Design techniques for low-power wide-band direct digital frequency synthesizers of spread spectrum communication applications

For frequency agile communication systems, fast frequency switching in fine frequency steps with good spectral purity is crucial. Direct Digital Frequency Synthesizer (DDFS) is best suitable for these applications, but is not widely employed in wireless communication systems due to its high power consumption. In general, low power and high integration design are two challenges for mixed signal-circuits and communication systems designers. In this dissertation, new design techniques for DDFS at both architecture and circuit levels are proposed and investigated in order to minimize power consumption and optimize performance. A ROM-less low power wide band DDFS prototype using segmented sine wave Digital-to-Analog Converter (DAC) were designed, fabricated and tested to demonstrate the new design techniques.;First, to further reduce power consumption and save chip area, two new phase interpolation ROM less DDFS architectures are proposed. Segmentation technique is applied to the design of sine wave DAC for DDFS: (1) based upon trigonometric identities, a segmented sine wave DAC with fine nonlinear interpolation DAC\u27s is proposed; (2) based upon first order Taylor series and simple linear interpolation, a segmented sine wave DAC with a fine linear interpolation DAC is proposed. Second, a figure of merit (FM) is defined to find the optimal sine wave DAC segmentations for various resolutions of the segmented sine wave DAC\u27s. The device mismatch effects on the performance of segmented sine wave were also discussed. Third, For DDFS using current-steering segmented sine wave DAC with 12-b phase resolution and 11-b amplitude resolution, a behavioral model in Verilog was used to verify the functionality and validate the architecture. Finally, a DDFS prototype was designed and fabricated in a standard 0.25mum CMOS process. The measured SFDR is better than 50 dB with output frequencies up to 3/8 of the 300 MHz clock frequency. The prototype occupies an active area of 1.4 mm2 and consumes 240 mW for 300 MHz clock frequency. The new techniques reduce the power dissipation and die area substantially when compared to conventional ROM based DDFS designs with on-chip DAC

Separating sexual dimorphism from other morphological variation in a specimen complex of fossil marine reptiles (Reptilia, Ichthyosauriformes, Chaohusaurus).

The Early Triassic Chaohu Fauna from Anhui Province, China, contains the oldest record of Mesozoic marine reptiles, such as Cartorhynchus and Sclerocormus. Most specimens from the fauna belong to the ichthyosauriform Chaohusaurus, more specifically resembling C. chaoxianensis. However, a wide range of morphological variation exists within about 40 skeletons that have been prepared, likely reflecting mixed signals from both sexual and taxonomic differences. We test whether the sexual and taxonomic signals are separable based on quantification, aided by the knowledge of sexual dimorphism in extant marine tetrapods. There are two different suites of dimorphism that divide the specimens differently from each other yet consistently within each suite, resulting in four morphotypes in combination, likely representing two sexes of two taxa. Presumed males have larger organ of prehension sensu Darwin, specifically limbs in the present case, for a given body length. This sexing criterion is supported by the only specimen of a gravid female, which belongs to the morphotype with short limbs. Males also have larger skulls for the trunk length compared to females. This study demonstrates that sexual and taxonomic signals are separable in fossil reptiles, with a sufficient sample size and careful analyses

Hypericin enhances β-lactam antibiotics activity by inhibiting sarA expression in methicillin-resistant Staphylococcus aureus.

Bacteremia is a life-threating syndrome often caused by methicillin-resistant Staphylococcus aureus (MRSA). Thus, there is an urgent need to develop novel approaches to successfully treat this infection. Staphylococcal accessory regulator A (SarA), a global virulence regulator, plays a critical role in pathogenesis and β-lactam antibiotic resistance in Staphylococcus aureus. Hypericin is believed to act as an antibiotic, antidepressant, antiviral and non-specific kinase inhibitor. In the current study, we investigated the impact of hypericin on β-lactam antibiotics susceptibility and mechanism(s) of its activity. We demonstrated that hypericin significantly decreased the minimum inhibitory concentrations of β-lactam antibiotics (e.g., oxacillin, cefazolin and nafcillin), biofilm formation and fibronectin binding in MRSA strain JE2. In addition, hypericin significantly reduced sarA expression, and subsequently decreased mecA, and virulence-related regulators (e.g., agr RNAⅢ) and genes (e.g., fnbA and hla) expression in the studied MRSA strain. Importantly, the in vitro synergistic effect of hypericin with β-lactam antibiotic (e.g., oxacillin) translated into in vivo therapeutic outcome in a murine MRSA bacteremia model. These findings suggest that hypericin plays an important role in abrogation of β-lactam resistance against MRSA through sarA inhibition, and may allow us to repurpose the use of β-lactam antibiotics, which are normally ineffective in the treatment of MRSA infections (e.g., oxacillin)

Copper-related genes predict prognosis and characteristics of breast cancer

BackgroundThe role of copper in cancer treatment is multifaceted, with copper homeostasis-related genes associated with both breast cancer prognosis and chemotherapy resistance. Interestingly, both elimination and overload of copper have been reported to have therapeutic potential in cancer treatment. Despite these findings, the exact relationship between copper homeostasis and cancer development remains unclear, and further investigation is needed to clarify this complexity.MethodsThe pan-cancer gene expression and immune infiltration analysis were performed using the Cancer Genome Atlas Program (TCGA) dataset. The R software packages were employed to analyze the expression and mutation status of breast cancer samples. After constructing a prognosis model to separate breast cancer samples by LASSO-Cox regression, we examined the immune statement, survival status, drug sensitivity and metabolic characteristics of the high- and low-copper related genes scoring groups. We also studied the expression of the constructed genes using the human protein atlas database and analyzed their related pathways. Finally, copper staining was performed with the clinical sample to investigate the distribution of copper in breast cancer tissue and paracancerous tissue.ResultsPan-cancer analysis showed that copper-related genes are associated with breast cancer, and the immune infiltration profile of breast cancer samples is significantly different from that of other cancers. The essential copper-related genes of LASSO-Cox regression were ATP7B (ATPase Copper Transporting Beta) and DLAT (Dihydrolipoamide S-Acetyltransferase), whose associated genes were enriched in the cell cycle pathway. The low-copper related genes scoring group presented higher levels of immune activation, better probabilities of survival, enrichment in pathways related to pyruvate metabolism and apoptosis, and higher sensitivity to chemotherapy drugs. Immunohistochemistry staining showed high protein expression of ATP7B and DLAT in breast cancer samples. The copper staining showed copper distribution in breast cancer tissue.ConclusionThis study displayed the potential impacts of copper-related genes on the overall survival, immune infiltration, drug sensitivity and metabolic profile of breast cancer, which could predict patients’ survival and tumor statement. These findings may serve to support future research efforts aiming at improving the management of breast cancer

The Potential Use of DCE-MRI Texture Analysis to Predict HER2 2+ Status

Purpose: To evaluate the ability of texture analysis of breast dynamic contrast enhancement-magnetic resonance (DCE-MR) images in differentiating human epidermal growth factor receptor 2 (HER2) 2+ status of breast tumors.Methods: A total of 73 cases were retrospectively selected. HER2 2+ status was confirmed by fluorescence in situ hybridization. For each case, 279 textural features were derived. A student's t-test or Mann-Whitney U test was used to select features with statistically significant differences between HER2 2+ positive and negative groups. A principal component analysis was applied to eliminate feature correlation. Three machine learning classifiers, logistic regression (LR), quadratic discriminant analysis (QDA), and a support vector machine (SVM), were trained and tested using a leave-one-out cross-validation method. The area under a receiver operating characteristic curve (AUC) was measured to assess the classifier's performance.Results: The AUCs for the different classifiers were satisfactory, ranging from 0.808 to 0.865. The classification methods derived with LR and SVM demonstrated similarly high performances, and the accuracy levels were 81.06 and 81.18%, respectively. The AUC for the classifier derived with SVM was the highest (0.865), and a marked specificity (88.90%) was presented. For the classifier with LR, the AUC was 0.851, and the corresponding sensitivity (94.44%) was the highest.Conclusion: The texture analysis for breast DCE-MRI proposed in this study demonstrated potential utility in HER2 2+ status discrimination