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Abstract
This study was performed to clarify the transfer and final end of lipofuscin substances that have been formed in cardiomyocytes. The hearts of BALB/c mice were obtained for resin embedding and ultra-thin sectioning. The specimens were observed under a transmission electron microscope, and the images were acquired using an XR401 side-insertion device. Lipofuscin granules are found abundantly in myocardial cells. Cardiomyocytes can excrete lipofuscin granules into the myocardial interstitium using capsule-like protrusions that are formed on the sarcolemma. These granules enter the myocardial interstitium and can be de-aggregated to form membrane-like garbage, which can pass from the myocardial stroma into the lumen of the vessel through its walls. Smaller lipofuscin granules can pass through the walls of the vessels and enter the blood vessel lumen through the capillary endothelial cells. When the extended cytoplasmic end of macrophages and fibroblasts fuse with the endothelial cells, the lipofuscin granules or clumps in the myocardial interstitium are transported to the capillary walls, and then, are released into the lumen of the blood vessel by the endothelial cells. The myocardial tissues of mice may have the ability to eliminate the lipofuscin produced in the cardiomyocytes into the myocardial blood circulation.

Background: Staphylococcus aureus is among the most common causes of health care-and community-associated infections worldwide. The distributions of different S. aureus clones change over time and also vary geographically. The purpose of this study was to determine the molecular type and antimicrobial resistance profiles of clinical S. aureus strains isolated in Urumqi, Northwestern China. ; Methods: A total of 605 clinical S. aureus isolates were collected from Xinjiang Military General Hospital, in Urumqi. Protein A-encoding (spa) typing, multilocus sequence typing, staphylococcal chromosomal cassette mec typing, Panton-Valentine leucocidin (pvl) gene detection, and antimicrobial resistance profiling were performed. ; Results: Among these strains, 271 isolates (44.7%) were methicillin-resistant S. aureus (MRSA) and 334 (55.3%) were methicillin-susceptible S. aureus (MSSA). The MRSA strains consisted of 22 spa types and 14 sequence types (STs). ST239-MRSA-III-t030 (73.1%, 198/271) and ST59-MRSA-IV-t437 (11.8%, 32/271) were the most common, and ST22-MRSA-IV-t309 was the rarest (2.02%, 6/271). The MSSA strains consisted of 93 spa types and 29 STs. ST22, ST121, ST398, ST5, ST7, ST188, and ST15 were the main MSSA STs, and ST22-MSSA-t309 was most common (26.0%, 87/334). The pvl gene was present in 20.3% of all S. aureus strains, and 80.8% (88/99) of ST22-MSSA strains harbored the pvl gene. A total of 85.7% pvl-positive ST22-MSSA strains were spa t309 (85/99), and 87.5% of pvl-positive ST22-MSSA strains were from abscesses or wounds (skin and soft tissue infections). All ST239-MRSA strains were resistant to gentamicin (GEN), levofloxacin (LEV), ciprofloxacin (CIP), moxifloxacin (MXF), rifampicin (RIF), and tetracycline (TET). Among the ST59-MRSA strains, over 70.0% were resistant to erythromycin (ERY), clindamycin (CLI), and TET. ST22-MSSA remained susceptible to most antibiotics, but was resistant to PEN (97.0%), ERY (57.6%), and CLI (15.2%). ; Conclusion: Our major results indicated that the antimicrobial resistance profiles and pvl genes of S. aureus isolates from Urumqi were closely associated with clonal lineage. ST239-MRSA-III-t030 and pvl-positive ST22-MSSA-t309 were the most common clones in this region of Northwestern China. ; Department of Applied Biology and Chemical Technology ; 201909 bcrc ; published_final

This paper offers a characterization of fundamental limits on the classification and reconstruction of high-dimensional signals from low-dimensional features, in the presence of side information. We consider a scenario where a decoder has access both to linear features of the signal of interest and to linear features of the side information signal; while the side information may be in a compressed form, the objective is recovery or classification of the primary signal, not the side information. The signal of interest and the side information are each assumed to have (distinct) latent discrete labels; conditioned on these two labels, the signal of interest and side information are drawn from a multivariate Gaussian distribution that correlates the two. With joint probabilities on the latent labels, the overall signal-(side information) representation is defined by a Gaussian mixture model. By considering bounds to the misclassification probability associated with the recovery of the underlying signal label, and bounds to the reconstruction error associated with the recovery of the signal of interest itself, we then provide sharp sufficient and/or necessary conditions for these quantities to approach zero when the covariance matrices of the Gaussians are nearly low rank. These conditions, which are reminiscent of the well-known Slepian–Wolf and Wyner–Ziv conditions, are the function of the number of linear features extracted from signal of interest, the number of linear features extracted from the side information signal, and the geometry of these signals and their interplay. Moreover, on assuming that the signal of interest and the side information obey such an approximately low-rank model, we derive the expansions of the reconstruction error as a function of the deviation from an exactly low-rank model; such expansions also allow the identification of operational regimes, where the impact of side information on signal reconstruction is most relevant. Our framework, which offers a principled mechanism to integrate side information in high-dimensional data problems, is also tested in the context of imaging applications. In particular, we report state-of-the-art results in compressive hyperspectral imaging applications, where the accompanying side information is a conventional digital photograph. ; This work was supported in part by the (PIDDAC) for Future Health/Faculdade de Engenharia da Universidade do Porto under Grant NORTE-07-0124-FEDER-000068, funded by the Fundo Europeu de Desenvolvimento Regional through the Programa Operacional do Norte, in part by the National Funds, through FCT/MEC (PIDDAC), in part by the Royal Society International Exchanges Scheme under Grant IE120996, in part by AFOSR, in part by ARO, in part by DARPA, in part by DOE, in part by NGA, and in part by ONR. F. Renna was supported by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie under Grant 655282. M. R. D. Rodrigues was supported by EPSRC under Grant EP/K033166/1.

Improper domestic food handling in rural areas of China is an important public health issue leading to foodborne illness. However, the underlying factors responsible for poor domestic food hygiene practices have not been comprehensively studied. Here, a cross-sectional study was conducted in Anhui Province, China between 2015 - 2016, using a questionnaire to collect data from 819 respondents, selected using multistage cluster random sampling techniques. Multivariate logistic regression analysis was then used to assess the demographic factors associated with improper food handling. Results showed that 525 (64.1%) of respondents used improper food handling techniques. The factors associated with improper food handling included gender, age, education, income, and occupation. Males (vs. females), adults aged ≥ 50 years (vs. those aged 18 - 30 years), individuals with primary school education or lower (vs. individuals with a bachelor's degree or higher), individuals with annual incomes of < 4,387 USD (vs. income ≥ 13,161 USD), and workers (vs. other occupation groups) were more likely to report inappropriate food handling practices in rural areas. The results obtained from the present work may provide the basis for training in domestic food safety hygiene/handling practices in rural areas of China in order to reduce the incidence of foodborne illnesses.