curves (AUROC) of 0.951 and 0.980, respectively. The diagnostic performances of ARFI elastography in predicting severe fibrosis ( F ≥ 3) and cirrhosis ( F ≥ 4) showed AUROC values of 0.997 and 0.993, respectively. In rats with mild fibrosis (F0–F1), severe steatosis had a significant effect on the mean SWV values. In rats with significant fibrosis (F2–F4), severe lobular inflammation had significant effects on the mean SWV values. Our findings indicate that ARFI elastography is a promising method for differentiating non-NASH rats from NASH rats and for staging hepatic fibrosis in NASH. The presence of severe steatosis and severe lobular inflammation are significant factors for evaluating fibrosis stages.

Background Brain functional connectivity network (BFCN) has been widely applied to identify biomarkers for the brain function understanding and brain diseases analysis. Objective Building a biologically meaningful brain network is a crucial work in these applications. For this task, sparse learning has been widely applied for the network construction. If multiple time-point data is added to the brain imaging application, the disease progression pattern in the longitudinal analysis can be better revealed. Methods A novel longitudinal analysis for MCI classification is devised based on resting-state functional magnetic resonating imaging (rs-fMRI). Specifically, this paper proposes a novel multi-task learning method to integrate fused penalty by regularization. In addition, a novel objective function is developed for fused sparse learning via smoothness constraint. Results The proposed method achieves the best classification performance with an accuracy of 95.74% for baseline and 93.64% for year 1 data. Conclusions The experimental results show that our proposed method achieves quite promising classification performance.

Ultrasound imaging has become a prevalent examination method in prenatal diagnosis. Accurate acquisition of fetal facial standard plane (FFSP) is the most important precondition for subsequent diagnosis and measurement. In the past few years, considerable effort has been devoted to FFSP recognition using various hand-crafted features, but the recognition performance is still unsatisfactory due to the high intraclass variation of FFSPs and the high degree of visual similarity between FFSPs and other non-FFSPs. To improve the recognition performance, we propose a method to automatically recognize FFSP via a deep convolutional neural network (DCNN) architecture. The proposed DCNN consists of 16 convolutional layers with small 3 × 3 size kernels and three fully connected layers. A global average pooling is adopted in the last pooling layer to significantly reduce network parameters, which alleviates the overfitting problems and improves the performance under limited training data. Both the transfer learning strategy and a data augmentation technique tailored for FFSP are implemented to further boost the recognition performance. Extensive experiments demonstrate the advantage of our proposed method over traditional approaches and the effectiveness of DCNN to recognize FFSP for clinical diagnosis.

In the rice cytoplasmic-genetic male sterility (CMS) system, the combination of a CMS line, maintainer line and restorer line carrying the restorer gene to restore fertility, is indispensable for the development of hybrids. However, the process of screening for the trait of fertility restoration is laborious and time-consuming. In the present study, we analyzed the nucleotide sequence of the Rf4 gene, which is the major locus controlling fertility restoration, to identify allele-specific variation. A single nucleotide polymorphism (SNP) A/C at +474 in the coding sequence (CDS) was found to be capable of strictly distinguishing groups of alleles Rf4 (A) and rf4 (C). Using KASP genotyping, this valuable SNP was converted to an allele-specific PCR marker. We evaluated and validated the marker among three-line parents with different backgrounds, and the results revealed a complete correlation between SNP alleles and the fertility restoration phenotype. Molecular screening was subsequently carried out for the presence of alleles of Rf4 and Rf3 among 328 diverse rice cultivars with worldwide distribution. The results demonstrate that this SNP marker could be the optimal choice for the molecular identification of potential restorers.

Yuanyuan Shen,1 Zhaoke Pi,1 Fei Yan,2 Chih-Kuang Yeh,3 Xiaojun Zeng,4 Xianfen Diao,1 Yaxin Hu,1 Siping Chen,1 Xin Chen,1 Hairong Zheng21National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, People’s Republic of China; 2Paul C Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, People’s Republic of China; 3Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan; 4Shenzhen Second People’s Hospital, Shenzhen, People’s Republic of ChinaAbstract: Paclitaxel liposomes (PTX-LIPO) are a clinically promising antineoplastic drug formulation for the treatment of various extracranial cancers, excluding glioblastoma. A main reason for this is the presence of the blood–brain barrier (BBB) or blood–tumor barrier (BTB), preventing liposomal drugs from crossing at a therapeutically meaningful level. Focused ultrasound (FUS) in conjunction with microbubbles (MBs) has been suggested in many studies to be an effective approach to increase the BBB or BTB permeability. In this study, we investigated the feasibility of enhancing the delivery of PTX-LIPO in intracranial glioblastoma-bearing nude mice using pulsed low-intensity FUS exposure in the presence of MBs. Our results showed that the delivery efficiency of PTX-LIPO could be effectively improved in terms of the penetration of both the BBB in vitro and BTB in vivo by pulsed FUS sonication with a 10 ms pulse length and 1 Hz pulse repetition frequency at 0.64 MPa peak-rarefactional pressure in the presence of MBs. Quantitative analysis showed that a 2-fold higher drug concentration had accumulated in the glioblastoma 3 h after FUS treatment, with 7.20±1.18 µg PTX per g glioma tissue. Longitudinal magnetic resonance imaging analysis illustrated that the intracranial glioblastoma progression in nude mice treated with PTX-LIPO delivered via FUS with MBs was suppressed consistently for 4 weeks compared to the untreated group. The medium survival time of these tumor-bearing nude mice was significantly prolonged by 20.8%, compared to the untreated nude mice. Immunohistochemical analysis further confirmed the antiproliferation effect and cell apoptosis induction. Our study demonstrated that noninvasive low-intensity FUS with MBs can be used as an effective approach to deliver PTX-LIPO in order to improve their chemotherapy efficacy toward glioblastoma.Keywords: paclitaxel liposomes, focused ultrasound, microbubbles, blood-brain barrier

Accurate identification and understanding informative feature is important for early Alzheimer's disease (AD) prognosis and diagnosis. In this paper, we propose a novel discriminative sparse learning method with relational regularization to jointly predict the clinical score and classify AD disease stages using multimodal features. Specifically, we apply a discriminative learning technique to expand the class-specific difference and include geometric information for effective feature selection. In addition, two kind of relational information are incorporated to explore the intrinsic relationships among features and training subjects in terms of similarity learning. We map the original feature into the target space to identify the informative and predictive features by sparse learning technique. A unique loss function is designed to include both discriminative learning and relational regularization methods. Experimental results based on a total of 805 subjects [including 226 AD patients, 393 mild cognitive impairment (MCI) subjects, and 186 normal controls (NCs)] from AD neuroimaging initiative database show that the proposed method can obtain a classification accuracy of 94.68% for AD versus NC, 80.32% for MCI versus NC, and 74.58% for progressive MCI versus stable MCI, respectively. In addition, we achieve remarkable performance for the clinical scores prediction and classification label identification, which has efficacy for AD disease diagnosis and prognosis. The algorithm comparison demonstrates the effectiveness of the introduced learning techniques and superiority over the state-of-the-arts methods.

BACKGROUND Ultrasound elastography has been widely used to measure liver stiffness. However, the accuracy of liver viscoelasticity obtained by ultrasound elastography has not been well established. OBJECTIVE To assess the accuracy of ultrasound elastography for measuring liver viscoelasticity and compare to conventional rheometry methods. In addition, to determine if combining these two methods could delineate the rheological behavior of liver over a wide range of frequencies. METHODS The phase velocities of shear waves were measured in livers over a frequency range from 100 to 400 Hz using the ultrasound elastography method of shearwave dispersion ultrasound vibrometry (SDUV), while the complex shear moduli were obtained by rheometry over a frequency range of 1 to 30 Hz. Three rheological models, Maxwell, Voigt, and Zener, were fit to the measured data obtained from the two separate methods and from the combination of the two methods. RESULTS The elasticity measured by SDUV was in good agreement with that of rheometry. However, the viscosity measured by SDUV was significantly different from that of rheometry. CONCLUSIONS The results indicate that the high frequency components of the dispersive data play a much more important role in determining the dispersive pattern or the viscous value than the low frequency components. It was found that the Maxwell model is not as appropriate as the Voigt and Zener models for describing the rheological behavior of liver.

Placental maturity staging is a challenging task due to complex imaging procedure, fetal and gestational age variations. To address this issue, we extract features not only from B-mode gray-scale ultrasound (US) images, but also from color Doppler energy (CDE) images. Based on these features, we propose a method to automatically determine the placental maturity by harnessing multi-view and multi-layout discriminative learning fusion. Specifically, we devise a multi-view technique to generate features of complementary information. Scale invariant features are extracted from image locally, and a Gaussian mixture model (GMM) is then applied to summarize the high-level information features. The clustering representatives from GMM are encoded via a multi-layout Fisher vector (MFV) instead of traditional Fisher vector (FV) to aggregate features based on their spatial information. We apply a multi-layout feature encoding method to improve the staging performance using discriminative learning technique. Extensive experimental results demonstrate that our method achieves promising performance in placental maturity staging and outperforms existing methods.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases in developed countries. Accurate, noninvasive tests for diagnosing NAFLD are urgently needed. The goals of this study were to evaluate the utility of acoustic radiation force impulse (ARFI) elastography for determining the severity grade of steatosis in rat livers, and to investigate the changes in various histologic and biochemical characteristics. Steatosis was induced in the livers of 57 rats by gavage feeding of a high fat emulsion; 12 rats received a standard diet only and served as controls. Liver mechanics were measured ex vivo using shear wave velocity (SWV) induced by acoustic radiation force. The measured mean values of liver SWV ranged from 1.33 to 3.85m/s for different grades of steatosis. The area under the receiver operative characteristic curve (⩾S1) was equal to 0.82 (95% CI=0.69, 0.96) between the steatosis group and the normal group, and the optimal cutoff value was 2.59 with sensitivity of 88% and specificity of 76%. However, there are no significant differences in SWV measurements between the steatosis grades. SWV values did not correlate with the early grade of inflammation. In conclusion, ARFI elastography is a promising method for differentiating normal rat liver from rat liver with steatosis, but it cannot reliably predict the grade of steatosis in rat livers. The early grade of inflammation activity did not significantly affect the SWV measurements.

Fetal viability, gestational age, and complicated image processing have made evaluating placental maturity a tedious and time-consuming task. Despite various developments, automatic placental maturity still remains as a challenging issue. To address this issue, we propose a new method to automatically grade placental maturity from B-mode ultrasound (BUS) and color Doppler energy (CDE) images based on a hybrid learning architecture. We also apply an improved pyramidal shift invariant feature transform (IPSIFT) descriptor using a coarse-to-fine scale representation for visual feature extraction. These local features are then clustered by a generative Gaussian mixture model (GMM) to incorporate high order statistics. Next, the clustering representatives are encoded and aggregated via Fisher vector (FV). Instead of using traditional FV, an end-to-end deep training strategy is developed to fine-tune the GMM parameters to boost evaluation performance. A multi-view fusion technique is also developed for feature complementarity exploration. Extensive experimental results demonstrate that our method delivers promising performance in placental maturity evaluation and outperforms competing methods.

Accurate segmentation of cervical cells in Pap smear images is an important step in automatic pre-cancer identification in the uterine cervix. One of the major segmentation challenges is overlapping of cytoplasm, which has not been well-addressed in previous studies. To tackle the overlapping issue, this paper proposes a learning-based method with robust shape priors to segment individual cell in Pap smear images to support automatic monitoring of changes in cells, which is a vital prerequisite of early detection of cervical cancer. We define this splitting problem as a discrete labeling task for multiple cells with a suitable cost function. The labeling results are then fed into our dynamic multi-template deformation model for further boundary refinement. Multi-scale deep convolutional networks are adopted to learn the diverse cell appearance features. We also incorporated high-level shape information to guide segmentation where cell boundary might be weak or lost due to cell overlapping. An evaluation carried out using two different datasets demonstrates the superiority of our proposed method over the state-of-the-art methods in terms of segmentation accuracy.

This study assesses gradations of hepatic fibrosis in rat livers using both model-dependent and model-independent approaches. Liver fibrosis was induced in 37 rats using carbon tetrachloride (CCl 4 ); 6 rats served as the controls. Shear wave velocity as a function of frequency, referred to as velocity dispersion, was measured in vitro by an ultrasound elastography method called shearwave dispersion ultrasound vibrometry (SDUV). For the model-dependent approach, the velocity dispersion data were fit to the Voigt model to solve the viscoelastic modulus. For the model-independent approach, the pattern of the velocity dispersion data was analyzed by linear regression to extract the slope and intercept features. The parameters obtained by both approaches were evaluated separately using a receiver operating characteristic (ROC) curve analysis. The results show that, of all the parameters for differentiating between grade F0–F1 and grade F2–F4 fibrosis, the intercept had the greatest value for the area under the ROC curve. This finding suggests that the model-independent approach may provide an alternative method to the model-dependent approach for staging liver fibrosis.

Background Rice stripe mosaic virus (RSMV) is a tentative new Cytorhabdovirus species in family Rhabdoviridae transmitted by the leafhopper Recilia dorsalis. Although the virus was first detected in southern China in 2015, few studies have investigated rice symptoms and yield losses caused by RSMV infection. Methods In this study, we observed and systematically compared symptoms of three virally infected, representative varieties of indica, hybrid and japonica rice and determined the yield parameters of the artificially inoculated plants. Results The three RSMV-infected cultivated rice varieties exhibited slight dwarfing, striped mosaicism, stiff, crinkled or even twisted leaves, an increased number of tillers, delayed heading, cluster-shaped shortening of panicles and mostly unfilled grains. Slight differences in symptom occurrence time were observed under different environmental conditions. For example, mosaic symptoms appeared earlier and crinkling symptoms appeared later, with both symptoms later receding in some infected plants. Yield losses due to RSMV also differed among varieties. The most serious yield reduction was experienced by indica rice (cv. Meixiangzhan), followed by hybrid indica rice (cv. Wuyou 1179) and then japonica (cv. Nipponbare). Single panicle weight, seed setting rate and 1000-kernel weight were reduced in the three infected varieties compared with healthy plants—by 85.42, 94.85 and 31.56% in Meixiangzhan; 52.43, 53.06 and 25.65% in Wuyou 1179 and 25.53, 49.32 and 23.86% in Nipponbare, respectively. Conclusions Our findings contribute basic data for field investigations, formulation of prevention and control strategies and further study of the pathogenesis of RSMV.

Real time transcranial ultrasound imaging of brain can be extremely intriguing because of its numerous applications. In this study, we proposed an ultrafast transcranial ultrasound imaging technique with diverging wave (DW) transmission, which has been a promising technique to image moving objects, such as complex blood flow field and transient elastography. However, diverging waves are all unfocused waves, which makes their image quality, especially the lateral resolution and contrast, has not yet been satisfactory. Here we tried to apply the adaptive beamforming algorithms to improve both the image contrast and the lateral resolution. Simulation and phantom experiments proved that our methods can significantly improve the DW image quality. Finally, transcranial ultrasound imaging collected through temporal bone were presented and analyzed. The ultrasound frequency used in this study ranges from 2 MHz to 4 MHz, centered at 2.8 MHz. Since the wavefront was offset and distorted after passing through temporal bone, the image quality will be slightly degraded. Even then, it was demonstrated that these adaptive algorithms can significantly improve the transcranial image quality, especially the image contrast.

There is a steady demand for high-quality rice varieties though consumers’ preference for high-quality rice varies from regions. The improvement of the quality of rice, especially its eating and cooking quality (ECQ), is an important breeding target as rice is mainly consumed in cooked form. The development and utilization of breeder-friendly and high-throughput marker systems play a pivotal role in marker-assisted breeding of rice cultivars, with pyramids of valuable genes affecting rice ECQ. In this study, we developed functional markers based on the Kompetitive Allele-Specific PCR (KASP) method for three principal genes, Wx, BADH2 and ALK, affecting ECQ in rice. The accuracy of all KASP markers was verified and confirmed with Sanger sequencing. A diverse rice panel consisting of 38 indica cultivars, 9 japonica cultivars and 1 Javanica cultivar were used to assess the validity of these markers for genotyping. The results showed that the functional KASP markers of Wx, ALK and BADH2 could effectively distinguish the different alleles. The genotyping results highly coincided with the phenotypic traits of rice eating and cooking quality. Eight rice entries harboring 3 favorable alleles were identified and superior rice restorers with improved ECQ were bred via functional marker genotyping. Breeders can develop rice cultivars that have desirable ECQ, customized to meet the market requirements in target regions. Hence, the development of these 3 applicable KASP functional markers based on allelic variation would be valuable for improving rice eating and cooking quality through maker-assisted selection to carter various consumer preferences especially in Asian areas.

It is essential to measure anatomical parameters in prenatal ultrasound images for the growth and development of the fetus, which is highly relied on obtaining a standard plane. However, the acquisition of a standard plane is, in turn, highly subjective and depends on the clinical experience of sonographers. In order to deal with this challenge, we propose a new multi-task learning framework using a faster regional convolutional neural network (MF R-CNN) architecture for standard plane detection and quality assessment. MF R-CNN can identify the critical anatomical structure of the fetal head and analyze whether the magnification of the ultrasound image is appropriate, and then performs quality assessment of ultrasound images based on clinical protocols. Specifically, the first five convolution blocks of the MF R-CNN learn the features shared within the input data, which can be associated with the detection and classification tasks, and then extend to the task-specific output streams. In training, in order to speed up the different convergence of different tasks, we devise a section train method based on transfer learning. In addition, our proposed method also uses prior clinical and statistical knowledge to reduce the false detection rate. By identifying the key anatomical structure and magnification of the ultrasound image, we score the ultrasonic plane of fetal head to judge whether it is a standard image or not. Experimental results on our own-collected dataset show that our method can accurately make a quality assessment of an ultrasound plane within half a second. Our method achieves promising performance compared with state-of-the-art methods, which can improve the examination effectiveness and alleviate the measurement error caused by improper ultrasound scanning.

Background Surgery is the gold standard therapy for patients with early-stage non–small-cell lung cancer (NSCLC). However, stereotactic body radiotherapy (SBRT) may provide as an alternative for patients who are medically inoperable or refuse surgical resection. The optimal treatment (SBRT or surgery) for patients with early-stage NSCLC is not clear. Methods A systematic search was performed from PubMed, MEDLINE, Embase, and the Cochrane Library. Study heterogeneity and publication bias were estimated. Results Fourteen cohort studies involving 1438 participants (719 who received SBRT and 719 who received surgery) were included in the meta-analysis. The main bias sources between the two groups, such as age, gender, tumor diameter, forced expiratory volume in 1 s, and Charlson comorbidity index were matched. The surgery was associated with a better overall survival (OS) and long-term distant control (DC) for early-stage NSCLC. The pooled OR and 95% confidence interval (CI) for 1-y, 3-y, 5-y OS, and 5-y DC were 1.56 (1.12-2.15), 1.86 (1.50-2.31), 2.43 (1.80-3.28), and 2.74 (1.12-6.67), respectively. No difference was found between the treatments in the 1-y and 3-y disease-free survival; 1-y, 3-y and 5-y locoregional control; or 1-y and 3-y DC. Conclusions Our results found a superior OS and long-term DC for early-stage NSCLC after surgery compared with SBRT after propensity score matching.

Optical coherence tomography angiography (OCTA) is extensively used for visualizing retinal vasculature, including the foveal avascular zone (FAZ). Assessment of the FAZ is critical in the diagnosis and management of various retinal diseases. Accurately segmenting the FAZ in the deep retinal layer (dFAZ) is very challenging due to unclear capillary terminals. In this study, a customized encoder-decoder deep learning network was used for dFAZ segmentation. Six-fold cross-validation was performed on a total of 80 subjects (63 healthy subjects and 17 diabetic retinopathy subjects). The proposed method obtained an average Dice of 0.88 and an average Hausdorff distance of 17.79, suggesting the dFAZ was accurately segmented. The proposed method is expected to realize good clinical application value by providing an objective and faster and spatially-quantitative preparation of dFAZ-related investigations.

With the increasing aging population as well as health concerns, chronic heart disease has become the focus of public attention. A comfortable, low-powered, and wearable electrocardiogram (ECG) system for continuously monitoring the elderly's ECG signals over several hours is important for preventing cardiovascular diseases. Traditional ECG monitoring apparatus is often inconvenient to carry, has many electrodes to attach to the chest, and has a high-power consumption. There is also a challenge to design an electrocardiograph that satisfies requirements such as comfort, confinement, and compactness. Based on these considerations, this study presents a biosensor acquisition system for wearable, ubiquitous healthcare applications using three textile electrodes and a recording circuit specialized for ECG monitoring. In addition, several methods were adopted to reduce the power consumption of the device. The proposed system is composed of three parts: (1) an ECG analog front end (AFE), (2) digital signal processing and micro-control circuits, and (3) system software. Digital filter methods were used to eliminate the baseline wander, skin contact noise, and other interfering signals. A comparative study was conducted using this system to observe its performance with two commercial Holter monitors. The experimental results demonstrated that the total power consumption of this proposed system in a full round of ECG acquisition was only 29.74 mW. In addition, this low-power system performed well and stably measured the heart rate with an accuracy of 98.55 %. It can also contain a real-time dynamic display with organic light-emitting diodes (OLED) and wirelessly transmit information via a Bluetooth 4.0 module.

An ultrasound imaging framework modeled with the first order nonlinear pressure–velocity relations (NPVR) and implemented by a half-time staggered solution and pseudospectral method is presented in this paper. The framework is capable of simulating linear and nonlinear ultrasound propagation and reflections in a heterogeneous medium with different sound speeds and densities. It can be initialized with arbitrary focus, excitation and apodization for multiple individual channels in both 2D and 3D spatial fields. The simulated channel data can be generated using this framework, and ultrasound image can be obtained by beamforming the simulated channel data. Various results simulated by different algorithms are illustrated for comparisons. The root mean square (RMS) errors for each compared pulses are calculated. The linear propagation is validated by an angular spectrum approach (ASA) with a RMS error of 3% at the focal point for a 2D field, and Field II with RMS errors of 0.8% and 1.5% at the electronic and the elevation focuses for 3D fields, respectively. The accuracy for the NPVR based nonlinear propagation is investigated by comparing with the Abersim simulation for pulsed fields and with the nonlinear ASA for monochromatic fields. The RMS errors of the nonlinear pulses calculated by the NPVR and Abersim are respectively 2.4%, 7.4%, 17.6% and 36.6% corresponding to initial pressure amplitudes of 50 kPa, 200 kPa, 500 kPa and 1 MPa at the transducer. By increasing the sampling frequency for the strong nonlinearity, the RMS error for 1 MPa initial pressure amplitude is reduced from 36.6% to 27.3%.

The progression of liver fibrosis changes the biomechanical properties of liver tissue. This study characterized and compared different liver fibrosis stages in rats in terms of viscoelasticity. Three viscoelastic models, the Voigt, Maxwell, and Zener models, were applied to experimental data from rheometer tests and then the elasticity and viscosity were estimated for each fibrosis stage. The study found that both elasticity and viscosity are correlated with the various stages of liver fibrosis. The study revealed that the Zener model is the optimal model for describing the mechanical properties of each fibrosis stage, but there is no significant difference between the Zener and Voigt models in their performance on liver fibrosis staging. Therefore the Voigt model can still be effectively used for liver fibrosis grading.

Transforming growth factor (TGF)‑β1 has a key role in the regulation of fibrosis and organ dysfunction. During the pathogenesis and progression of vital organ fibrosis, the microRNA (miR)‑29 family is irregularly downregulated and exogenous supplementation of miR‑29b has a strong anti‑fibrotic capacity. However, whether TGF‑β1 is able to provoke endometrial fibrosis, and the role of miR‑29 in endometrial fibrosis remain unclear. In the present study, RT‑qPCR, immunocytochemistry, western blot analysis, scanning electron microscopy, immunofluorescence staining, cell proliferation assay and flow cytometric analysis were employed. The results demonstrated that the expression levels of collagen, type 1, alpha 1 (COL1A1), α‑smooth muscle actin (α‑SMA) and phosphorylated (p)‑Smad2/3 were increased, whereas miR‑29b and maternally expressed gene 3 (MEG3) were decreased in primary endometrial stromal cells (ESCs) in response to TGF‑β1 stimulation, in a time and dose‑dependent manner. Furthermore, overexpression of miR‑29b markedly reduced the expression levels of COL1A1 and α‑SMA, and decreased the expression and nuclear accumulation of p‑Smad2/3. In addition, ectopic overexpression of miR‑29b increased the expression levels of MEG3, inhibited myofibroblast‑like cell proliferation and induced apoptosis. These findings indicated that miR‑29b may have a significant anti‑fibrotic role, and may attenuate TGF‑β1‑induced fibrosis in ESCs. Therefore, exogenous miR‑29b may serve as a potential therapeutic agent for the treatment of endometrial fibrosis.

Polynomial regression is the most common method to estimate the relationship between muscle signals and torque during muscle contraction, but it is not capable of characterizing important transient patterns in the signal–torque relationship that only exist during short bursts of torque but may convey detailed information of muscle behavior. In this study, we proposed an integrated data analysis approach based on local polynomial regression (LPR) to identify transient patterns in the signal–torque relationship. For each subject, the LPR method can represent electromyography (EMG), mechanomyography (MMG) and ultrasonography (US) features as nonlinear functions of torque and can further estimate the derivatives of these signal–torque nonlinear functions. Further, a number of break points can be detected from the derivatives of the signal–torque relationships at the group level, and they can segment the signal–torque relationships into several stages, where multimodal features change with torque in different dynamic manners. Eight subjects performed isometric ramp contraction of knee up to 90% of the maximal voluntary contraction (MVC). EMG, MMG and US were simultaneously recorded from the rectus femoris muscle. Results showed that, for each feature, the whole torque range were clearly segmented into several distinct stages by the proposed method and the feature–torque relationship could be approximately described by a piecewise linear function with different slopes at different stages. A critical break-point of 20% MVC was detected during the isometric contraction for all muscle signals. As compared with the conventional regression methods, the proposed LPR-based data analysis approach can effectively identify stage-dependent transient patterns in the feature–torque relationships, providing deeper insights into the motor unit activation strategy.

Skin lesion segmentation from dermoscopy images is a fundamental yet challenging task in the computer-aided skin diagnosis system due to the large variations in terms of their views and scales of lesion areas. We propose a novel and effective generative adversarial network (GAN) to meet these challenges. Specifically, this network architecture integrates two modules: a skip connection and dense convolution U-Net (UNet-SCDC) based segmentation module and a dual discrimination (DD) module. While the UNet-SCDC module uses dense dilated convolution blocks to generate a deep representation that preserves fine-grained information, the DD module makes use of two discriminators to jointly decide whether the input of the discriminators is real or fake. While one discriminator, with a traditional adversarial loss, focuses on the differences at the boundaries of the generated segmentation masks and the ground truths, the other examines the contextual environment of target object in the original image using a conditional discriminative loss. We integrate these two modules and train the proposed GAN in an end-to-end manner. The proposed GAN is evaluated on the public International Skin Imaging Collaboration (ISIC) Skin Lesion Challenge Datasets of 2017 and 2018. Extensive experimental results demonstrate that the proposed network achieves superior segmentation performance to state-of-the-art methods.

The analysis of fundus images in ophthalmology can be greatly facilitated by data integration of multimodal retinal images, which can be achieved via image registration based on the matching of keypoints represented by certain descriptors. However, the matching results offered by conventional feature descriptors may be substantially compromised due to their inconsistent estimates of the main orientation for keypoints in multimodal images. In this paper, we propose an orientation-independent feature matching (OIFM) method for better matching of feature points in multimodal retinal images. The keypoints detected in the images are firstly represented with a new circular neighborhood-based feature descriptor, allowing for the rotation of the neighborhood around the keypoints can be achieved by circularly shifting the elements in the descriptor. Then, the proposed feature descriptor is applied for the matching of keypoints, whose distance is measured after the compensation of the orientation discrepancy. The proposed OIFM method has two distinct characteristics. First, the feature descriptor no longer relies on the calculation of main orientations, and instead it is formulated by stacking the feature vectors of the keypoint neighborhood in a circular order with a conveniently assigned reference. Second, orientation independence is achieved during the matching stage where the feature points are aligned in a global manner, leading the OIFM method more robust to rotation and content variations among multimodal retinal images. Experimental results on a total of 160 pairs of multimodal retinal images show that the proposed OIFM method outperforms the conventional algorithms in terms of registration accuracy and robustness.

Ovarian cancer (OC) is one of the deadliest malignancies of the female reproductive system. The present study focused on the role of Nucleolar spindle-associated protein 1 (NuSAP1) in OC. Relative expression of NuSAP1 was detected in OC tissues as well as cells. After knocking down NuSAP1 with lentivirus-mediated shRNA and verifying the knockdown efficiency via quantitative real-time polymerase chain reaction and Western blot assays, the cell proliferation, apoptosis, and cell cycle were determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, colony formation, and flow cytometry, respectively. Transwell assay was conducted to detect the migration and invasion of OC cells. It was showed that NuSAP1 was abundantly expressed in OC tissues and cell lines. After knocking down NuSAP1 in OC cells, in addition to significantly inhibiting proliferation and colony forming ability, it also promotes apoptosis and affects cell cycle distribution. Moreover, cells in the shNuSAP1 group showed significantly suppressed migration and invasion ability compared with that in the shCtrl group. In conclusion, NuSAP1 may act as an oncogenic factor in OC and therefore might serve as an indicator for prognosis and therapeutic target for OC treatment.

Various physical methods have been developed to modulate the electrophysiologic properties of cells and their biochemical signaling pathways. In this study, we propose a sonomagnetic method using pulsed ultrasound (1.1 MHz frequency, 1.1 or 2.2 MPa pressure, 50 cycles per pulse and 500 Hz pulse repetition frequency) and a static magnetic field (680 mT) to stimulate live cells. We found that sonomagnetic stimulation promoted the cell and mitochondrial membrane potentials to more hyperpolarized states. The degree of cell membrane hyperpolarization was cell-type dependent. Furthermore, we found that the intracellular concentrations of Ca2+ ions, reactive oxygen species and nitric oxide were substantially increased after sonomagnetic stimulation, and a small decrease in intracellular pH was also observed. Lastly, we found that the daily sonomagnetic stimulation for 3 d inhibited the proliferation rate of neuro-2a cancer cells by 48.64%. Our work demonstrates that sonomagnetic stimulation can effectively perturb cell signaling and drive cancer cells into relatively quiescent states.

Automatic delineation of skin lesion contours from dermoscopy images is a basic step in the process of diagnosis and treatment of skin lesions. However, it is a challenging task due to the high variation of appearances and sizes of skin lesions. In order to deal with such challenges, we propose a new dense deconvolutional network (DDN) for skin lesion segmentation based on residual learning. Specifically, the proposed network consists of dense deconvolutional layers (DDLs), chained residual pooling (CRP), and hierarchical supervision (HS). First, unlike traditional deconvolutional layers, DDLs are adopted to maintain the dimensions of the input and output images unchanged. The DDNs are trained in an end-to-end manner without the need of prior knowledge or complicated postprocessing procedures. Second, the CRP aims to capture rich contextual background information and to fuse multilevel features. By combining the local and global contextual information via multilevel feature fusion, the high-resolution prediction output is obtained. Third, HS is added to serve as an auxiliary loss and to refine the prediction mask. Extensive experiments based on the public ISBI 2016 and 2017 skin lesion challenge datasets demonstrate the superior segmentation results of our proposed method over the state-of-the-art methods.

As magneto-acoustic-electrical tomography (MAET) combines the merits of high contrast and high imaging resolution, and is extremely useful for electrical conductivity measurement, so it is expected to be a promising medical imaging modalities for diagnosis of early-stage cancer. Based on the Verasonics system and the MC600 displacement platform, we designed and implemented a MAET system with a chirp pulse stimulation (MAET-CPS) method and a focal probe was utilized for stepscan focus excitation to enhance the imaging resolution. The relevant experiments were conducted to explore the influence of excitation positions of the single-focus point, and the effect of the excitation position on the amplitudes of the conductivity variation was clearly demonstrated. In order to take advantage of the merits of multifocus imaging, we firstly proposed a single focus MAET system with a chirp pulse stimulation (sfMAET-CPS) method and a multifocus MAET system with a chirp pulse stimulation (mfMAET-CPS) method for high-resolution conductivity imaging, and a homogenous gelatin phantom with a cuboid-shaped hole was used to investigate the accuracy of mfMAET-CPS. Comparative experiments were carried out on the same uniform phantom by the sfMAET-CPS and the mfMAET-CPS, respectively. The results showed that: (1) the electrical conductivity distributions of the homogenous phantom with a cuboid-shaped hole were detected by the sfMAET-CPS but were easily affected by the focal point, which demonstrated that the sfMAET-CPS had a low imaging resolution. (2) Compared with the sfMAET-CPS, the imaging effect of the mfMAET-CPS was much better than that of the sfMAET-CPS. (3) A linear interpolation algorithm was used to process the 2D conductivity distribution, it increased the smoothness of the conductivity distribution and improved the imaging effect. The stepscan focus excitation and the linearly frequency-modulated theory provide an alternative scheme for the clinical application of MAET.

Background The pathological or physiological changes of a crystalline lens directly affect the eye accommodation and transmittance, and then they increase the risk of presbyopia and cataracts for people in the middle and old age groups. There is no universally accepted quantitative method to measure the lens' mechanical properties in vivo so far. This study aims to investigate the possibility of assessing the age-related stiffness change of crystalline lens by acoustic-radiation-force-based ultrasound elastography (ARF-USE) in a rabbit model in vivo. Methods There were 13 New Zealand white rabbits that were divided into four groups and fed normally until they were 60 (n = 4), 90 (n = 2), 120 (n = 4), and 150 (n = 3) days old, respectively. An ARF-USE platform was built based on the Verasonics™ Vantage 256 system. The shear waves were excited and traced in the lens by a linear ultrasound probe after a rabbit was anaesthetized. Results The average group velocities were 1.38 ± 0.2 m/s, 2.06 ± 0.3 m/s, 2.07 ± 0.29 m/s, and 2.30 ± 0.28 m/s, respectively, for the four groups of rabbits. The results shows that the group velocity has a strong correlation with the day age (r = 0.84, p < 1 × 10−7) and the weight (r = 0.83, p < 1×10−7) of the rabbits while the maximum displacement has no correlations with the day age (r = 0.27, p > 0.1) and the weight (r = 0.32, p > 0.1). Conclusion This study demonstrated that the group velocity measured by ARF-USE had a strong correlation with age-related stiffness in a rabbit model, suggesting that group velocity is a good biomarker to characterize the stiffness of a crystalline lens. This study also demonstrated the feasibility of using this USE technique to assess the mechanical properties of the lens in vivo for clinical or research purposes.

During the past two decades, tissue elasticity has been extensively studied and has been used in clinical disease diagnosis. But biological soft tissues are viscoelastic in nature. Therefore, they should be simultaneously characterized in terms of elasticity and viscosity. In addition, the mechanical properties of soft tissues are temperature dependent. However, how the temperature influences the shear wave dispersion and the viscoelasticity of soft tissue are still unclear. The aim of this study is to compare viscoelasticity of fat emulsion phantom with different temperature using acoustic radiation force elasticity imaging method. In our experiment, we produced four proportions of ultrasonic phantom by adding fat emulsion gelatin. Through adjusting the component of the fat emulsion, we change the viscoelasticity of the ultrasonic phantom. We used verasonics system to gather data and voigt model to fit the elasticity and viscosity value of the ultrasonic phantom we made. The influence of temperature to the ultrasonic phantom also measured in our study. The results show that the addition of fat emulsion to the phantom can increase the viscosity of the phantom, and the shear wave phase velocity decreases gradually at each frequency with the temperature increases, which provides a new material for the production of viscoelastic phantom.

Nanometer-scale pores have been developed for the detection, characterization, and quantification of a wide range of analytes (e.g., ions, polymers, proteins, anthrax toxins, neurotransmitters, and synthetic nanoparticles) and for DNA sequencing. We describe the key requirements that made this method possible and how the technique evolved. Finally, we show that, despite sound theoretical work, which advanced both the conceptual framework and quantitative capability of the method, there are still unresolved questions that need to be addressed to further improve the technique.

The determination and interpretation of fetal standard planes (FSPs) in ultrasound examinations are the precondition and essential step for prenatal ultrasonography diagnosis. However, identifying multiple standard planes from ultrasound videos is a time-consuming and tedious task since there are only little differences between standard and non-standard planes in the adjacent scan frames. To address this challenge, we propose a general and efficient framework to detect several standard planes from ultrasound scan images or videos automatically. Specifically, a multi-scale dense networks (MSDNet) utilizing the multi-scale architecture and dense connection is exploited, which combines the fine level features from the shallow layers and coarse level features from the deep layers. Moreover, this MSDNet is resource efficient, and the cascade structure can adaptively select lightweight networks when test images are not complicated or computational resources limited. Experimental results based on our self-collected dataset demonstrate that the proposed method achieves a mean average precision (mAP) of 98.15% with half resources and double speeds in FSPs recognition task.

To evaluate meibomian gland morphology and function in children without ocular discomfort.A total of 266 eyes of 266 children without signs or symptoms of ocular surface dysfunction were enrolled. Morphology of meibomian glands (MG) and non-invasive break-up time (BUT) was assessed by noncontact meibography. Based on lipid layer thickness (LLT) of the tear film measurements, 66 children were chosen to be assessed by meibomian glands yielding liquid secretion (MGYLS).Based on the presence of physiologic conjunctival follicles (PCF), participants were divided into normal or PCF groups. The distortion and deficiency of MG function was significantly higher in PCF group (P = 0.002, 0.007, respectively). Five different gland duct shapes (vertical, tortuous, overriding, hooked, U-shaped) were observed. MG deficiency was positively correlated with age (R = 0.362, P 0.001). Distortion and the number of MG showed no correlation with age (P 0.05). However, distortion and deficiency of MG were negatively correlated with LLT (P 0.001, P 0.01).Children with PCF had significantly more MG distortion and deficiency which was associated with LLT. These results prompt future studies to determine if changes in MG morphology are congenital or acquired.