High-Fidelity 3D Digital Human Head Creation from RGB-D Selfies

We present a fully automatic system that can produce high-fidelity, photo-realistic three-dimensional (3D) digital human heads with a consumer RGB-D selfie camera. The system only needs the user to take a short selfie RGB-D video while rotating his/her head and can produce a high-quality head reconstruction in less than 30 s. Our main contribution is a new facial geometry modeling and reflectance synthesis procedure that significantly improves the state of the art. Specifically, given the input video a two-stage frame selection procedure is first employed to select a few high-quality frames for reconstruction. Then a differentiable renderer-based 3D Morphable Model (3DMM) fitting algorithm is applied to recover facial geometries from multiview RGB-D data, which takes advantages of a powerful 3DMM basis constructed with extensive data generation and perturbation. Our 3DMM has much larger expressive capacities than conventional 3DMM, allowing us to recover more accurate facial geometry using merely linear basis. For reflectance synthesis, we present a hybrid approach that combines parametric fitting and Convolutional Neural Networks (CNNs) to synthesize high-resolution albedo/normal maps with realistic hair/pore/wrinkle details. Results show that our system can produce faithful 3D digital human faces with extremely realistic details. The main code and the newly constructed 3DMM basis is publicly available.

Robust RDH Technique using Sorting and IPVO-based Pairwise PEE for Secure Communication

Nowadays, Reversible Data Hiding (RDH) is used extensively in information sensitive communication domains to protect the integrity of hidden data and the cover medium. However, most of the recently proposed RDH methods lack robustness. Robust RDH methods are required to protect the hidden data from security attacks at the time of communication between the sender and receiver. In this paper, we propose a Robust RDH scheme using IPVO based pairwise embedding. The proposed scheme is designed to prevent unintentional modifications caused to the secret data by JPEG compression. The cover image is decomposed into two planes namely HSB plane and LSB plane. As JPEG compression most likely modifies the LSBs of the cover image during compression, it is best not to hide the secret data into LSB planes. So, the proposed method utilizes a pairwise embedding to embed secret data into HSB plane of the cover image. High fidelity improved pixel value ordering (IPVO) based pairwise embedding ensures that the embedding performance of the proposed method is improved.

First-Response ABCDE Management of Status Epilepticus: A Prospective High-Fidelity Simulation Study

Respiratory infections following status epilepticus (SE) are frequent, and associated with higher mortality, prolonged ICU stay, and higher rates of refractory SE. Lack of airway protection may contribute to respiratory infectious complications. This study investigates the order and frequency of physicians treating a simulated SE following a systematic Airways-Breathing-Circulation-Disability-Exposure (ABCDE) approach, identifies risk factors for non-adherence, and analyzes the compliance of an ABCDE guided approach to SE with current guidelines. We conducted a prospective single-blinded high-fidelity trial at a Swiss academic simulator training center. Physicians of different affiliations were confronted with a simulated SE. Physicians (n = 74) recognized SE and performed a median of four of the five ABCDE checks (interquartile range 3–4). Thereof, 5% performed a complete assessment. Airways were checked within the recommended timeframe in 46%, breathing in 66%, circulation in 92%, and disability in 96%. Head-to-toe (exposure) examination was performed in 15%. Airways were protected in a timely manner in 14%, oxygen supplied in 69%, and antiseizure drugs (ASDs) administered in 99%. Participants’ neurologic affiliation was associated with performance of fewer checks (regression coefficient −0.49; p = 0.015). We conclude that adherence to the ABCDE approach in a simulated SE was infrequent, but, if followed, resulted in adherence to treatment steps and more frequent protection of airways.

The Role of Recombinant AAV in Precise Genome Editing

The replication-defective, non-pathogenic, nearly ubiquitous single-stranded adeno-associated viruses (AAVs) have gained importance since their discovery about 50 years ago. Their unique life cycle and virus-cell interactions have led to the development of recombinant AAVs as ideal genetic medicine tools that have evolved into effective commercialized gene therapies. A distinctive property of AAVs is their ability to edit the genome precisely. In contrast to all current genome editing platforms, AAV exclusively utilizes the high-fidelity homologous recombination (HR) pathway and does not require exogenous nucleases for prior cleavage of genomic DNA. Together, this leads to a highly precise editing outcome that preserves genomic integrity without incorporation of indel mutations or viral sequences at the target site while also obviating the possibility of off-target genotoxicity. The stem cell-derived AAV (AAVHSCs) were found to mediate precise and efficient HR with high on-target accuracy and at high efficiencies. AAVHSC editing occurs efficiently in post-mitotic cells and tissues in vivo. Additionally, AAV also has the advantage of an intrinsic delivery mechanism. Thus, this distinctive genome editing platform holds tremendous promise for the correction of disease-associated mutations without adding to the mutational burden. This review will focus on the unique properties of direct AAV-mediated genome editing and their potential mechanisms of action.

Spatial MIST Technology for Rapid, Highly Multiplexed Detection of Protein Distribution on Brain Tissue

Highly multiplexed analysis of biospecimens significantly advances the understanding of biological basics of diseases, but these techniques are limited by the number of multiplexity and the speed of processing. Here, we present a rapid multiplex method for quantitative detection of protein markers on brain sections with the cellular resolution. This spatial multiplex in situ tagging (MIST) technology is built upon a MIST microarray that contains millions of small microbeads carrying barcoded oligonucleotides. Using antibodies tagged with UV cleavable oligonucleotides, the distribution of protein markers on a tissue slice could be printed on the MIST microarray with high fidelity. The performance of this technology in detection sensitivity, resolution and signal-to-noise level has been fully characterized by detecting brain cell markers. We showcase the codetection of 31 proteins simultaneously within 2 h which is about 10 times faster than the other immunofluorescence-based approaches of similar multiplexity. A full set of computational toolkits was developed to segment the small regions and identify the regional differences across the entire mouse brain. This technique enables us to rapidly and conveniently detect dozens of biomarkers on a tissue specimen, and it can find broad applications in clinical pathology and disease mechanistic studies.