Bubble-Inspired Multifunctional Magnetic Microrobots for Integrated Multidimensional Targeted Biosensing.

Microrobots possessing multifunctional integration are desired for therapeutics and biomedicine applications. However, existing microrobots with desired functionalities need to be fabricated through complex procedures due to their constrained volume, limited manufacturing processes, and lack of effective in vivo observation methods. Inspired by bubbles exhibiting various abilities, we report magnetic air bubble microrobots with simpler structures to simultaneously integrate multiple functions, including microcargo delivery, multimode locomotion, imaging, and biosensing. Contributed by buoyancy and magnetic actuation to overcome obstacles, flexible three-dimensional locomotion is implemented, guaranteeing the integrity of micro-objects adsorbed on the surface of the air bubble microrobot. Introducing air microbubbles enhances the ultrasound imaging capability of microrobots in the vascular system of mice in vivo, facilitating ample medical applications. Moreover, air-liquid reactions endow microrobots with rapid pH biosensing. This work provides a unique strategy to utilize relatively simple air bubbles to achieve the complex functions of microrobots for biomedical applications.

External light-dark cycle shapes gut microbiota through intrinsically photosensitive retinal ganglion cells.

Gut microbiota are involved in many physiological functions such as metabolism, brain development, and neurodegenerative diseases. Many microbes in the digestive tract do not maintain a constant level of their relative abundance but show daily oscillations under normal conditions. Recent evidence indicates that chronic jetlag, constant darkness, or deletion of the circadian core gene can alter the composition of gut microbiota and dampen the daily oscillation of gut microbes. However, the neuronal circuit responsible for modulating gut microbiota remained unclear. Using genetic mouse models and 16s rRNA metagenomic analysis, we find that light-dark cycle information transmitted by the intrinsically photosensitive retinal ganglion cells (ipRGCs) is essential for daily oscillations of gut microbes under temporal restricted high-fat diet conditions. Furthermore, aberrant light exposure such as dim light at night (dLAN) can alter the composition, relative abundance, and daily oscillations of gut microbiota. Together, our results indicate that external light-dark cycle information can modulate gut microbiota in the direction from the brain to the gut via the sensory system.

Diagnosis of Esophageal Lesions by Multi-Classification and Segmentation Using an Improved Multi-Task Deep Learning Model.

It is challenging for endoscopists to accurately detect esophageal lesions during gastrointestinal endoscopic screening due to visual similarities among different lesions in terms of shape, size, and texture among patients. Additionally, endoscopists are busy fighting esophageal lesions every day, hence the need to develop a computer-aided diagnostic tool to classify and segment the lesions at endoscopic images to reduce their burden. Therefore, we propose a multi-task classification and segmentation (MTCS) model, including the Esophageal Lesions Classification Network (ELCNet) and Esophageal Lesions Segmentation Network (ELSNet). The ELCNet was used to classify types of esophageal lesions, and the ELSNet was used to identify lesion regions. We created a dataset by collecting 805 esophageal images from 255 patients and 198 images from 64 patients to train and evaluate the MTCS model. Compared with other methods, the proposed not only achieved a high accuracy (93.43%) in classification but achieved a dice similarity coefficient (77.84%) in segmentation. In conclusion, the MTCS model can boost the performance of endoscopists in the detection of esophageal lesions as it can accurately multi-classify and segment the lesions and is a potential assistant for endoscopists to reduce the risk of oversight.

Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning.

OBJECTIVES: To evaluate the performance of deep learning using ResNet50 in differentiation of benign and malignant vertebral fracture on CT. METHODS: A dataset of 433 patients confirmed with 296 malignant and 137 benign fractures was retrospectively selected from our spinal CT image database. A senior radiologist performed visual reading to evaluate six imaging features, and three junior radiologists gave diagnostic prediction. A ROI was placed on the most abnormal vertebrae, and the smallest square bounding box was generated. The input channel into ResNet50 network was 3, including the slice with its two neighboring slices. The diagnostic performance was evaluated using 10-fold cross-validation. After obtaining the malignancy probability from all slices in a patient, the highest probability was assigned to that patient to give the final diagnosis, using the threshold of 0.5. RESULTS: Visual features such as soft tissue mass and bone destruction were highly suggestive of malignancy; the presence of a transverse fracture line was highly suggestive of a benign fracture. The reading by three radiologists with 5, 3, and 1 year of experience achieved an accuracy of 99%, 95.2%, and 92.8%, respectively. In ResNet50 analysis, the per-slice diagnostic sensitivity, specificity, and accuracy were 0.90, 0.79, and 85%. When the slices were combined to ve per-patient diagnosis, the sensitivity, specificity, and accuracy were 0.95, 0.80, and 88%. CONCLUSION: Deep learning has become an important tool for the detection of fractures on CT. In this study, ResNet50 achieved good accuracy, which can be further improved with more cases and optimized methods for future clinical implementation. KEY POINTS: • Deep learning using ResNet50 can yield a high accuracy for differential diagnosis of benign and malignant vertebral fracture on CT. • The per-slice diagnostic sensitivity, specificity, and accuracy were 0.90, 0.79, and 85% in deep learning using ResNet50 analysis. • The slices combined with per-patient diagnostic sensitivity, specificity, and accuracy were 0.95, 0.80, and 88% in deep learning using ResNet50 analysis.

Multi-Task Model for Esophageal Lesion Analysis Using Endoscopic Images: Classification with Image Retrieval and Segmentation with Attention.

The automatic analysis of endoscopic images to assist endoscopists in accurately identifying the types and locations of esophageal lesions remains a challenge. In this paper, we propose a novel multi-task deep learning model for automatic diagnosis, which does not simply replace the role of endoscopists in decision making, because endoscopists are expected to correct the false results predicted by the diagnosis system if more supporting information is provided. In order to help endoscopists improve the diagnosis accuracy in identifying the types of lesions, an image retrieval module is added in the classification task to provide an additional confidence level of the predicted types of esophageal lesions. In addition, a mutual attention module is added in the segmentation task to improve its performance in determining the locations of esophageal lesions. The proposed model is evaluated and compared with other deep learning models using a dataset of 1003 endoscopic images, including 290 esophageal cancer, 473 esophagitis, and 240 normal. The experimental results show the promising performance of our model with a high accuracy of 96.76% for the classification and a Dice coefficient of 82.47% for the segmentation. Consequently, the proposed multi-task deep learning model can be an effective tool to help endoscopists in judging esophageal lesions.

T1rho and T2 mapping of ankle cartilage of female and male ballet dancers.

BACKGROUND: Since ballet dancers begin their training before skeletal maturity, accurate and non-invasive identification of cartilage diseases is clinically important. Angle-dependent analysis of T1rho and T2 sequences can be useful for quantification of the composition of cartilage. PURPOSE: To investigate the angle-dependent T1rho and T2 profiles of ankle cartilage in non-dancers and dancers. MATERIAL AND METHODS: Ten female non-dancers, ten female dancers, and 9 male dancers were evaluated using T1rho and T2 mapping sequences. Manual segmentation of talar and tibial cartilage on these images was performed by two radiologists. Inter- and intra-rater reliabilities were calculated using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. Mean thickness and volume of cartilage were estimated. Angle-dependent relaxation time profiles of talar and tibial cartilage were created. RESULTS: ICCs of the number of segmented pixels were poor to excellent. Bland-Altman plots indicated that differences were associated with segment sizes. Segmented cartilage on T1rho demonstrated larger thickness and volume than those on T2 in all populations. Male dancers showed larger cartilage thickness and volume than female dancers and non-dancers. Each cartilage demonstrated angular-dependent T1rho and T2 profiles. Minimal T1rho and T2 values were observed at approximately 180°-200°; higher values were seen at the angle closer to the magic angle. Minimal T2 value of talar cartilage of dancers was larger than that of non-dancers. CONCLUSION: In this small cohort study, regional and sex variations of ankle cartilage T1rho and T2 values in dancers and non-dancers were demonstrated using an angle-dependent approach.

Diagnosis of spinal lesions using perfusion parameters measured by DCE-MRI and metabolism parameters measured by PET/CT.

PURPOSE: To investigate the correlation of parameters measured by dynamic-contrast-enhanced MRI (DCE-MRI) and 18F-FDG PET/CT in spinal tumors, and their role in differential diagnosis. METHODS: A total of 49 patients with pathologically confirmed spinal tumors, including 38 malignant, six benign and five borderline tumors, were analyzed. The MRI and PET/CT were done within 3 days, before biopsy. On MRI, the ROI was manually placed on area showing the strongest enhancement to measure pharmacokinetic parameters Ktrans and kep. On PET, the maximum standardized uptake value SUVmax was measured. The parameters in different histological groups were compared. ROC was performed to differentiate between the two largest subtypes, metastases and plasmacytomas. Spearman rank correlation was performed to compare DCE-MRI and PET/CT parameters. RESULTS: The Ktrans, kep and SUVmax were not statistically different among malignant, benign and borderline groups (P = 0.95, 0.50, 0.11). There was no significant correlation between Ktrans and SUVmax (r = - 0.20, P = 0.18), or between kep and SUVmax (r = - 0.16, P = 0.28). The kep was significantly higher in plasmacytoma than in metastasis (0.78 ± 0.17 vs. 0.61 ± 0.18, P = 0.02); in contrast, the SUVmax was significantly lower in plasmacytoma than in metastasis (5.58 ± 2.16 vs. 9.37 ± 4.26, P = 0.03). In differential diagnosis, the AUC of kep and SUVmax was 0.79 and 0.78, respectively. CONCLUSIONS: The vascular parameters measured by DCE-MRI and glucose metabolism measured by PET/CT from the most aggressive tumor area did not show a significant correlation. The results suggest they provide complementary information reflecting different aspects of the tumor, which may aid in diagnosis of spinal lesions. These slides can be retrieved under Electronic Supplementary Material.

Identification of TMAO-producer phenotype and host-diet-gut dysbiosis by carnitine challenge test in human and germ-free mice.

OBJECTIVE: The gut microbiota-derived metabolite, trimethylamine N-oxide (TMAO) plays an important role in cardiovascular disease (CVD). The fasting plasma TMAO was shown as a prognostic indicator of CVD incident in patients and raised the interest of intervention targeting gut microbiota. Here we develop a clinically applicable method called oral carnitine challenge test (OCCT) for TMAO-related therapeutic drug efforts assessment and personalising dietary guidance. DESIGN: A pharmacokinetic study was performed to verify the design of OCCT protocol. The OCCT was conducted in 23 vegetarians and 34 omnivores to validate gut microbiota TMAO production capacity. The OCCT survey was integrated with gut microbiome, host genotypes, dietary records and serum biochemistry. A humanised gnotobiotic mice study was performed for translational validation. RESULTS: The OCCT showed better efficacy than fasting plasma TMAO to identify TMAO producer phenotype. The omnivores exhibited a 10-fold higher OR to be high TMAO producer than vegetarians. The TMAO-associated taxa found by OCCT in this study were consistent with previous animal studies. The TMAO producer phenotypes were also reproduced in humanised gnotobiotic mice model. Besides, we found the faecal CntA gene was not associated with TMAO production; therefore, other key relevant microbial genes might be involved. Finally, we demonstrated the urine TMAO exhibited a strong positive correlation with plasma TMAO (r=0.92, p<0.0001) and improved the feasibility of OCCT. CONCLUSION: The OCCT can be used to identify TMAO-producer phenotype of gut microbiota and may serve as a personal guidance in CVD prevention and treatment. TRIAL REGISTRATION NUMBER: NCT02838732; Results.

Population Density and Risk of Inflammatory Bowel Disease: A Prospective Population-Based Study in 13 Countries or Regions in Asia-Pacific.

INTRODUCTION: Living in an urban environment may increase the risk of developing inflammatory bowel disease (IBD). It is unclear if this observation is seen globally. We conducted a population-based study to assess the relationship between urbanization and incidence of IBD in the Asia-Pacific region. METHODS: Newly diagnosed IBD cases between 2011 and 2013 from 13 countries or regions in Asia-Pacific were included. Incidence was calculated with 95% confidence interval (CI) and pooled using random-effects model. Meta-regression analysis was used to assess incidence rates and their association with population density, latitude, and longitude. RESULTS: We identified 1175 ulcerative colitis (UC), 656 Crohn's disease (CD), and 37 IBD undetermined (IBD-U). Mean annual IBD incidence per 100 000 was 1.50 (95% CI: 1.43-1.57). India (9.31; 95% CI: 8.38-10.31) and China (3.64; 95% CI, 2.97-4.42) had the highest IBD incidence in Asia. Incidence of overall IBD (incidence rate ratio [IRR]: 2.19; 95% CI: 1.01-4.76]) and CD (IRR: 3.28; 95% CI: 1.83-9.12) was higher across 19 areas of Asia with a higher population density. In China, incidence of IBD (IRR: 2.37; 95% CI: 1.10-5.16) and UC (IRR: 2.63; 95% CI: 1.2-5.8) was positively associated with gross domestic product. A south-to-north disease gradient (IRR: 0.94; 95% CI: 0.91-0.98) was observed for IBD incidence and a west-to-east gradient (IRR: 1.14; 95% CI: 1.05-1.24) was observed for CD incidence in China. This study received IRB approval. CONCLUSIONS: Regions in Asia with a high population density had a higher CD and UC incidence. Coastal areas within China had higher IBD incidence. With increasing urbanization and a shift from rural areas to cities, disease incidence may continue to climb in Asia.

Using a deep learning system in endoscopy for screening of early esophageal squamous cell carcinoma (with video).

BACKGROUND AND AIMS: Few artificial intelligence-based technologies have been developed to improve the efficiency of screening for esophageal squamous cell carcinoma (ESCC). Here, we developed and validated a novel system of computer-aided detection (CAD) using a deep neural network (DNN) to localize and identify early ESCC under conventional endoscopic white-light imaging. METHODS: We collected 2428 (1332 abnormal, 1096 normal) esophagoscopic images from 746 patients to set up a novel DNN-CAD system in 2 centers and prepared a validation dataset containing 187 images from 52 patients. Sixteen endoscopists (senior, mid-level, and junior) were asked to review the images of the validation set. The diagnostic results, including accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were compared between the DNN-CAD system and endoscopists. RESULTS: The receiver operating characteristic curve for DNN-CAD showed that the area under the curve was >96%. For the validation dataset, DNN-CAD had a sensitivity, specificity, accuracy, PPV, and NPV of 97.8%, 85.4%, 91.4%, 86.4%, and 97.6%, respectively. The senior group achieved an average diagnostic accuracy of 88.8%, whereas the junior group had a lower value of 77.2%. After referring to the results of DNN-CAD, the average diagnostic ability of the endoscopists improved, especially in terms of sensitivity (74.2% vs 89.2%), accuracy (81.7% vs 91.1%), and NPV (79.3% vs 90.4%). CONCLUSIONS: The novel DNN-CAD system used for screening of early ESCC has high accuracy and sensitivity, and can help endoscopists to detect lesions previously ignored under white-light imaging.

Variations in Gut Microbiota of Siberian Flying Squirrels Correspond to Seasonal Phenological Changes in Their Hokkaido Subarctic Forest Ecosystem.

Gut microbial communities of animals are influenced by diet and seasonal weather changes. Since foraging strategies of wild animals are affected by phenological changes, gut microbial communities would differ among seasons. However, interactions of plant-animal-microbiota with seasonal changes have not been well characterized. Here, we surveyed gut microbial diversity of Siberian flying squirrels (Pteromys volans orii) from a natural forest in Hokkaido during spring and summer of 2013 and 2014. Additionally, we compared microbial diversity to temperature changes and normalized difference vegetation index (NDVI). Changes in both seasonal temperature and phenology were significantly associated with alterations in gut microbiota. There were two clusters of OTUs, below and above 20 °C that were significantly correlated with low and high temperatures, respectively. Low-temperature cluster OTUs belonged to various phyla, whereas the high-temperature cluster was only constituted by Firmicutes. In conclusion, gut microbiota of Siberian flying squirrels varied with environmental changes on an ecological scale.

Computed Diffusion Weighted Imaging of the Liver Using Extrapolation Technique in Patients Who Underwent Liver Transplantation With Hepatocellular Carcinomas: Initial Experience and Feasibility Study.

OBJECTIVE: This study aimed to evaluate the feasibility and image quality of computed diffusion weighted imaging (DWI) of the liver in patients with hepatocellular carcinoma (HCC). METHODS: Twenty-four patients who underwent liver transplantation with HCC were enrolled. Computed DWI was synthesized for b-values of 800 (cDWI800) and 1200 s/mm (cDWI1200) using directly acquired DWI with b-values of 0, 50, and 500 s/mm. Signal intensity of HCC, background liver, and contrast-to-noise ratio were evaluated for directly acquired DWI of 800 s/mm (dDWI800), cDWI800, and cDWI1200. Two radiologists evaluated the image quality for contrast between HCC and liver, suppression of background signal and T2 shine-through, and overall image quality. RESULTS: cDWI1200 showed the lowest contrast-to-noise ratio. Qualitative scores for background suppression and decreased T2 shine-through were highest for cDWI1200. However, contrast between HCC and background liver was worst in cDWI1200. CONCLUSIONS: In computed DWI of high b-values, contrast between HCC and background liver was very low.

Early Course of Inflammatory Bowel Disease in a Population-Based Inception Cohort Study From 8 Countries in Asia and Australia.

BACKGROUND & AIMS: The incidence of inflammatory bowel disease (IBD) is increasing in Asia, but little is known about disease progression in this region. The Asia-Pacific Crohn's and Colitis Epidemiology Study was initiated in 2011, enrolling subjects from 8 countries in Asia (China, Hong Kong, Indonesia, Sri Lanka, Macau, Malaysia, Singapore, and Thailand) and Australia. We present data from this ongoing study. METHODS: We collected data on 413 patients diagnosed with IBD (222 with ulcerative colitis [UC], 181 with Crohn's disease [CD], 10 with IBD unclassified; median age, 37 y) from 2011 through 2013. We analyzed the disease course and severity and mortality. Risks for medical and surgical therapies were assessed using Kaplan-Meier analysis. RESULTS: The cumulative probability that CD would change from inflammatory to stricturing or penetrating disease was 19.6%. The cumulative probabilities for use of immunosuppressants or anti-tumor necrosis factor agents were 58.9% and 12.0% for patients with CD, and 12.7% and 0.9% for patients with UC, respectively. Perianal CD was associated with an increased risk of anti-tumor necrosis factor therapy within 1 year of its diagnosis (hazard ratio, 2.97; 95% confidence interval, 1.09-8.09). The cumulative probabilities for surgery 1 year after diagnosis were 9.1% for patients with CD and 0.9% for patients with UC. Patients with CD and penetrating disease had a 7-fold increase for risk of surgery, compared with patients with inflammatory disease (hazard ratio, 7.67; 95% confidence interval, 3.93-14.96). The overall mortality for patients with IBD was 0.7%. CONCLUSIONS: In a prospective population-based study, we found that the early course of disease in patients with IBD in Asia was comparable with that of the West. Patients with CD frequently progress to complicated disease and have accelerated use of immunosuppressants. Few patients with early stage UC undergo surgery in Asia. Increasing our understanding of IBD progression in different populations can help optimize therapy and improve outcomes.

Morphological and dynamic contrast enhanced MR imaging features for the differentiation of chordoma and giant cell tumors in the Axial Skeleton.

PURPOSE: To characterize the morphological and dynamic-contrast-enhanced (DCE) MRI features of chordoma and giant cell tumor (GCT) of bone occurring in the axial skeleton. MATERIALS AND METHODS: A total of 13 patients with chordoma and 26 patients with GCT who received conventional T1, T2, and DCE-MRI on 3 Tesla MR scanners were retrospectively identified and analyzed. Two radiologists evaluated morphological features independently, including the lesion location, expansile bone changes, vertebral compression, presence of paraspinal soft tissue mass, fibrous septa, and the signal intensity on T1WI and T2WI. The inter-observer agreement was evaluated by kappa test. The DCE kinetics was measured to obtain the initial area under curve (IAUC) and the wash-out slope; also the two-compartmental pharmacokinetic model was applied to obtain Ktrans and kep . The diagnostic accuracy was evaluated by CHAID decision tree and ROC analysis. RESULTS: Chordomas were more likely to show soft tissue mass than GCTs (13/13 = 100% versus 15/26 = 58%; P = 0.007), as well as fibrous septa (9/13 = 69% versus 0; P < 0.001). In decision tree analysis, presence of fibrous septa and lesion location yield 31/39 = 79% accuracy. The DCE-MRI pharmacokinetic parameters Ktrans and kep of GCTs were significantly higher than those of chordomas, 0.13 ± 0.65 versus 0.06 ± 0.04 (1/min) for Ktrans , 0.62 ± 0.22 versus 0.17 ± 0.12 (1/min) for kep , P < 0.001 for both. If using kep = 0.43/min as the cut-off value, it achieved 100% sensitivity and 92% specificity to differentiate chordoma from GCT, with an overall accuracy of 37/39 = 95%. The IAUC was highly correlated with Ktrans (r = 0.94), and the slope was highly correlated with kep (r = 0.95). CONCLUSION: Several morphological features were significantly different between chordoma and GCT, but their diagnostic performance was inferior to that of DCE-MRI. LEVEL OF EVIDENCE: 4 J. Magn. Reson. Imaging 2017;45:1068-1075.

Advanced Imaging Techniques of the Wrist.

OBJECTIVE: This article covers the technical aspects and clinical applications of recent advancements in wrist MRI techniques, including T2 and T1rho mapping, compressed sensing, and isotropic 3D imaging using driven equilibrium sequences, variable-flip-angle refocusing pulse sequences, and parallel imaging. The clinical applications of these techniques include the quantitative analysis of cartilage and triangular fibrocartilaginous complex (TFCC) degeneration, faster scanning times, and improved resolution of complex wrist anatomy, allowing differentiation of degenerative from traumatic TFCC tears and improved morphologic evaluation of chondromalacia. CONCLUSION: MRI of the wrist and of the musculoskeletal system has had multiple novel and exciting advancements in recent years. Several of these advancements, such as parallel imaging, are already in clinical use, and others will be entering the clinical realm in the near future. An understanding of these techniques allows one to use their advantages to greatest effect.

T1rho and T2 relaxation times of the normal adult knee meniscus at 3T: analysis of zonal differences.

BACKGROUND: Prior studies describe histological and immunohistochemical differences in collagen and proteoglycan content in different meniscal zones. The aim of this study is to evaluate horizontal and vertical zonal differentiation of T1rho and T2 relaxation times of the entire meniscus from volunteers without symptom and imaging abnormality. METHODS: Twenty volunteers age between 19 and 38 who have no knee-related clinical symptoms, and no history of prior knee surgeries were enrolled in this study. Two T1rho mapping (b-FFE T1rho and SPGR T1rho) and T2 mapping images were acquired with a 3.0-T MR scanner. Each meniscus was divided manually into superficial and deep zones for horizontal zonal analysis. The anterior and posterior horns of each meniscus were divided manually into white, red-white and red zones for vertical zonal analysis. Zonal differences of average relaxation times among each zone, and both inter- and intra-observer reproducibility were statistically analyzed. RESULTS: In horizontal zonal analysis, T1rho relaxation times of the superficial zone tended to be higher than those of the deep zone, and this difference was statistically significant in the medial meniscal segments (84.3 ms vs 76.0 ms on b-FFE, p < 0.0001 and 96.5 ms vs 91.7 ms on SPGR, p = 0.004). In vertical zonal analysis, T1rho relaxation times of the white zone tended to be higher than those of the red zone, and this difference was statistically significant in the posterior horn of the medical meniscus (88.4 ms vs 77.1 ms on b-FFE, p < 0.001 and 104.9 ms vs 96.8 ms on SPGR, p =0.001). Likewise, T2 relaxation times of the superficial zone were significantly higher than those of the deep zone (80.4 ms vs 74.4 ms in the medial meniscus, p = 0.011). T2 relaxation times of the white zone were significantly higher than those of the red zone in the medial meniscus posterior horn (96.8 ms vs 84.3 ms, p < 0.001) and lateral meniscus anterior horn (104.6 ms vs 84.2 ms, p < 0.0001). Inter-class and intra-class correlation coefficients were excellent (>0.74) or good (0.60-0.74) in all meniscal segments on both horizontal and vertical zonal analysis, except for inter-class correlation coefficients of the lateral meniscus on SPGR. Compared with SPGR T1rho images, b-FFE T1rho images demonstrated more significant zonal differentiation with higher inter- and intra-observer reproducibility. CONCLUSIONS: There are zonal differences in T1rho and T2 relaxation times of the normal meniscus.

An invertebrate Warburg effect: a shrimp virus achieves successful replication by altering the host metabolome via the PI3K-Akt-mTOR pathway.

In this study, we used a systems biology approach to investigate changes in the proteome and metabolome of shrimp hemocytes infected by the invertebrate virus WSSV (white spot syndrome virus) at the viral genome replication stage (12 hpi) and the late stage (24 hpi). At 12 hpi, but not at 24 hpi, there was significant up-regulation of the markers of several metabolic pathways associated with the vertebrate Warburg effect (or aerobic glycolysis), including glycolysis, the pentose phosphate pathway, nucleotide biosynthesis, glutaminolysis and amino acid biosynthesis. We show that the PI3K-Akt-mTOR pathway was of central importance in triggering this WSSV-induced Warburg effect. Although dsRNA silencing of the mTORC1 activator Rheb had only a relatively minor impact on WSSV replication, in vivo chemical inhibition of Akt, mTORC1 and mTORC2 suppressed the WSSV-induced Warburg effect and reduced both WSSV gene expression and viral genome replication. When the Warburg effect was suppressed by pretreatment with the mTOR inhibitor Torin 1, even the subsequent up-regulation of the TCA cycle was insufficient to satisfy the virus's requirements for energy and macromolecular precursors. The WSSV-induced Warburg effect therefore appears to be essential for successful viral replication.

US-localized diffuse optical tomography in breast cancer: comparison with pharmacokinetic parameters of DCE-MRI and with pathologic biomarkers.

BACKGROUND: To correlate parameters of Ultrasonography-guided Diffuse optical tomography (US-DOT) with pharmacokinetic features of Dynamic contrast-enhanced (DCE)-MRI and pathologic markers of breast cancer. METHODS: Our institutional review board approved this retrospective study and waived the requirement for informed consent. Thirty seven breast cancer patients received US-DOT and DCE-MRI with less than two weeks in between imaging sessions. The maximal total hemoglobin concentration (THC) measured by US-DOT was correlated with DCE-MRI pharmacokinetic parameters, which included K(trans), k ep and signal enhancement ratio (SER). These imaging parameters were also correlated with the pathologic biomarkers of breast cancer. RESULTS: The parameters THC and SER showed marginal positive correlation (r = 0.303, p = 0.058). Tumors with high histological grade, negative ER, and higher Ki-67 expression ≥ 20% showed statistically higher THC values compared to their counterparts (p = 0.019, 0.041, and 0.023 respectively). Triple-negative (TN) breast cancers showed statistically higher K(trans) values than non-TN cancers (p = 0.048). CONCLUSION: THC obtained from US-DOT and K(trans) obtained from DCE-MRI were associated with biomarkers indicative of a higher aggressiveness in breast cancer. Although US-DOT and DCE-MRI both measured the vascular properties of breast cancer, parameters from the two imaging modalities showed a weak association presumably due to their different contrast mechanisms and depth sensitivities.

The effects of sequential treatments on hippocampal volumes in malignant glioma patients.

Malignant gliomas (MG) are very aggressive tumors. In an effort to improve the outcome, the patients receive multi-modal therapies such as surgery, radiation and chemotherapy (temozolomide followed in many cases by bevacizumab). The survivors are affected by multiple learning and memory deficits. Greater deterioration over time in hippocampal specific cognitive tasks was shown in patients receiving bevacizumab in addition to radiation and temozolomide for a longer period of time (RTOG 0825). The rate of hippocampal atrophy in patients treated with radiation and temozolomide followed by bevacizumab is not yet determined, and is the goal of the present study. We used the serial MRIs obtained as parts of standard clinical care in patients with MG. Measurements were done using the Medical Image Processing, Analysis and Visualization (MIPAV) software. The hippocampus in the contralateral hemisphere was manually traced and measured, to avoid morphological structure changes induced by the tumor, radiation fields or surgical markers. We determined a longitudinal progression of hippocampal atrophy-with the maximum volume loss (33.26 %) for the patients that were on treatment for 5 years. There was no detectable hippocampal atrophy during the chemo-radiation followed by adjuvant temozolomide. A significant decrease in the absolute hippocampus volume was noted after 6 months of continuous bevacizumab treatment (p < 0.05). The hippocampal volume loss progressed over the next 3 years, and was higher than the one previously reported in Alzheimer disease patients. The hippocampal volume loss is minimal during the 1 month after diagnosis, when the patients receive chemo-radiation and adjuvant temozolomide. However, prolonged treatment including bevacizumab is associated with a significant rate of hippocampal volume loss.

T1rho mapping of entire femoral cartilage using depth- and angle-dependent analysis.

OBJECTIVES: To create and evaluate normalized T1rho profiles of the entire femoral cartilage in healthy subjects with three-dimensional (3D) angle- and depth-dependent analysis. METHODS: T1rho images of the knee from 20 healthy volunteers were acquired on a 3.0-T unit. Cartilage segmentation of the entire femur was performed slice-by-slice by a board-certified radiologist. The T1rho depth/angle-dependent profile was investigated by partitioning cartilage into superficial and deep layers, and angular segmentation in increments of 4° over the length of segmented cartilage. Average T1rho values were calculated with normalized T1rho profiles. Surface maps and 3D graphs were created. RESULTS: T1rho profiles have regional and depth variations, with no significant magic angle effect. Average T1rho values in the superficial layer of the femoral cartilage were higher than those in the deep layer in most locations (p < 0.05). T1rho values in the deep layer of the weight-bearing portions of the medial and lateral condyles were lower than those of the corresponding non-weight-bearing portions (p < 0.05). Surface maps and 3D graphs demonstrated that cartilage T1rho values were not homogeneous over the entire femur. CONCLUSIONS: Normalized T1rho profiles from the entire femoral cartilage will be useful for diagnosing local or early T1rho abnormalities and osteoarthritis in clinical applications. KEY POINTS: • T1rho profiles are not homogeneous over the entire femur. • There is angle- and depth-dependent variation in T1rho profiles. • There is no influence of magic angle effect on T1rho profiles. • Maps/graphs might be useful if several difficulties are solved.