Efficacy of ormutivimab, a novel recombinant human anti-rabies monoclonal antibody, in post-exposure prophylaxis animal models.

Human rabies is a serious public health problem that can't be ignored. Rabies immune globulin (RIG) is an indispensable component of rabies post-exposure prophylaxis (PEP). However, current PEP relies on RIG purified from pooled human or equine plasma, which are either in chronic shortage or associated with safety concerns. Monoclonal antibodies have become widely accepted as safer and more cost-effective alternatives to RIG products in recent years. Here, we assessed the neutralization breadth of human monoclonal antibody ormutivimab and its protective efficacy in PEP models. Ormutivimab was able to neutralize a broad panel of Chinese prevalent street RABVs with neutralizing potency form 198-1487.6 IU/mL. Furthermore, ormutivimab offered comparable protection to that with HRIG both at standard doses (20 IU/kg) and higher doses (100 IU/kg and 200 IU/kg). The interference of ormutivimab on vaccine potency was also analyzed and found slightly reduced neutralizing antibody titers similar to HRIG. The broad-spectrum neutralization activities, highly protective potency, and rapid onset of action make ormutivimab an effective candidate for human rabies PEP.

MiR-590-3p Attenuates Acute Kidney Injury by Inhibiting Tumor Necrosis Factor Receptor-Associated Factor 6 in Septic Mice.

Previous studies have been indicated that tumor necrosis factor receptor-associated factor 6 (TRAF6)-induced inflammation leads to acute kidney injury (AKI). How microRNA (miR) contributes to this process is poorly defined. The aim of this study was to investigate whether miR-590-3p regulated lipopolysaccharide (LPS)-induced inflammatory response by inhibiting TRAF6. LPS-induced septic mice were treated with adenovirus expressing miR-590-3p (ad-miR-590-3p) via tail-vein injection. AKI was evaluated by examining serum cystatin C (CysC), serum ß2-microglobulin (ß2-MG), and blood urea nitrogen (BUN). The mRNA and protein levels were assayed by RT-qPCR and western blotting, respectively. The proliferation of podocytes was monitored using the MTT assay. Cell apoptosis was analyzed by flow cytometry. Survival outcomes in ad-miR-590-3p-transfected septic mice were markedly improved compared with mice with LPS-induced sepsis. Ad-miR-590-3p transfection significantly attenuated LPS-induced AKI, which was reflected by an improved glomerular filtration rate (GFR) as determined by measuring CysC, ß2-MG, and BUN. Moreover, we observed that miR-590-3p was a novel regulator of TRAF6, binding to its 3'-untranslated regions (3'-UTRs). In vitro, a miR-590-3p gain-of-function mutation blocked LPS-induced podocyte growth inhibition and apoptosis, as well as overactivation of the inflammatory response. miR-590-3p has the ability to suppress LPS-induced AKI and podocyte apoptosis by targeting TRAF6. This might provide a novel strategy for the treatment of LPS-induced renal injuries.

Optimized discriminative kernel for SVM scoring and its application to speaker verification.

The decision-making process of many binary classification systems is based on the likelihood ratio (LR) scores of test patterns. This paper shows that LR scores can be expressed in terms of the similarity between the supervectors (SVs) formed by stacking the mean vectors of Gaussian mixture models corresponding to the test patterns, the target model, and the background model. By interpreting the support vector machine (SVM) kernels as a specific similarity (or discriminant) function between SVs, this paper shows that LR scoring is a special case of SVM scoring and that most sequence kernels can be obtained by assuming a specific form for the similarity function of SVs. This paper further shows that this assumption can be relaxed to derive a new general kernel. The kernel function is general in that it is a linear combination of any kernels belonging to the reproducing kernel Hilbert space. The combination weights are obtained by optimizing the ability of a discriminant function to separate the positive and negative classes using either regression analysis or SVM training. The idea was applied to both high-and low-level speaker verification. In both cases, results show that the proposed kernels achieve better performance than several state-of-the-art sequence kernels. Further performance enhancement was also observed when the high-level scores were combined with acoustic scores.