Earticle

Three isolates, E. faecium P1, P2 and P3, from intestinal drugs of three phamaceutical companies, four clinical vancomycin resistant isolates, E. faecium V1, V2, V3 and E. faecalis V4, and three isolates, E. faecalis DW01, DW07 and DW14, from infant feces were tested for the presence of virulence genes, ace, agg, esp, efaA, gelE, sprE, vanA and vanB as well as fsrABC, regulatory genes of gelE and sprE, cylMBA, cytolysin activation genes and cpd, cob and ccf, pheromone genes by PCR and for their phenotype activities such as protease, biofilm formation, cell clumping and hemolysis. The genes encoding cell surface adherence proteins, ace, agg, esp and efaA, were predominantly amplified from the vancomycin resistant strain V4 and the fecal isolates DW01, DW07 and DW14. Both protease and biofilm formation activity were detected only from E. faecalis V4 from which the PCR products of gelE and spreE as well as fsrABC were amplified. The pheromone genes were amplified from the V4, DW01, DW07 and DW14 strains and these strains showed clumping activity. Biofilm formation was observed from the strains DW01, DW07 and DW14, all of which produced PCR products of pheromone, and V4 as well. Whole cytolysin regulator genes were amplified from DW01, DW07 and DW14 and β-hemolysis activity was detected from these strains. Any virulence genes or activities except the pheomone gene ccf were not detected from the pharmaceutical isolates, E. faecium P1, P2 and P3.

Both the electrically positive and negative particles in a cell of quick response-liquid powder display (QR-LPD) are surrounded by conductive electrodes on the upper and lower substrate and the dielectric materials of the barrier ribs. Particles in a cell are attached to or detached from the other materials by image force, electric field, Coulomb's force, and Van der Waals' force. Through these forces, the moving particles form an image but induce clumping phenomena. Particles having a large kinetic energy by a large q/m value crash into the opposite electrode with high speed at a large driving voltage and quickly lose electrically charged material. As a result, these particles are clumped and degrade panel performance. The clumped particles in a cell are observed by microscopic photographs and ascertained by a response time. When the bias voltage is increased to 0.68-0.76 $V/{\mu}m$, particle clumping occurs abruptly and the response time increases sharply. This particle clumping is similarly observed after the number of driving times at the driving voltage (0.42-0.64 $V/{\mu}m$).

The analysis of plankton species distribution in sea or fresh water is very important in preserving marine ecosystem health. Since manual analysis is infeasible, many automatic approaches were proposed. They usually use images from in situ towed underwater imaging sensor or specially designed, lab mounted microscopic imaging system. Normally they assume that only single plankton is present in an image so that, if there is a clumping among multiple plankton of same species (homogeneous clumping) or if there are multiple plankton of different species scattered in an image (heterogeneous interspersion), they have a difficulty in recognition. In this work, we propose a deep learning based method that can detect and recognize individual plankton in images with homogeneous clumping, heterogeneous interspersion, or combination of both.

Pseudothrombocytopenia caused by platelet clumping (PC) can lead to unnecessary platelet transfusions or underdiagnosis of hematologic neoplasms. To overcome these limitations, we assessed the capacity of the Sysmex DI-60 digital morphology analyzer (Sysmex, Kobe, Japan) for detecting PC and determining an accurate platelet count in the presence of PC. For this purpose, 135 samples with or without PC (groups Y and N, respectively) were processed by an examiner (a hematologic specialist) using both the Sysmex XN-9000 and DI-60 analyzers. Although the platelet aggregate (PA) and giant platelet (GP) counts reported by the DI-60 and the examiner exhibited strong correlations, they proved inadequate as effective indicators for screening samples containing PC. Between the PA and GP counts and four platelet indices (the platelet distribution width [PDW], mean platelet volume [MPV], platelet large cell ratio [P_LCR], and plateletcrit [PCT]) reported by the XN- 9000, we observed statistically significant correlations (both overall and with group Y), but they were relatively weak. The platelet counts determined using the DI-60 and light microscopy in group Y showed substantial variations. Although the performance of the DI-60 was reliable for detecting PA and GP in smear images, such fixed areas are not representative of whole samples. Further, in the presence of PC, the resulting platelet counts determined using the DI-60 were not sufficiently accurate to be accepted as the final count.

Sortase A (SrtA), a type of transpeptidase responsible for anchoring surface proteins to the peptidoglycan cell wall, is important in the virulence of gram-positive bacteria. Three compounds were isolated from marine-derived Streptomyces sp. MBTH32 using various chromatography techniques. The structures of these compounds were determined based on spectroscopic data and comparisons with previously reported data. Among the metabolites tested, lumichrome showed strong inhibitory activity against Staphylococcus aureus SrtA without affecting cell viability. The results of cell clumping activity assessment suggest the potential for using this compound to treat S. aureus infection by inhibiting SrtA activity.

젖은 헤어 또는 동물의 털 시뮬레이션에서 응집력과 강성(stiffness)을 처리하는 것은 어려운 문제이다. 격렬한 움직임을 갖는 헤어나 털이 물에 젖게 되면 끝이 뭉치고 빳빳해지는 현상이 나타나게 되는데, 이는 달리는 동물이나 헤드뱅잉 하는 장면 등에서 쉽게 관찰 할 수 있다. 기존의 방법들은 정해진 시뮬레이션 시나리오에서 이 문제를 해결하려고 했지만 여전히 젖은 헤어의 특징을 묘사하기 위한 일반적인 방법이 존재하지 않는다. 이 문제를 해결하기 위해 우리는 응집력과 강성에 대한 새로운 모델링 방법을 제안한다. 기존 연구들은 물이 모발에 흡수되는 현상을 모델링 하는데 초점을 맞춘 반면, 우리는 젖은 모발의 움직임을 사실적으로 표현하는데 집중한다. 젖은 헤어는 마른 헤어와는 다르게 인접한 모발들끼리 응집력이 작용하여 서로 뭉치는 형태를 띄며, 물의 포화도가 높아질수록 빳빳해지는 독특한 물리적 특성이 나타난다. 제안된 기법의 핵심은 SPH (smoothed particle hydrodynamics) 기반의 표면 장력 모델을 확장하여 응집력을 표현하고, 강성 제약을 두어 모발의 탄성력을 조절하는 것이다. 우리 기법은 젖은 모발이 격렬한 움직임에서도 응집력을 잘 유지할 수 있도록 도와주며, 물의 포화도에 따른 모발의 빳빳함을 표현하여 사실적인 젖은 헤어 시뮬레이션 결과를 보여준다.

Simulating the clumping and stiffness of wet hair or fur is a challenging problem. The dynamics of wet hair or fur is characterized by the clumping and stiffness at the tip, which is easily seen in running animals or headbanging scenes. Existing methods address these phenomenon within pre-set scenarios. But there is no consensus on the method of depicting the details of wet hair. Hence, the present paper proposes a new method of modeling the clumping and stiffness of wet hair or fur. Previous studies focused on modeling the absorption of water into hair or fur, whereas this paper highlights a realistic simulation of wet hair. Unlike dry hair strands, wet hair strands adjacent to one another are subjected to the clumping force and gather together, while at the same time becoming stiff as the saturation of water increases. The proposed method builds on the surface tension model based on SPH (smoothed particle hydrodynamics) to simulate the clumping force and to adjust the hair elasticity by giving stiffness constraints. The present method enables a realistic simulation of wet hair by maintaining the clumping force of the wet hair even in dynamic motions, and by simulating the stiffness of hair in line with water saturation.