Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomic Model for Discrimination of Pathological Subtypes of Craniopharyngioma.

BACKGROUND: Preoperative, noninvasive discrimination of the craniopharyngioma subtypes is important because it influences the treatment strategy. PURPOSE: To develop a radiomic model based on multiparametric magnetic resonance imaging for noninvasive discrimination of pathological subtypes of craniopharyngioma. STUDY TYPE: Retrospective. POPULATION: A total of 164 patients from two medical centers were enrolled in this study. Patients from the first medical center were divided into a training cohort (N = 99) and an internal validation cohort (N = 33). Patients from the second medical center were used as the external independent validation cohort (N = 32). FIELD STRENGTH/SEQUENCE: Axial T1 -weighted (T1 -w), T2 -weighted (T2 -w), contrast-enhanced T1 -weighted (CET1 -w) on 3.0 T or 1.5 T magnetic resonance scanners. ASSESSMENT: Pathological subtypes (squamous papillary craniopharyngioma and adamantinomatous craniopharyngioma) were confirmed by surgery and hematoxylin and eosin staining. Optimal radiomic feature selection was performed by SelectKBest, the least absolute shrinkage and selection operator algorithm, and support vector machine (SVM) with a recursive feature elimination algorithm. Models based on each sequence or combinations of sequences were built using a SVM classifier and used to differentiate pathological subtypes of craniopharyngioma in the training cohort, internal validation, and external validation cohorts. STATISTICAL TESTS: The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of the radiomic models. RESULTS: Seven texture features, three from T1 -w, two from T2 -w, and two from CET1 -w, were selected and used to construct the radiomic model. The AUC values of the radiomic model were 0.899, 0.810, and 0.920 in the training cohort, internal and external validation cohorts, respectively. The AUC values of the clinicoradiological model were 0.677, 0.655, and 0.671 in the training cohort, internal and external validation cohorts, respectively. DATA CONCLUSION: The model based on radiomic features from T1 -w, T2 -w, and CET1 -w has a high discriminatory ability for pathological subtypes of craniopharyngioma. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: 2.

A Compact Convolutional Neural Network for Surface Defect Inspection.

The advent of convolutional neural networks (CNNs) has accelerated the progress of computer vision from many aspects. However, the majority of the existing CNNs heavily rely on expensive GPUs (graphics processing units). to support large computations. Therefore, CNNs have not been widely used to inspect surface defects in the manufacturing field yet. In this paper, we develop a compact CNN-based model that not only achieves high performance on tiny defect inspection but can be run on low-frequency CPUs (central processing units). Our model consists of a light-weight (LW) bottleneck and a decoder. By a pyramid of lightweight kernels, the LW bottleneck provides rich features with less computational cost. The decoder is also built in a lightweight way, which consists of an atrous spatial pyramid pooling (ASPP) and depthwise separable convolution layers. These lightweight designs reduce the redundant weights and computation greatly. We train our models on groups of surface datasets. The model can successfully classify/segment surface defects with an Intel i3-4010U CPU within 30 ms. Our model obtains similar accuracy with MobileNetV2 while only has less than its 1/3 FLOPs (floating-point operations per second) and 1/8 weights. Our experiments indicate CNNs can be compact and hardware-friendly for future applications in the automated surface inspection (ASI).

PL-VIO: Tightly-Coupled Monocular Visual-Inertial Odometry Using Point and Line Features.

To address the problem of estimating camera trajectory and to build a structural three-dimensional (3D) map based on inertial measurements and visual observations, this paper proposes point-line visual-inertial odometry (PL-VIO), a tightly-coupled monocular visual-inertial odometry system exploiting both point and line features. Compared with point features, lines provide significantly more geometrical structure information on the environment. To obtain both computation simplicity and representational compactness of a 3D spatial line, Plücker coordinates and orthonormal representation for the line are employed. To tightly and efficiently fuse the information from inertial measurement units (IMUs) and visual sensors, we optimize the states by minimizing a cost function which combines the pre-integrated IMU error term together with the point and line re-projection error terms in a sliding window optimization framework. The experiments evaluated on public datasets demonstrate that the PL-VIO method that combines point and line features outperforms several state-of-the-art VIO systems which use point features only.

[Anti-breast cancer mechanism of flavonoids].

Flavonoids are a kind of ubiquitous natural products in plants and essential active ingredients of many medicinal plants. They have the characteristics of broad biological activity, high efficiency and low toxicity, with good prevention and cure effects on various types of tumors. Breast cancer is the commonest cancer disease and the main cause of cancer death in women worldwide. In China, the morbidity and mortality are still on the rise. Flavonoids can inhibit the occurrence and development of breast cancer in various aspects. The main mechanisms include the inhibition of aerobic glycolysis, the promotion of apoptosis, the retardation of cell cycle, the suppression of invasion and migration, the induction of DNA damage, and the inhibition of aromatase and microtubule production. Due to its chemical structure similar to estrogen, flavonoids have unique advantages in the prevention and treatment of breast cancer. In this paper, studies on anti-breast cancer of flavonoids in recent years were reviewed, which could provide reference for further studies.

Study on angle of immediate loading of immediate implant placement.

OBJECTIVE: To investigate the clinical immediate load at an angle after immediate placement of the implant. METHODS: Select 4 adult dogs; through establishing the angle loading animal experiment model, perform lateral loading on 32 implants respectively at vertical and 0°, 10°, and 20°, with which as a basis for grouping, determine the osseointegration index and new bone growth rate; and observe the peri-implant bone remodeling conditions. RESULTS: The 20° group is found with the most obvious bone absorption, and compared with other groups, its osseointegration index and new bone growth rate are statistically significant (P < 0.01); bone remodeling under 0° load stress is the best, with the formation of new bone and the highest bone contact ratio, which is the most reasonable under this the stress distribution compared with other angles. CONCLUSIONS: The implant stress distribution at 0° against the occlusal force direction is closer to physiologic optimum stress on the implant bone interface, and it is permitted for the long axis of the immediately implanted and immediately loaded implant to be tilted within about 10° against the load angle.

Analysis of Tim-3 as a therapeutic target in prostate cancer.

T cell immunoglobulin domain and mucin domain-containing molecule 3 (Tim-3) is a newly discovered immunomodulatory, which plays an important role in immunity regulation. Recent evidence suggests that Tim-3 is differentially regulated in a variety of tumors and has a potential as a therapeutic target. The aim of this study was to investigate the effect of Tim-3 on the development of prostate cancer (PCa). Tim-3 expressing on peripheral CD4+ T and CD8+ T cells was analyzed by flow cytometry. The relationships between Tim-3 expression and clinicopathological features were analyzed. Immunohistochemical expression of Tim-3 was examined in our large numbers of paraffin-fixed prostate tissues. Flow cytometry revealed that expression of Tim-3 was significantly increased on both CD4+ and CD8+ T cells in PCa patients than that in benign prostate hyperplasia (BPH) patients. Also, the level of Tim-3 on CD4+ T cells was positively correlated with CD8+ T cells in patients. Further analyses revealed that the levels of Tim-3 on CD4+ T cells and CD8+ T cells exhibited different expression patterns in terms of localization depending on pathological category of PCa and metastasis. Immunohistochemical analysis revealed that positive staining of Tim-3 in PCa but little or no staining of Tim-3 was observed in BPH epithelium. Tim-3 may affect the development and progression of PCa, which may provide knowledge for using Tim-3 as a novel therapy for effective PCa management.

[Study on relationship between endogenous androgens and insulin resistance at the different stages of postmenopause].

OBJECTIVE: To investigate the relationship between insulin resistance and endogenous androgens at early and late phase of postmenopause. METHODS: A total of 105 women with early postmenopause ( ≤ 5 years since menopause) and 107 women with late postmenopause ( ≥ 10 years since menopause) were enrolled in this study.In the mean time, those women were classified into normal weight[body mass index (BMI), BMI <24 kg/m(2)] group and overweight (BMI ≥ 24 kg/m(2)) group.Sex hormone-binding globulin (SHBG), testosterone (T) , dehydroepiandrosterone-sulfate (DHEA-S) , fasting blood glucose(FBG), fasting insulin (FINS) levels were measured and then calculated free androgen index (FAI) and homeostatic model assessment of insulin resistance (HOMA-IR) . The relationship between sex hormones and insulin resistance was analyzed by partial correlation and multiple linear regression analyses. RESULTS: Compared to early postmenopausal women, late postmenopausal women had higher FINS [(7.9 ± 6.6) mU/L versus (6.6 ± 4.0) mU/L] and HOMA-IR(2.1 ± 1.9 versus 1.7 ± 1.1), but they had lower DHEA-S[(0.9 ± 0.5) mg/L versus (1.1 ± 0.5) mg/L, all P < 0.05) ]. Both in early postmenopausal and late postmenopausal groups, overweight women had higher HOMA-IR (early group, 2.2 ± 1.0 versus 1.2 ± 0.9;late group, 2.8 ± 2.6 versus 1.6 ± 1.1) and FINS early group[(6.9 ± 2.9) mU/L versus (4.6 ± 2.0) mU/L];late group[(10.2 ± 9.3) mU/L versus (6.4 ± 3.6) mU/L] than those at women with normal weight group (all P < 0.05) .In early postmenopausal group, overweight women had lower SHBG[ (52 ± 37) nmol/L versus (71 ± 37) nmol/L] and higher FAI (2.5 ± 2.1) versus (1.3 ± 1.1) than those at normal weight women group (all P < 0.05) .In late postmenopausal group, overweight women had higher DHEA-S (1.0 ± 0.5) mg/L versus (0.8 ± 0.4) mg/L (P < 0.05) . The analyses suggested that in early postmenopausal group, SHBG was correlated negatively with FINS and HOMA-IR (ß = -0.386, P < 0.05;ß = -0.553, P < 0.05) , DHEA-S was correlated positively with FBG (ß = 0.348, P < 0.05) in early postmenopausal group.FAI was correlated positively with FBG in late postmenopausal group (ß = 0.505, P < 0.05) . CONCLUSIONS: The increased androgenic activities are associated with insulin resistance after of menopause. These correlations are different at different stages of postmenopause, which SHBG levels correlate with high risk of insulin resistance and DHEA-S levels correlates with high blood glucose levels at early postmenopause and FAI correlates with high blood glucose levels at late postmenopause.

In Situ Buildup of Zinc Anode Protection Films with Natural Protein Additives for High-Performance Zinc Battery Cycling.

The uncontrolled growth of dendrites and serious side reactions, such as hydrogen evolution and corrosion, significantly hinder the industrial application and development of aqueous zinc-ion batteries (ZIBs). This article presents ovalbumin (OVA) as a multifunctional electrolyte additive for aqueous ZIBs. Experimental characterizations and theoretical calculations reveal that the OVA additive can replace the solvated sheath of recombinant hydrated Zn2+ through the coordination water, preferentially adsorb on the surface of the Zn anode, and construct a high-quality self-healing protective film. Notably, the OVA-based protective film with strong Zn2+ affinity will promote uniform Zn deposition and inhibit side reactions. As a result, Zn||Zn symmetrical batteries in ZnSO4 electrolytes containing OVA achieve a cycle life exceeding 2200 h. Zn||Cu batteries and Zn||MnO2 (2 A g-1) full batteries show excellent cycling stability for 2500 cycles, demonstrating promising application prospects. This study provides insights into utilizing natural protein molecules to modulate the kinetics of Zn2+ diffusion and enhance the stability of the anode interface.

Exosomes: The role in mammalian reproductive regulation and pregnancy-related diseases.

Exosomes are a kind of extracellular vesicles that are produced and secreted by different mammalian cells. They serve as cargo proteins and can transfer different kinds of biomolecules, including proteins, lipids, and nucleic acids, which consequently act on target cells to exert different biological effects. Recent years have witnessed a significant increase in the number of studies on exosomes due to the potential effects of exosomes in the diagnosis and treatment of cancers, neurodegenerative diseases, and immune disorders. Previous studies have demonstrated that exosomal contents, especially miRNAs, are implicated in numerous physiological processes such as reproduction, and are crucial regulators of mammalian reproduction and pregnancy-related diseases. Here, we describe the origin, composition, and intercellular communication of exosomes, and discuss their functions in follicular development, early embryonic development, embryonic implantation, male reproduction and development of pregnancy-related diseases in humans and animals. We believe this study will provide a foundation for revealing the mechanism of exosomes in regulating mammalian reproduction, and providing new approaches and ideas for the diagnosis and treatment of pregnancy-related diseases.

A personalized prediction model for urinary tract infections in type 2 diabetes mellitus using machine learning.

Patients with type 2 diabetes mellitus (T2DM) are at higher risk for urinary tract infections (UTIs), which greatly impacts their quality of life. Developing a risk prediction model to identify high-risk patients for UTIs in those with T2DM and assisting clinical decision-making can help reduce the incidence of UTIs in T2DM patients. To construct the predictive model, potential relevant variables were first selected from the reference literature, and then data was extracted from the Hospital Information System (HIS) of the Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital for analysis. The data set was split into a training set and a test set in an 8:2 ratio. To handle the data and establish risk warning models, four imputation methods, four balancing methods, three feature screening methods, and eighteen machine learning algorithms were employed. A 10-fold cross-validation technique was applied to internally validate the training set, while the bootstrap method was used for external validation in the test set. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to evaluate the performance of the models. The contributions of features were interpreted using the SHapley Additive ExPlanation (SHAP) approach. And a web-based prediction platform for UTIs in T2DM was constructed by Flask framework. Finally, 106 variables were identified for analysis from a total of 119 literature sources, and 1340 patients were included in the study. After comprehensive data preprocessing, a total of 48 datasets were generated, and 864 risk warning models were constructed based on various balancing methods, feature selection techniques, and a range of machine learning algorithms. The receiver operating characteristic (ROC) curves were used to assess the performances of these models, and the best model achieved an impressive AUC of 0.9789 upon external validation. Notably, the most critical factors contributing to UTIs in T2DM patients were found to be UTIs-related inflammatory markers, medication use, mainly SGLT2 inhibitors, severity of comorbidities, blood routine indicators, as well as other factors such as length of hospital stay and estimated glomerular filtration rate (eGFR). Furthermore, the SHAP method was utilized to interpret the contribution of each feature to the model. And based on the optimal predictive model a user-friendly prediction platform for UTIs in T2DM was built to assist clinicians in making clinical decisions. The machine learning model-based prediction system developed in this study exhibited favorable predictive ability and promising clinical utility. The web-based prediction platform, combined with the professional judgment of clinicians, can assist to make better clinical decisions.

[Investigation of the Performance of Organic Contaminant Degradation by Fe2+/PDS Under Environmentally Relevant pH Conditions].

Peroxydisulfate (PDS) activation by Fe2+ has proven to be a promising method to abate emerging organic contaminants by generating reactive oxidation species. Nevertheless, this process may only achieve good decontamination performance under acidic conditions, which has markedly limited its application in real practice. To address this issue, we comprehensively investigated the performance of the Fe2+/PDS process toward some probe contaminants at different pH levels and explored the potential change in reactive oxidative species and the influence of oxygen. Both SO4-· and Fe(Ⅳ) were identified to be involved in the Fe2+/PDS process, and the types of these oxidative species did not change with varying pH values. Although dissolved oxygen could compete with PDS for Fe2+, especially at high pH values, this competition process was not the major reason for the declined performance of the Fe2+/PDS process, since 37.6%-100% of PDS could also be activated with the presence of oxygen. Instead, the overdosing of Fe2+could greatly inhibit carbamazepine removal, indicating that the nonproductive consumption of reactive oxidants by Fe2+should account for the declined performance of Fe2+/PDS under environmentally relevant pH conditions. Accordingly, the feasibility of applying zero-valent iron and sulfidated zero-valent iron was further evaluated, and the formation of corrosion products was characterized using X-ray absorption fine structure spectroscopy. All these findings will improve our understanding about the Fe2+/PDS process and thus facilitate its application.

Conventional MRI Features of Central Nervous System Embryonal Tumor, Not Otherwise Specified in Adults: Comparison with Glioblastoma.

RATIONALE AND OBJECTIVES: The purpose of this study was to explore conventional MRI features that can accurately differentiate central nervous system embryonal tumor, not otherwise specified (CNS ETNOS) from glioblastoma (GBM) in adults. MATERIALS AND METHODS: Preoperative conventional MRI images of 30 CNS ETNOS and 98 GBMs were analyzed by neuroradiologists retrospectively to identify valuable MRI features. Five blinded neuroradiologists independently reviewed all these MRI images, and scored MRI features on a five-point scale. Kendall's coefficient of concordance was used to measure inter-rater agreement. Diagnostic value was assessed by the area under the curve (AUC) of receiver operating curve, and sensitivity and specificity were also calculated. RESULTS: Seven MRI features, including isointensity on T1WI, T2WI, and FLAIR, ill-defined margin, severe peritumoral edema, ring enhancement, and broad-based attachment sign, were helpful for the differential diagnosis of these two entities. Among these features, ring enhancement showed the highest inter-rater concordance (0.80). Ring enhancement showed the highest AUC value (0.79), followed by severe peritumoral edema (0.67). The combination of seven features showed the highest AUC value (0.86), followed by that of three features (ill-defined margin, severe peritumoral edema, and ring enhancement) (0.83). CONCLUSION: Enhancement pattern, peritumoral edema, and margin are valuable for the discrimination between CNS ETNOS and GBM in adults.

Esthesioneuroblastoma methods of intracranial extension: CT and MR imaging findings.

INTRODUCTION: Esthesioneuroblastoma (ENB) is an aggressive neuroectodermal malignancy in the upper nasal cavity with local infiltration and lymphatic or hematogenous metastasis. The purpose of this paper is to document three types of direct intracranial extensions by ENB using computed tomography (CT) and magnetic resonance imaging (MRI). METHODS: Eleven patients with pathologically confirmed ENB were admitted in our hospital between December 2002 and December 2008. Their magnetic resonance (MR; n = 10) and CT (n = 8) images were retrospectively reviewed, and particular attention was paid to tumor location and extension, enhancement pattern, cervical lymph node metastasis, and Kadish stage. RESULTS: The majority of patients were male (8/11) with Kadish stage C tumor (10/11). Three types of direct intracranial extension by ENBs were put forward according to their MR and CT findings. The primary tumors were well-defined soft-tissue masses centered in the roof of the nasal cavity eroding into the paranasal sinuses (11/11), the contralateral nasal cavity (4/11), the cranial cavity (5/11), and the fossa orbitalis (3/11). The tumor parenchyma were hypointensity on T1-weighted images, heterogeneous hyperintensity on T2-weighted images, and isodensity or slight hyperdensity on CT images with scattered necroses (4/11) and marginal cysts(4/11). Their enhancements were significant and inhomogeneous. Cervical lymph nodes metastases were observed in four patients (4/11), but no pathologically proved distant metastasis was observed. CONCLUSION: Three types of direct intracranial extensions by ENB can be found on CT and MRI: cranio-orbital-nasal-communicating ENB, cranio-nasal-communicating ENB, and orbital-nasal-communicating ENB.

Upregulation of microRNA-205 is a potential biomarker for intracranial aneurysms.

Inhibition of microRNA-205 is considered to be a therapeutic target for abdominal aortic aneurysm in animal model. Hepatocyte growth factor also plays pivotal roles in the pathogenesis of intracranial aneurysms, and its expression can be regulated by different miRNAs in different processes. We investigated the involvement of microRNA-205 in intracranial aneurysms and explored is potential interaction with hepatocyte growth factor. We found that blood levels of microRNA-205 were significantly higher in patients with intracranial aneurysms than in healthy controls. High blood levels of microRNA-205 showed diagnostic values for intracranial aneurysms. MicroRNA-205 and hepatocyte growth factor were negatively correlated in patients with intracranial aneurysms. MicroRNA-205 overexpression inhibited hepatocyte growth factor expression and reduced cell viability. Therefore, microRNA-205 may participate in intracranial aneurysms and may serve as a diagnostic marker for this disease.

MiR-16 attenuates ß-amyloid-induced neurotoxicity through targeting ß-site amyloid precursor protein-cleaving enzyme 1 in an Alzheimer's disease cell model.

The aberrant deposition of ß-amyloid (Aß) is closely linked to the pathogenesis and development of Alzheimer's disease (AD). MiR-16 was abnormally downregulated and may be related to the development of AD. However, the functional role and molecular mechanism of miR-16 in AD pathogenesis are still not well elucidated. The expressions of miR-16 and ß-site amyloid precursor protein-cleaving enzyme 1 (BACE1) mRNA and protein levels in AD brain tissues and Aß-treated PC12 cellular AD model were examined by qRT-PCR and western blot analyses. Luciferase reporter assay was used to verify the potential target of miR-16. The cell viability, apoptosis, and caspase-3 activity in PC12 cells were determined by the MTT assay, flow cytometry analysis, and caspase-3 activity assay, respectively. Downregulation of miR-16 and upregulation of BACE1 existed in AD tissues and the cellular AD model of PC12. In addition, miR-16 directly suppressed BACE1 expression. Moreover, miR-16 overexpression and BACE1 knockdown facilitated Aß-induced cell toxicity, apoptosis, and caspase-3 activity in N2a cells, which was partially eliminated by overexpression of BACE1. In contrast, BACE1 knockdown reversed the miR-16 inhibition-mediated inhibitory effect on Aß-induced cell toxicity, apoptosis, and caspase-3 activity in PC12 cells. Collectively, miR-16 attenuated Aß-induced neurotoxicity through targeting BACE1 in an Aß insult cellular AD model, providing a potential therapeutic target for AD treatment.

Sinusoidal Signal Assisted Multivariate Empirical Mode Decomposition for Brain-Computer Interfaces.

A brain-computer interface (BCI) is a communication approach that permits cerebral activity to control computers or external devices. Brain electrical activity recorded with electroencephalography (EEG) is most commonly used for BCI. Noise-assisted multivariate empirical mode decomposition (NA-MEMD) is a data-driven time-frequency analysis method that can be applied to nonlinear and nonstationary EEG signals for BCI data processing. However, because white Gaussian noise occupies a broad range of frequencies, some redundant components are introduced. To solve this leakage problem, in this study, we propose using a sinusoidal assisted signal that occupies the same frequency ranges as the original signals to improve MEMD performance. To verify the effectiveness of the proposed sinusoidal signal assisted MEMD (SA-MEMD) method, we compared the decomposition performances of MEMD, NA-MEMD, and the proposed SA-MEMD using synthetic signals and a real-world BCI dataset. The spectral decomposition results indicate that the proposed SA-MEMD can avoid the generation of redundant components and over decomposition, thus, substantially reduce the mode mixing and misalignment that occurs in MEMD and NA-MEMD. Moreover, using SA-MEMD as a signal preprocessing method instead of MEMD or NA-MEMD can significantly improve BCI classification accuracy and reduce calculation time, which indicates that SA-MEMD is a powerful spectral decomposition method for BCI.

Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy.

BACKGROUND: It is very difficult to predict the early response to NAC only on the basis of change in tumor size. ADC value derived from DWI promises to be a valuable parameter for evaluating the early response to treatment. This study aims to establish the optimal time window of predicting the early response to neoadjuvant chemotherapy (NAC) for different subtypes of locally advanced breast carcinoma using diffusion-weighted imaging (DWI). METHODS: We conducted an institutional review board-approved prospective clinical study of 142 patients with locally advanced breast carcinoma. All patients underwent conventional MR and DW examinations prior to treatment and after first, second, third, fourth, sixth and eighth cycle of NAC. The response to NAC was classified into a pathologic complete response (pCR) and a non-pCR group. DWI parameters were compared between two groups, and the optimal time window for predicting tumor response was established for each chemotherapy regimen. RESULTS: For all the genomic subtypes, there were significant differences in baseline ADC value between pCR and non-pCR group (p < 0.05). The time point prior to treatment could be considered as the ideal time point regardless of genomic subtype. In the group that started with taxanes or anthracyclines, for Luminal A or Luminal B subtype, postT1 could be used as the ideal time point during chemotherapy; for Basal-like or HER2-enriched subtype, postT2 as the ideal time point during chemotherapy. In the group that started with taxanes and anthracyclines, for HER2-enriched, Luminal B or Basal-like subtype, postT1 could be used as the ideal time point during chemotherapy; for Luminal A subtype, postT2 as the ideal time point during chemotherapy. CONCLUSIONS: The time point prior to treatment can be considered as the optimal time point regardless of genomic subtype. For each chemotherapy regimen, the optimal time point during chemotherapy varies across different genomic subtypes.

A remote controlled multimode micro-stimulator for freely moving animals.

This paper presents a remote controlled multimode micro-stimulator based on the chip nRF24E1, which consists mainly of a micro-control unit (MCU) and a radio frequency (RF) transceiver. This micro-stimulator is very compact (18 mmx28 mm two layer printed circuit board) and light (5 g without battery), and can be carried on the back of a small animal to generate electrical stimuli according to the commands sent from a PC 10 meters away. The performance and effectiveness of the micro-stimulator were validated by in vitro experiments on the sciatic nerve (SN) of the frog, where action potentials (APs) as well as artifacts were observed when the SN was stimulated by the micro-stimulator. It was also shown by in vivo behavioral experiments on operant conditioned reflexes in rats which can be trained to obey auditory instruction cues by turning right or left to receive electrical stimulation ('virtual' reward) of the medial forebrain bundle (MFB) in a maze. The correct response for the rats to obey the instructions increased by three times and reached 93.5% in an average of 5 d. This micro-stimulator can not only be used for training small animals to become an 'animal robot', but also provide a new platform for behavioral and neurophysiological experiments.

Development of a spectroscopic Mueller matrix imaging ellipsometer for nanostructure metrology.

In this paper, we describe the development of a spectroscopic Mueller matrix imaging ellipsometer (MMIE), which combines the great power of Mueller matrix ellipsometry with the high spatial resolution of optical microscopy. A dual rotating-compensator configuration is adopted to collect the full 4 × 4 imaging Mueller matrix in a single measurement. The light wavelengths are scanned in the range of 400-700 nm by a monochromator. The instrument has measurement accuracy and precision better than 0.01 for all the Mueller matrix elements in both the whole image and the whole spectral range. The instrument was then applied for the measurement of nanostructures combined with an inverse diffraction problem solving technique. The experiment performed on a photoresist grating sample has demonstrated the great potential of MMIE for accurate grating reconstruction from spectral data collected by a single pixel of the camera and for efficient quantification of geometrical profile of the grating structure over a large area with pixel resolution. It is expected that MMIE will be a powerful tool for nanostructure metrology in future high-volume nanomanufacturing.