Convergence to diffusion waves for solutions of Euler equations with time-depending damping on quadrant

This paper is concerned with the asymptotic behavior of the solution to the Euler equations with time-depending damping on quadrant $(x,t)\in \mathbb{R}^+\times\mathbb{R}^+$, \begin{equation}\notag \partial_t v - \partial_x u=0, \qquad \partial_t u + \partial_x p(v) =\displaystyle -\frac{\alpha}{(1+t)^\lambda} u, \end{equation} with null-Dirichlet boundary condition or null-Neumann boundary condition on $u$. We show that the corresponding initial-boundary value problem admits a unique global smooth solution which tends time-asymptotically to the nonlinear diffusion wave. Compared with the previous work about Euler equations with constant coefficient damping, studied by Nishihara and Yang (1999, J. Differential Equations, 156, 439-458), and Jiang and Zhu (2009, Discrete Contin. Dyn. Syst., 23, 887-918), we obtain a general result when the initial perturbation belongs to the same space. In addition, our main novelty lies in the facts that the cut-off points of the convergence rates are different from our previous result about the Cauchy problem. Our proof is based on the classical energy method and the analyses of the nonlinear diffusion wave

Adherence to anti-tuberculosis treatment among pulmonary tuberculosis patients: a qualitative and quantitative study

BACKGROUND: Tuberculosis (TB) patients have difficulty following a long-term treatment regimen. Efforts to improve treatment outcomes require better understanding of adherence as a complex behavioral issue and of the particular barriers to and facilitators of patient adherence. METHODS: This study was carried out in Jiangsu Province of China with both quantitative and qualitative approaches. For the quantitative study, 780 sputum-smear positive TB patients consecutively registered since 2006 in 13 counties (districts) were queried with a structured questionnaire. Patients who had missed 10% of their total prescribed doses of TB drugs were deemed as non-adherent. Risks for non-adherence were estimated by computing odds ratios (ORs) and their 95% confidence intervals (95% CIs) using a logistic regression model. We also invited 20 TB patients and 10 local health workers for in-depth interviews. We then used content analysis based on this qualitative study to explore factors associated with non-adherence. RESULTS: The proportion of non-adherence among 670 patients was 12.2%. Univariate analysis showed that patients, who were illiterate, divorced/widowed, lacked health insurance and were migrants, were more likely to be non-adherent. The crude ORs(95%CIs) were 2.38(1.37-4.13), 2.42(1.30-4.52), 1.89(1.07-3.32) and 1.98(1.03-3.83), respectively. The risk of non-adherence was lower among patients whose treatment was given under direct observation by village doctors or regular home visits by health workers, with ORs (95% CIs) of 0.19(0.10-0.36) and 0.23(0.10-0.51), respectively. In multivariate analysis, factors associated with non-adherence included illiteracy (OR: 2.42; 95% CI: 1.25-4.67) and direct observation by village doctors (OR: 0.23; 95% CI: 0.11-0.45). The in-depth interviews indicated that financial burdens and extra medical expenditures, adverse drug reactions, and social stigma were additional potential factors accounted for non-adherence. CONCLUSION: More importance should be given to treatment adherence under the current TB control program. Heavy financial burdens, lack of social support, adverse drug reactions and personal factors are associated with non-adherence. Direct observation and regular home visits by health workers appear to reduce the risk of non-adherence. More patient-centered interventions and greater attention to structural barriers are needed to improve treatment adherence

Now and Future of Artificial Intelligence-based Signet Ring Cell Diagnosis: A Survey

Since signet ring cells (SRCs) are associated with high peripheral metastasis rate and dismal survival, they play an important role in determining surgical approaches and prognosis, while they are easily missed by even experienced pathologists. Although automatic diagnosis SRCs based on deep learning has received increasing attention to assist pathologists in improving the diagnostic efficiency and accuracy, the existing works have not been systematically overviewed, which hindered the evaluation of the gap between algorithms and clinical applications. In this paper, we provide a survey on SRC analysis driven by deep learning from 2008 to August 2023. Specifically, the biological characteristics of SRCs and the challenges of automatic identification are systemically summarized. Then, the representative algorithms are analyzed and compared via dividing them into classification, detection, and segmentation. Finally, for comprehensive consideration to the performance of existing methods and the requirements for clinical assistance, we discuss the open issues and future trends of SRC analysis. The retrospect research will help researchers in the related fields, particularly for who without medical science background not only to clearly find the outline of SRC analysis, but also gain the prospect of intelligent diagnosis, resulting in accelerating the practice and application of intelligent algorithms

In Situ Absorption in Rat Intestinal Tract of Solid Dispersion of Annonaceous Acetogenins

Isolated from Annona squamosa L, Annonaceous acetogenins (ACGs) exhibit a broad range of biological properties yet absorbed badly due to the low solubility. Solid dispersion in polyethylene glycol 4000 (PEG 4000) has been developed to increase the solubility and oral absorption of ACGs. The formulation of ACGS-solid dispersion was optimized by a simplex lattice experiment design and carried out by a solvent-fusion method. We studied the absorption property of ACGs in rat's intestine, which showed there was a good absorption and uptake percentages with solid dispersion. The study on uptake percentage in different regions of rat's intestine attested that the duodenum had the best permeability, followed by jejunum, ileum, and colon in order with no significant differences. So the paper drew the conclusion that solid dispersion could improve the solubility and oral absorption of annonaceous acetogenins

Use of 3D-computed tomography angiography for planning the surgical removal of pineal region meningiomas using Poppen's approach: a report of ten cases and a literature review

<p>Abstract</p> <p>Background</p> <p>There are several treatment approaches for pineal region meningiomas, such as Poppen's approach, Krause's approach and combinations of the two approaches. We present our experience with the use of 3D-computed tomography angiography for planning the surgical removal of pineal region meningiomas using a suboccipital transtentorial approach (Poppen's approach) and evaluate the role of Poppen's approach.</p> <p>Methods</p> <p>During the period from January 2005 to June 2010, ten patients presented to us with pineal region meningioma. MRI was routinely used to define the tumor size, position, and its relevant complications while 3D-CTA was applied to define the blood supply of the tumor and the venous complex (VC) shift before operations. Most of the meningiomas had developed at both sides of the tentorial plane and extended laterally with typical characteristics of a pineal region tumor.</p> <p>Results</p> <p>All tumors were completely removed surgically without any injury to the VC. Postoperative intracranial infection occurred in one case who recovered after antibiotics were given. Postoperative intraventricular hemorrhage and pneumocephalus were found in one case, but fully recovered after conservative treatment. In the nine cases of concurrent hydrocephalus, this was gradually relieved in eight patients and the single case that became aggravated was successfully treated with ventriculoperitoneal shunt. Moreover, the follow-up MRI examinations did not indicate any recurrence of the meningiomas.</p> <p>Conclusion</p> <p>We found that the use of Poppen's approach is strongly supported for the successful removal of pineal region meningiomas without serious complications.</p

Assessing and Enhancing Robustness of Deep Learning Models with Corruption Emulation in Digital Pathology

Deep learning in digital pathology brings intelligence and automation as substantial enhancements to pathological analysis, the gold standard of clinical diagnosis. However, multiple steps from tissue preparation to slide imaging introduce various image corruptions, making it difficult for deep neural network (DNN) models to achieve stable diagnostic results for clinical use. In order to assess and further enhance the robustness of the models, we analyze the physical causes of the full-stack corruptions throughout the pathological life-cycle and propose an Omni-Corruption Emulation (OmniCE) method to reproduce 21 types of corruptions quantified with 5-level severity. We then construct three OmniCE-corrupted benchmark datasets at both patch level and slide level and assess the robustness of popular DNNs in classification and segmentation tasks. Further, we explore to use the OmniCE-corrupted datasets as augmentation data for training and experiments to verify that the generalization ability of the models has been significantly enhanced

Design, synthesis and biological evaluation of pyridine-chalcone derivatives as novel microtubule-destabilizing agents

Further optimization of the trimethoxyphenyl scaffold of parent chalcone compound (2a) by introducing a pyridine ring afforded a series of novel pyridine-chalcone derivatives as potential anti-tubulin agents. All the target compounds were evaluated for their antiproliferative activities. Among them, representative compound 16f exhibited the most potent activity with the IC50 values ranging from 0.023 to 0.045 μM against a panel of cancer cell lines. Further mechanism study results demonstrated that compound 16f effectively inhibited the microtubule polymerization by binding to the colchicine site of tubulin. Moreover, cellular mechanism studies disclosed that 16f caused G2/M phase arrest, induced cell apoptosis and disrupted the intracellular microtubule network. Also, 16f reduced the cell migration and disrupted the capillary-like tube formation of human umbilical vein endothelial cells (HUVECs). Importantly, 16f significantly inhibited tumor growth in H22 xenograft models without apparent toxicity, which was stronger than the reference compound CA-4, indicating that it is worthy to investigate 16f as a potent microtubule-destabilizing agent for cancer therapy

Proteome changes of lungs artificially infected with H-PRRSV and N-PRRSV by two-dimensional fluorescence difference gel electrophoresis

<p>Abstract</p> <p>Background</p> <p>Porcine reproductive and respiratory syndrome with PRRS virus (PRRSV) infection, which causes significant economic losses annually, is one of the most economically important diseases affecting swine industry worldwide. In 2006 and 2007, a large-scale outbreak of highly pathogenic porcine reproductive and respiratory syndrome (PRRS) happened in China and Vietnam. However little data is available on global host response to PRRSV infection at the protein level, and similar approaches looking at mRNA is problematic since mRNA levels do not necessarily predict protein levels. In order to improve the knowledge of host response and viral pathogenesis of highly virulent Chinese-type PRRSV (H-PRRSV) and Non-high-pathogenic North American-type PRRSV strains (N-PRRSV), we analyzed the protein expression changes of H-PRRSV and N-PRRSV infected lungs compared with those of uninfected negative control, and identified a series of proteins related to host response and viral pathogenesis.</p> <p>Results</p> <p>According to differential proteomes of porcine lungs infected with H-PRRSV, N-PRRSV and uninfected negative control at different time points using two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) and mass spectrometry identification, 45 differentially expressed proteins (DEPs) were identified. These proteins were mostly related to cytoskeleton, stress response and oxidation reduction or metabolism. In the protein interaction network constructed based on DEPs from lungs infected with H-PRRSV, HSPA8, ARHGAP29 and NDUFS1 belonged to the most central proteins, whereas DDAH2, HSPB1 and FLNA corresponded to the most central proteins in those of N-PRRSV infected.</p> <p>Conclusions</p> <p>Our study is the first attempt to provide the complex picture of pulmonary protein expression during H-PRRSV and N-PRRSV infection under the in vivo environment using 2D-DIGE technology and bioinformatics tools, provides large scale valuable information for better understanding host proteins-virus interactions of these two PRRSV strains.</p