Studies of Protein-Protein and Protein-Water Interactions by Small Angle X-Ray Scattering, Terahertz Spectroscopy, ASMOS, And Computer Simulation

The protein folding problem has been one of the most challenging subjects in biological physics due to its complexity. Energy landscape theory based on statistical mechanics provides a thermodynamic interpretation of the protein folding process. We have been working to answer fundamental questions about protein-protein and protein-water interactions, which are very important for describing the energy landscape surface of proteins correctly. At first, we present a new method for computing protein-protein interaction potentials of solvated proteins directly from SAXS data. An ensemble of proteins was modeled by Metropolis Monte Carlo and Molecular Dynamics simulations, and the global X-ray scattering of the whole model ensemble was computed at each snapshot of the simulation. The interaction potential model was optimized and iterated by a Levenberg-Marquardt algorithm. Secondly, we report that terahertz spectroscopy directly probes hydration dynamics around proteins and determines the size of the dynamical hydration shell. We also present the sequence and pH-dependence of the hydration shell and the effect of the hydrophobicity. On the other hand, kinetic terahertz absorption (KITA) spectroscopy is introduced to study the refolding kinetics of ubiquitin and its mutants. KITA results are compared to small angle X-ray scattering, tryptophan fluorescence, and circular dichroism results. We propose that KITA monitors the rearrangement of hydrogen bonding during secondary structure formation. Finally, we present development of the automated single molecule operating system (ASMOS) for a high throughput single molecule detector, which levitates a single protein molecule in a 10 µm diameter droplet by the laser guidance. I also have performed supporting calculations and simulations with my own program codes

Simulation-Based Fitting of Protein-Protein Interaction Potentials to SAXS Experiments

AbstractWe present a new method for computing interaction potentials of solvated proteins directly from small-angle x-ray scattering data. An ensemble of proteins is modeled by Monte Carlo or molecular dynamics simulation. The global x-ray scattering of the whole model ensemble is then computed at each snapshot of the simulation, and averaged to obtain the x-ray scattering intensity. Finally, the interaction potential parameters are adjusted by an optimization algorithm, and the procedure is iterated until the best agreement between simulation and experiment is obtained. This new approach obviates the need for approximations that must be made in simplified analytical models. We apply the method to lambda repressor fragment 6-85 and fyn-SH3. With the increased availability of fast computer clusters, Monte Carlo and molecular dynamics analysis using residue-level or even atomistic potentials may soon become feasible

Bacterial community analysis in upflow multilayer anaerobic reactor (UMAR) treating high-solids organic wastes

A novel anaerobic digestion configuration, the upflow multi-layer anaerobic reactor (UMAR), was developed to treat high-solids organic wastes. The UMAR was hypothesized to form multi-layer along depth due to the upflow plug flow; use of a recirculation system and a rotating distributor and baffles aimed to assist treating high-solids influent. The chemical oxygen demand (COD) removal efficiency and methane (CH4) production rate were 89% and 2.10 L CH4/L/day, respectively, at the peak influent COD concentration (110.4 g/L) and organic loading rate (7.5 g COD/L/day). The 454 pyrosequencing results clearly indicated heterogeneous distribution of bacterial communities at different vertical locations (upper, middle, and bottom) of the UMAR. Firmicutes was the dominant (>70%) phylum at the middle and bottom parts, while Deltaproteobacteria and Chloroflexi were only found in the upper part. Potential functions of the bacteria were discussed to speculate on their roles in the anaerobic performance of the UMAR system

Autologous collagen-induced chondrogenesis: From bench to clinical development

Microfracture is a common technique that uses bone marrow components to stimulate cartilage regeneration. However, the clinical results of microfracture range from poor to good. To enhance cartilage healing, several reinforcing techniques have been developed, including porcine-derived collagen scaffold, hyaluronic acid, and chitosan. Autologous collagen-induced chondrogenesis (ACIC) is a single-step surgical technique for cartilage regeneration that combines gel-type atelocollagen scaffolding with microfracture. Even though ACIC is a relatively new technique, literature show excellent clinical results. In addition, all procedures of ACIC are performed arthroscopically, which is increasing in preference among surgeons and patients. The ACIC technique also is called the Shetty–Kim technique because it was developed from the works of A.A. Shetty and S.J. Kim. This is an up-to-date review of the history of ACIC

Ruthenium Bottom Electrode Prepared by Electroplating for a High-density DRAM Capacitor

The possibility of Ru electroplating for application as the bottom electrode in high density dynamic random access memory ~DRAM! capacitors was investigated. Prior to Ru electroplating on a TiN substrate, HF cleaning and Pd activation were performed. Removal of Ti oxide from the TiN substrate by HF treatment enabled Pd activation, which enhanced the nucleation of Ru on TiN substrate. Optimized pretreatments led to a continuous Ru film deposition. The surface roughness was measured to be 4.4 nm at 45 nm Ru film on the bare substrate. Moreover Ru electroplating method was also applied to a capacitor node-type TiN wafer. The deposition rate of Ru on the patterned wafer was the same as that on a bare wafer. The film showed 93% step coverage and good adhesion, comparable to CVD Ru films

Importin-9 wraps around the H2A-H2B core to act as nuclear importer and histone chaperone.

We report the crystal structure of nuclear import receptor Importin-9 bound to its cargo, the histones H2A-H2B. Importin-9 wraps around the core, globular region of H2A-H2B to form an extensive interface. The nature of this interface coupled with quantitative analysis of deletion mutants of H2A-H2B suggests that the NLS-like sequences in the H2A-H2B tails play a minor role in import. Importin-9•H2A-H2B is reminiscent of interactions between histones and histone chaperones in that it precludes H2A-H2B interactions with DNA and H3-H4 as seen in the nucleosome. Like many histone chaperones, which prevent inappropriate non-nucleosomal interactions, Importin-9 also sequesters H2A-H2B from DNA. Importin-9 appears to act as a storage chaperone for H2A-H2B while escorting it to the nucleus. Surprisingly, RanGTP does not dissociate Importin-9•H2A-H2B but assembles into a RanGTP•Importin-9•H2A-H2B complex. The presence of Ran in the complex, however, modulates Imp9-H2A-H2B interactions to facilitate its dissociation by DNA and assembly into a nucleosome

Comparative Pharmacokinetics of Orbifloxacin Following a Single Intravenous or Oral Administration to Healthy and Diabetic Rats

The single-dose disposition kinetics of orbifloxacin was determined in clinically healthy and diabetic rats  after intravenous or oral administration of 5 mg/kg body weight. Orbifloxacin concentrations were determined  by HPLC with fluorescence detection. The HPLC method was sensitive, specific and repeatable. A  systemic bioavailability of 99.1% and 108 %, and a Cmax of 6.55 } 1.09 μg /mL and 8.63 } 1.09 μg /mL were  observed in healthy and diabetic rats, respectively. The terminal half-life after intravenous and oral administration  was 4.17 } 0.38 h and 4.03 } 0.41 h for healthy and 2.31 } 0.34 h and 3.03 } 0.28 h for diabetic  rats. Orbifloxacin was cleared more rapidly in diabetic rats (0.15 } 0.01 L/kg.h) than healthy group (0.11 }  0.01 L/kg.h), with longer mean resident time (MRT) values observed in the latter. Other kinetic parameters  were almost the same between the healthy and diabetic groups. This investigation revealed that a dose of 5  mg/kg orbifloxacin can be safely and effectively used to combat infections in rats of either group associated  with susceptible bacteria.

A Prospective Population-based Study of Total Nasal Resistance in Korean Subjects

ObjectivesRhinomanometry is a widely accepted method for objective assessment of nasal patency. However, few studies have reported the values of otherwise healthy population for nasal resistance in East Asians. The purpose of this study was to measure normal total nasal resistance (TNR) values in a large sample of Korean adults and to reveal parameters contributing to TNR values.MethodsSubjects were enrolled from a cohort of the Korean Genome and Epidemiology Study. They were evaluated by anthropometry, questionnaire, and active anterior rhinomanometry at transnasal pressures of 100 and 150 Pascal (Pa).ResultsThe study sample consisted of 2,538 healthy subjects (1,298 women and 1,240 men) aged 20 to 80 years. Normal reference TNR values were 0.19±0.08 Pa/cm3/second at 100 Pa and 0.22±0.09 Pa/cm3/second at 150 Pa. The TNR of women was significantly higher than that of men (P<0.0001). TNR decreased with increasing age in both genders (P<0.05). In women, lower body weight was related to increasing TNR. In men, current smokers had higher TNR than ex-smokers and never smokers.ConclusionThe results of the present study provide information regarding the values of otherwise healthy population of TNR and parameters associated with TNR in Korean adults

An Arrhythmia Classification-Guided Segmentation Model for Electrocardiogram Delineation

Accurate delineation of key waveforms in an ECG is a critical initial step in extracting relevant features to support the diagnosis and treatment of heart conditions. Although deep learning based methods using a segmentation model to locate P, QRS and T waves have shown promising results, their ability to handle signals exhibiting arrhythmia remains unclear. In this study, we propose a novel approach that leverages a deep learning model to accurately delineate signals with a wide range of arrhythmia. Our approach involves training a segmentation model using a hybrid loss function that combines segmentation with the task of arrhythmia classification. In addition, we use a diverse training set containing various arrhythmia types, enabling our model to handle a wide range of challenging cases. Experimental results show that our model accurately delineates signals with a broad range of abnormal rhythm types, and the combined training with classification guidance can effectively reduce false positive P wave predictions, particularly during atrial fibrillation and atrial flutter. Furthermore, our proposed method shows competitive performance with previous delineation algorithms on the Lobachevsky University Database (LUDB)