Lizhen Huang

A series of derivatives of the known thromboxane A2 prostanoid receptor antagonists, 3-sulfonamido)-5,6,7,8-tetrahydronaphthalen-1-yl)propanoic acid and 3-sulfonamido)ethyl)phenyl) propanoic acid, were synthesized in which the carboxylic acid functional group was replaced with substituted cyclopentane-1,3-dione bioisosteres. Characterization of these molecules led to the discovery of remarkably potent new analogues, some of which were considerably more active than the corresponding parent carboxylic acid compounds. Depending on the choice of the C2 substituent of the CPD unit, these new derivatives can produce either a reversible or an apparent irreversible inhibition of the human TP receptor. Given the potency and the long-lasting inhibition of TP receptor signaling, these novel antagonists may comprise promising leads for the development of antithromboxane therapies.

To examine predictors and outcomes of Staphylococcus aureus Pneumonia in people with HIV compared with Streptococcus pneumoniae Pneumonia, and to compare Methicillin-Resistant S. aureus with Methicillin-Sensitive S. aureus pneumonias in this population.We conducted a retrospective case-control study of HIV-infected patients admitted to a single center with culture-proven S. aureus or S. pneumoniae pneumonia. We identified patients through a computerized database, conducted structured chart reviews, and performed bivariate and multivariate analyses using logistic regression.We compared 47 SAP episodes in 42 patients with 100 SPP episodes in 93 patients. Use of any antibiotics prior to admission, a co-morbid illness, and recent healthcare contact were significant independent predictors of SAP. Patients with SAP were more likely to require intensive care and mechanical ventilation, but not to die. MRSA was more common than MSSA, but outcomes were not significantly worse.Patients with HIV and SAP have worse outcomes than those with SPP. Clinicians should consider empiric antibiotic coverage for MRSA in patients admitted with HIV and pneumonia, given the high prevalence of MRSA. Further studies are warranted to examine morbidity differences between HIV-associated MSSA and MRSA pneumonia.

Peptides show much promise as potent and selective drug candidates. Fusing peptides to a scaffold monoclonal antibody produces a conjugated antibody which has the advantages of peptide activity yet also has the pharmacokinetics determined by the scaffold antibody. However, the conjugated antibody often has poor binding affinity to antigens that may be related to unknown structural changes. The study of the conformational change is difficult by conventional techniques because structural fluctuation under equilibrium results in multiple structures co-existing. Here, we employed our two recently developed electron microscopy techniques: optimized negative-staining EM and individual-particle electron tomography. Two-dimensional image analyses and three-dimensional maps have shown that the domains of antibodies present an elongated peptide-conjugated conformational change, suggesting that our EM techniques may be novel tools to monitor the structural conformation changes in heterogeneous and dynamic macromolecules, such as drug delivery vehicles after pharmacological synthesis and development.

Aiming at the problem of radar target recognition of High-Resolution Range Profile under low signal-to-noise ratio conditions, a recognition method based on the Constrained Naive Least-Squares Generative Adversarial Network, Short-time Fourier Transform, and Convolutional Neural Network is proposed. Combining the Least-Squares Generative Adversarial Network with the Wasserstein Generative Adversarial Network with Gradient Penalty, the CN-LSGAN is presented and applied to the HRRP denoise. The frequency domain and phase features of HRRP are gained by STFT in order to facilitate feature learning and also match the input data format of the CNN. These experimental results show that the CN-LSGAN has better data augmentation performance and can effectively avoid the model collapse compared to the generative adversarial network and LSGAN. Also, the method has better recognition performance than the one-dimensional CNN method and the Long Short-Term Memory network method.