Multi-valent mRNA vaccines against monkeypox enveloped or mature viron surface antigens demonstrate robust immune response and neutralizing activity

Monkeypox was declared a global health emergency by the World Health Organization,and as of March 2023,86,000 confirmed cases and 111 deaths across 110 countries have been reported.Its causal agent,monkeypox virus(MPV)belongs to a large family of double-stranded DNA viruses,Orthopoxviridae,that also includes vaccinia virus(VACV)and others.MPV produces two distinct forms of viral particles during its replication cycles:the enveloped viron(EV)that is released via exocytosis,and the mature viron(MV)that is discharged through lysis of host cells.This study was designed to develop multi-valent m RNA vaccines against monkeypox EV and MV surface proteins,and examine their efficacy and mechanism of action.Four m RNA vaccines were produced with different combinations of surface proteins from EV(A35R and B6R),MV(A29L,E8L,H3L and M1R),or EV and MV,and were administered in Balb/c mice to assess their immunogenicity potentials.A dynamic immune response was observed as soon as seven days after initial immunization,while a strong Ig G response to all immunogens was detected with ELISA after two vaccinations.The higher number of immunogens contributed to a more robust total Ig G response and correlating neutralizing activity against VACV,indicating the additive potential of each immunogen in generating immune response and nullifying VACV infection.Further,the m RNA vaccines elicited an antigen-specific CD4^(+)T cell response that is biased towards Th1.The m RNA vaccines with different combinations of EVand MV surface antigens protected a mouse model from a lethal dose VACV challenge,with the EV and MV antigens-combined vaccine offering the strongest protection.These findings provide insight into the protective mechanism of multi-valent m RNAvaccines against MPV,and also the foundation for further development of effective and safe m RNA vaccines for enhanced protection against monkeypox virus outbreak.

Linear geometric algebra rotor estimator for efficient mesh deformation

The authors solve the problem of estimating the best rotation aligning two sets of corresponding vectors(also known as Wahba's problem or point cloud registration).The proposed method is among the fastest methods reported in recent literatures,moreover it is robust to noise,accurate and simpler than most other methods.It is based on solving the linear equations derived from the formulation of the problem in Euclidean Geometric Algebra.The authors show its efficiency in two applications:the as-rigid-as-possible(ARAP)surface modelling and the more smooth rotation enhanced ARAP mesh animation which is the only method capable of deforming surface modes with quality of tetrahedral models.Mesh deformation is a key technique in games,automated construction and robotics.The ARAP technique along with its improved variants,although have been extensively studied,can still not be achieved efficiently.Linear geometric algebra based rotor solution proposed in this study gives another perspective of the kernel problem.This,however,not only improves the real performance of the three-dimensional mesh deformation,but also provides a brand new computationally efficient solution to the Wahba's problem and point cloud registration,which has been closely related to the automation science and engineering.