Creating high-resolution 3D cranial implant geometry using deep learning techniques

Creating a personalized implant for cranioplasty can be costly and aesthetically challenging, particularly for comminuted fractures that affect a wide area. Despite significant advances in deep learning techniques for 2D image completion, generating a 3D shape inpainting remains challenging due to the higher dimensionality and computational demands for 3D skull models. Here, we present a practical deep-learning approach to generate implant geometry from defective 3D skull models created from CT scans. Our proposed 3D reconstruction system comprises two neural networks that produce high-quality implant models suitable for clinical use while reducing training time. The first network repairs low-resolution defective models, while the second network enhances the volumetric resolution of the repaired model. We have tested our method in simulations and real-life surgical practices, producing implants that fit naturally and precisely match defect boundaries, particularly for skull defects above the Frankfort horizontal plane

Construction and Characterization of Insect Cell-Derived Influenza VLP: Cell Binding, Fusion, and EGFP Incorporation

We have constructed virus-like particles (VLPs) harboring hemagglutinin (HA), neuraminidase (NA), matrix protein 1 (M1) ,and proton channel protein (M2) using baculovirus as a vector in the SF9 insect cell. The size of the expressed VLP was estimated to be ~100 nm by light scattering experiment and transmission electron microscopy. Recognition of HA on the VLP surface by the HA2-specific monoclonal antibody IIF4 at acidic pH, as probed by surface plasmon resonance, indicated the pH-induced structural rearrangement of HA. Uptake of the particle by A549 mediated by HA-sialylose receptor interaction was visualized by the fluorescent-labeled VLP. The HA-promoted cell-virus fusion activity was illustrated by fluorescence imaging on the Jurkat cells incubated with rhodamine-loaded VLP performed at fusogenic pH. Furthermore, the green fluorescence protein (GFP) was fused to NA to produce VLP with a pH-sensitive probe, expanding the use of VLP as an antigen carrier and a tool for viral tracking

Resveratrol retards progression of diabetic nephropathy through modulations of oxidative stress, proinflammatory cytokines, and AMP-activated protein kinase

<p>Abstract</p> <p>Background</p> <p>Diabetic nephropathy (DN) has been recognized as the leading cause of end-stage renal disease. Resveratrol (RSV), a polyphenolic compound, has been indicated to possess an insulin-like property in diabetes. In the present study, we aimed to investigate the renoprotective effects of RSV and delineate its underlying mechanism in early-stage DN.</p> <p>Methods</p> <p>The protective effects of RSV on DN were evaluated in streptozotocin (STZ)-induced diabetic rats.</p> <p>Results</p> <p>The plasma glucose, creatinine, and blood urea nitrogen were significantly elevated in STZ-induced diabetic rats. RSV treatment markedly ameliorated hyperglycemia and renal dysfunction in STZ-induced diabetic rats. The diabetes-induced superoxide anion and protein carbonyl levels were also significantly attenuated in RSV-treated diabetic kidney. The AMPK protein phosphorylation and expression levels were remarkably reduced in diabetic renal tissues. In contrast, RSV treatment significantly rescued the AMPK protein expression and phosphorylation compared to non-treated diabetic group. Additionally, hyperglycemia markedly enhanced renal production of proinflammatory cytokine IL-1β. RSV reduced IL-1β but increased TNF-α and IL-6 levels in the diabetic kidneys.</p> <p>Conclusions</p> <p>Our findings suggest that RSV protects against oxidative stress, exhibits concurrent proinflammation and anti-inflammation, and up-regulates AMPK expression and activation, which may contribute to its beneficial effects on the early stage of DN.</p

Monitoring Apnea in the Elderly by an Electromechanical System with a Carbon Nanotube-based Sensor

SummaryBackgroundBreathing, a part of respiration, is one of the vital functions. Breathing disorders are common in the elderly. An effective breathing sensor for real-time detection of apnea is important in clinical critical care. We aimed to construct a real-time warning platform with a combination of carbon nanotubes (CNTs) and related nano-electromechanical system (NEMS) for elderly care.MethodsThrough a specific acid-treated procedure, multiwalled carbon nanotubes (MWCNTs) were immobilized on a thin silicon dioxide (SiO2) film, coated on a heated silicon wafer. Techniques of photolithography and sputtering with chromium and gold were then implemented on the MWCNT film to develop micro-interdigitated electrodes as a base for the breathing sensor. The sensor was equipped with a programmed microchip processor to become a warning detector for abnormal human breathing, namely less than six breaths per minute. Elderly volunteers were enrolled for examining the effective sensitivity of this novel electromechanical device.ResultsThere were 15 elderly volunteers (9 males and 6 females) tested in this experiment. The dynamic analyses of the MWCNT sensor to exhaled breath showed that it had characteristics of rapid response, high aspect ratio, small tip ratio, and high electrical conductivity. Responses of the MWCNT sensor to exhaled breath was recorded according to different performance parameters, i.e., strength, frequency, flow rate, and breath components. In this study, variable pattern-simulated tests showed that a MWCNT sensor combined with a processor could accurately evoke warning signals (100% of sensitivity rate), indicating its effectiveness and usefulness for detecting abnormal breathing rates, especially apnea.ConclusionOur results showed that a new device composed of an NEMS by combining an MWCNT sensor and complementary metal-oxide semiconductor (CMOS) circuits could be integrated to effectively detect apnea in the elderly. This novel device may improve the pattern of safe respiratory care for the elderly in the future

Japanese encephalitis virus co-opts the ER-stress response protein GRP78 for viral infectivity

The serum-free medium from Japanese encephalitis virus (JEV) infected Baby Hamster Kidney-21 (BHK-21) cell cultures was analyzed by liquid chromatography tandem mass spectrometry (LC-MS) to identify host proteins that were secreted upon viral infection. Five proteins were identified, including the molecular chaperones Hsp90, GRP78, and Hsp70. The functional role of GRP78 in the JEV life cycle was then investigated. Co-migration of GRP78 with JEV particles in sucrose density gradients was observed and co-localization of viral E protein with GRP78 was detected by immunofluorescence analysis in vivo. Knockdown of GRP78 expression by siRNA did not effect viral RNA replication, but did impair mature viral production. Mature viruses that do not co-fractionate with GPR78 displayed a significant decrease in viral infectivity. Our results support the hypothesis that JEV co-opts host cell GPR78 for use in viral maturation and in subsequent cellular infections

Identification of hot regions in protein-protein interactions by sequential pattern mining

<p>Abstract</p> <p>Background</p> <p>Identification of protein interacting sites is an important task in computational molecular biology. As more and more protein sequences are deposited without available structural information, it is strongly desirable to predict protein binding regions by their sequences alone. This paper presents a pattern mining approach to tackle this problem. It is observed that a functional region of protein structures usually consists of several peptide segments linked with large wildcard regions. Thus, the proposed mining technology considers large irregular gaps when growing patterns, in order to find the residues that are simultaneously conserved but largely separated on the sequences. A derived pattern is called a cluster-like pattern since the discovered conserved residues are always grouped into several blocks, which each corresponds to a local conserved region on the protein sequence.</p> <p>Results</p> <p>The experiments conducted in this work demonstrate that the derived long patterns automatically discover the important residues that form one or several hot regions of protein-protein interactions. The methodology is evaluated by conducting experiments on the web server MAGIIC-PRO based on a well known benchmark containing 220 protein chains from 72 distinct complexes. Among the tested 218 proteins, there are 900 sequential blocks discovered, 4.25 blocks per protein chain on average. About 92% of the derived blocks are observed to be clustered in space with at least one of the other blocks, and about 66% of the blocks are found to be near the interface of protein-protein interactions. It is summarized that for about 83% of the tested proteins, at least two interacting blocks can be discovered by this approach.</p> <p>Conclusion</p> <p>This work aims to demonstrate that the important residues associated with the interface of protein-protein interactions may be automatically discovered by sequential pattern mining. The detected regions possess high conservation and thus are considered as the computational hot regions. This information would be useful to characterizing protein sequences, predicting protein function, finding potential partners, and facilitating protein docking for drug discovery.</p

Interplay between the magnetic and electric degrees-of-freedom in multiferroic Co3TeO6

Neutron diffraction, magnetic susceptibility, specific heat, and dielectric constant measurements of single crystal Co3TeO6 have been measured to study the interplay between the ferroelectricity and magnetic order. Long range incommensurate magnetic order develops below TM1=26 K, which is followed by three additional zero-field phase transitions at TM2=19.5 K, TM3=18 K, and TM4=16 K where the incommensurate order changes and commensurate order develops. In magnetic fields up to 14 T we find that the magnetic intensities and incommensurate wave vector are dramatically altered as ferroelectricity develops, with a fifth abrupt transition around 10 T. The overall behavior characterizes Co3TeO6 as a type-II multiferroic.Comment: Phys. Rev. B (in press

Does Long-Term Use of Silver Nanoparticles Have Persistent Inhibitory Effect on H. pylori Based on Mongolian Gerbil’s Model?

It is urgent to find alternative agents due to increasing failure rate of Helicobacter pylori (H. pylori) eradication. The study surveyed the long-term effect of silver nanoparticles (AgNP) on H. pylori based on Mongolian gerbil's model

Potassium {4-[(3S,6S,9S)-3,6-dibenzyl-9-isopropyl-4,7,10-trioxo-11–oxa-2,5,8-triazadodecyl]phenyl}trifluoroborate

[[abstract]]The reported compound 4 was synthesized and fully characterized by 1H NMR, 13C NMR, 11B NMR, 19F NMR, and high resolution mass spectrometry.[[booktype]]電子版[[countrycodes]]CH