Meandering river sandstone architecture characterization based on seisimic sedimentology in Kumkol South oilfields [RETRACTED ARTICLE]

1460-1471To improve the finely architecture characterization of meandering river sand body in wide well space oilfield, this study identified the meandering river sand body of Layer MI-1 of Kumkol South Oilfield in South Turgai Basin. Under the guidance of the sedimentary pattern of meandering channel sand body, this study establishes the log-seismic reservoir characterization method by applying reservoir characterization，seismic sedimentology and seismic forward simulation with well logging and seismic data. The different levels of meandering river sand body which include the composite meandering belts, single meandering belt, single point bar and single point bar inner are finely studied in Layer MI-1 of Kumkol South Oilfield. Based on the researches mentioned above, the recognition method and criteria of composite channel are studied. Specifically, the cosine phase seismic attribute can be used to recognize the lateral boundaries of composite channel when the thickness of composite channels >8 m. And the frequency division data can be used to recognize the vertical boundaries of composite channels when the thickness of composite channels >9 m. The recognition methods of the abandon channel and the mud stone between channels are also studied. Specifically, the sweet, waveform classification and the three-instantaneous information can improve the recognition of single channel boundary. Six boundaries are recognized in layer MI-1. Finally, the recognition method and criteria of lateral accretionary layers are studied. In the sedimentary and seismic data conditions of study area, the synthetic seismic information can improve the recognition of the lateral accretionary layers when the thickness of point bar >12 m and the thickness of lateral accretionary layers >1. 5 m

An effective method for refining predicted protein complexes based on protein activity and the mechanism of protein complex formation

BACKGROUND: Identifying protein complexes from protein-protein interaction network is fundamental for understanding the mechanism of cellular component and protein function. At present, many methods to identify protein complexes are mainly based on the topological characteristics or the functional similarity features, neglecting the fact that proteins must be in their active forms to interact with others and the formation of protein complex is following a just-in-time mechanism. RESULTS: This paper firstly presents a protein complex formation model based on the just-in-time mechanism. By investigating known protein complexes combined with gene expression data, we find that most protein complexes can be formed in continuous time points, and the average overlapping rate of the known complexes during the formation is large. A method is proposed to refine the protein complexes predicted by clustering algorithms based on the protein complex formation model and the properties of known protein complexes. After refinement, the number of known complexes that are matched by predicted complexes, Sensitivity, Specificity, and f-measure are significantly improved, when compared with those of the original predicted complexes. CONCLUSION: The refining method can discard the spurious proteins by protein activity and generate new complexes by just-in-time assemble mechanism, which can enhance the ability to predict complex

Rechecking the Centrality-Lethality Rule in the Scope of Protein Subcellular Localization Interaction Networks

Essential proteins are indispensable for living organisms to maintain life activities and play important roles in the studies of pathology, synthetic biology, and drug design. Therefore, besides experiment methods, many computational methods are proposed to identify essential proteins. Based on the centrality-lethality rule, various centrality methods are employed to predict essential proteins in a Protein-protein Interaction Network (PIN). However, neglecting the temporal and spatial features of protein-protein interactions, the centrality scores calculated by centrality methods are not effective enough for measuring the essentiality of proteins in a PIN. Moreover, many methods, which overfit with the features of essential proteins for one species, may perform poor for other species. In this paper, we demonstrate that the centrality-lethality rule also exists in Protein Subcellular Localization Interaction Networks (PSLINs). To do this, a method based on Localization Specificity for Essential protein Detection (LSED), was proposed, which can be combined with any centrality method for calculating the improved centrality scores by taking into consideration PSLINs in which proteins play their roles. In this study, LSED was combined with eight centrality methods separately to calculate Localization-specific Centrality Scores (LCSs) for proteins based on the PSLINs of four species (Saccharomyces cerevisiae, Homo sapiens, Mus musculus and Drosophila melanogaster). Compared to the proteins with high centrality scores measured from the global PINs, more proteins with high LCSs measured from PSLINs are essential. It indicates that proteins with high LCSs measured from PSLINs are more likely to be essential and the performance of centrality methods can be improved by LSED. Furthermore, LSED provides a wide applicable prediction model to identify essential proteins for different species

Spinal nerve segmentation method and dataset construction in endoscopic surgical scenarios

Endoscopic surgery is currently an important treatment method in the field of spinal surgery and avoiding damage to the spinal nerves through video guidance is a key challenge. This paper presents the first real-time segmentation method for spinal nerves in endoscopic surgery, which provides crucial navigational information for surgeons. A finely annotated segmentation dataset of approximately 10,000 consec-utive frames recorded during surgery is constructed for the first time for this field, addressing the problem of semantic segmentation. Based on this dataset, we propose FUnet (Frame-Unet), which achieves state-of-the-art performance by utilizing inter-frame information and self-attention mechanisms. We also conduct extended exper-iments on a similar polyp endoscopy video dataset and show that the model has good generalization ability with advantageous performance. The dataset and code of this work are presented at: https://github.com/zzzzzzpc/FUnet .Comment: Accepted by MICCAI 202

Novel approach to investigate η\eta decays via η′→ππη\eta'\rightarrow\pi\pi\eta

To avoid the impact from the background events directly from $e^+e^-$ annihilations or $J/\psi$ decays, we propose a novel approach to investigate $\eta$ decays, in particular for its rare or forbidden decays, by using $\eta^\prime\rightarrow\pi\pi\eta$ produced in $J/\psi$ decays at the $\tau-$charm factories. Based on the MC studies of a few typical decays, $\eta\rightarrow \pi\pi$, $\gamma l^+l^- (l= e, \mu)$, $l^+l^-$, as well as $l^+l^-\pi^0$, the sensitivities could be obviously improved by taking advantage of the extra constraint of $\eta^\prime$. Using one trillion $J/\psi$ events accumulated at the Super $\tau$-Charm facility, the precision on the investigation of $\eta$ decays could be improved significantly and the observation of the rare decay $\eta\rightarrow e^+e^-$ is even accessable.Comment: 7 pages, 6 figure

Correlation between serum RANTES levels and the severity of Parkinson’s disease,”

Inflammatory mediators may reflect a role of systemic inflammation in the neurodegenerative process of Parkinson's disease (PD). Interleukin-6 (IL-6) and chemokine ligand 5 (CCL5), also known as RANTES (regulated on activation, normal T cell expressed and secreted), have been implicated in neurodegenerative diseases including PD. Serum levels of RANTES and IL-6 of 78 consecutive PD patients and age-matched 80 controls were measured. Patients with PD had higher RANTES and IL-6 levels compared with the controls. We found that serum RANTES levels strongly correlated with Hoehn-Yahr score and disease duration in PD patients. This study indicated that patients with PD have an on-going systemic inflammatory profile where the elevated peripheral production of RANTES may play a role in the neurodegenerative process

Differences in brain gray matter volume in patients with Crohn’s disease with and without abdominal pain

Increasing evidence indicates that abnormal pain processing is present in the central nervous system of patients with Crohn’s disease (CD). The purposes of this study were to assess changes in gray matter (GM) volumes in CD patients in remission and to correlate structural changes in the brain with abdominal pain. We used a 3.0 T magnetic resonance scanner to examine the GM structures in 21 CD patients with abdominal pain, 26 CD patients without abdominal pain, and 30 healthy control subjects (HCs). Voxel-based morphometric analyses were used to assess the brain GM volumes. Patients with abdominal pain exhibited higher CD activity index and lower inflammatory bowel disease questionnaire scores than those of the patients without abdominal pain. Compare to HCs and to patients without abdominal pain, patients with abdominal pain exhibited lower GM volumes in the insula and anterior cingulate cortex (ACC); whereas compare to HCs and to patients with abdominal pain, the patients without abdominal pain exhibited higher GM volumes in the hippocampal and parahippocampal cortex. The GM volumes in the insula and ACC were significantly negatively correlated with daily pain scores. These results suggest that differences exist in the brain GM volume between CD patients in remission with and without abdominal pain. The negative correlation between the GM volumes in the insula and ACC and the presence and severity of abdominal pain in CD suggests these structures are closely related to visceral pain processing