Subclavian and internal jugular CVA routes have similar risks for catheter-related complications in long-term catheterization in cancer patients. Subclavian CVA is preferable to femoral CVA in short-term catheterization because of lower risks of catheter colonization and thrombotic complications. In short-term haemodialysis catheterization, femoral and internal jugular CVA routes have similar risks for catheter-related complications except internal jugular CVA routes are associated with higher risks of mechanical complications.

we found a graded independent relation between higher RDW and adverse outcomes in ICU patients. RDW has the potentially clinical utility to predict outcome in ICU patients.

IntroductionAlthough nonthyroidal illness syndrome is considered to be associated with adverse outcome in ICU patients, the performance of thyroid hormone levels in predicting clinical outcome in ICU patients is unimpressive. This study was conducted to assess the prognostic value of the complete thyroid indicators (free triiodothyronine (FT3), total triiodothyronine; free thyroxine, total thyroxine, thyroid-stimulating hormone and reverse triiodothyronine) in unselected ICU patients.MethodsA total of 480 consecutive patients without known thyroid diseases were screened for eligibility and followed up during their ICU stay. We collected each patient's baseline characteristics, including the Acute Physiology and Chronic Health Evaluation II (APACHE II) score and thyroid hormone, N-terminal pro-brain natriuretic peptide (NT-proBNP) and C-reactive protein (CRP) levels. The primary outcome was ICU mortality. Potential predictors were analyzed for possible association with outcomes. We also evaluated the ability of thyroid hormones together with APACHE II score to predict ICU mortality by calculation of net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices.ResultsAmong the thyroid hormone indicators, FT3 had the greatest power to predict ICU mortality, as suggested by the largest area under the curve (AUC) of 0.762 ± 0.028. The AUC for FT3 level was less than that for APACHE II score (0.829 ± 0.022) but greater than that for NT-proBNP level (0.724 ± 0.030) or CRP level (0.689 ± 0.030). Multiple regression analysis revealed that FT3 level (standardized β = -0.600, P = 0.001), APACHE II score (standardized β = 0.912, P < 0.001), NT-proBNP level (standardized β = 0.459, P = 0.017) and CRP level (standardized β = 0.367, P = 0.030) could independently predict primary outcome. The addition of FT3 level to APACHE II score gave an NRI of 54.29% (P < 0.001) and an IDI of 36.54% (P < 0.001). The level of FT3 was significantly correlated with NT-proBNP levels (r = -0.344, P < 0.001) and CRP levels (r = -0.408, P < 0.001).ConclusionIn unselected ICU patients, FT3 was the most powerful and only independent predictor of ICU mortality among the complete indicators. The addition of FT3 level to the APACHE II score could significantly improve the ability to predict ICU mortality.

BACKGROUND: The viral shedding duration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has not been fully defined. Consecutive detection of SARS-CoV-2 RNA from respiratory tract specimens is essential for determining duration of virus shedding and providing evidence to optimize the clinical management of coronavirus disease 2019 (COVID-19). RESEARCH QUESTION: What are the shedding durations of SARS-CoV-2 RNA in the upper and lower respiratory tract specimens? What are their associated risk factors? STUDY DESIGN AND METHODS: A total of 68 patients with COVID-19 admitted to Wuhan Taikang Tongji Hospital and Huoshenshan Hospital from February 10, 2020, to March 20, 2020, were recruited. Consecutive SARS-CoV-2 RNA detection from paired specimens of nasopharyngeal swab (NPS) and sputum were carried out. The clinical characteristics of patients were recorded for further analysis. RESULTS: SARS-CoV-2 RNA was detected from NPSs in 48 patients (70.6%), and from sputum specimens in 30 patients (44.1%). The median duration of viral shedding from sputum specimens (34 days; interquartile range [IQR], 24-40) was significantly longer than from NPSs (19 days; IQR, 14-25; P < .001). Elderly age was an independent factor associated with prolonged virus shedding time of SARS-CoV-2 (hazard ratio, 1.71; 95% CI, 1.01-2.93). It was noteworthy that in 9 patients, the viral RNA was detected in sputum after NPS turned negative. Chronic lung disease and steroids were associated with virus detection in sputum, and diabetes mellitus was associated with virus detection in both NPS and sputum. INTERPRETATION: These findings may impact a test based clearance discharge criteria given patients with COVID-19 may shed virus longer in their lower respiratory tracts, with potential implication for prolonged transmission risk. In addition, more attention should be given to elderly patients who might have prolonged viral shedding duration.

Passively-generated mobile phone data is emerging as a potential data source for transportation research and applications. Despite the large amount of studies based on the mobile phone data, only a few have reported the properties of such data, and documented how they have processed the data. In this paper, we describe two types of common mobile phone data: Call Details Record (CDR) data and sightings data, and propose a data processing framework and the associated algorithms to address two key issues associated with the sightings data: locational uncertainty and oscillation. We show the effectiveness of our proposed methods in addressing these two issues compared to the state of art algorithms in the field. We also demonstrate that without proper processing applied to the data, the statistical regularity of human mobility patterns—a key, significant trait identified for human mobility—is over-estimated. We hope this study will stimulate more studies in examining the properties of such data and developing methods to address them. Though not as glamorous as those directly deriving insights on mobility patterns (such as statistical regularity), understanding properties of such data and developing methods to address them is a fundamental research topic on which important insights are derived on mobility patterns.

Electrospinning is a technique for creating continuous nanofibrous networks that can architecturally be similar to the structure of extracellular matrix (ECM). However, the shrinkage of electrospun mats is unfavorable for the triggering of cell adhesion and further growth. In this work, electrospun PLGA nanofiber assemblies are utilized to create a scaffold. Aided by a polypropylene auxiliary supporter, the scaffold is able to maintain long-term integrity without dimensional shrinkage. This scaffold is also able to suspend in cell culture medium; hence, keratinocyte cells seeded on the scaffold are exposed to air as required in skin tissue engineering. Experiments also show that human skin keratinocytes can proliferate on the scaffold and infiltrate into the scaffold.

Nonsense-mediated mRNA decay (NMD) is a highly conserved post-transcriptional regulatory mechanism of gene expression in eukaryotes. Originally, NMD was identified as an RNA surveillance machinery in degrading ‘aberrant’ mRNA species with premature termination codons. Recent studies indicate that NMD regulates the stability of natural gene transcripts that play significant roles in cell functions. Although components and action modes of the NMD machinery in degrading its RNA targets have been extensively studied with biochemical and structural approaches, the biological roles of NMD remain to be defined. Stem cells are rare cell populations, which play essential roles in tissue homeostasis and hold great promises in regenerative medicine. Stem cells self-renew to maintain the cellular identity and differentiate into somatic lineages with specialized functions to sustain tissue integrity. Transcriptional regulations and epigenetic modulations have been extensively implicated in stem cell biology. However, post-transcriptional regulatory mechanisms, such as NMD, in stem cell regulation are largely unknown. In this paper, we summarize the recent findings on biological roles of NMD factors in embryonic and tissue-specific stem cells. Furthermore, we discuss the possible mechanisms of NMD in regulating stem cell fates.

Passively-generated data, such as GPS data and cellular data, bring tremendous opportunities for human mobility analysis and transportation applications. Since their primary purposes are often nontransportation related, the passively-generated data need to be processed to extract trips. Most existing trip extraction methods rely on data that are generated via a single positioning technology such as GPS or triangulation through cellular towers (thereby called single-sourced data), and methods to extract trips from data generated via multiple positioning technologies (or, multi-sourced data) are absent. And yet, multi-sourced data are now increasingly common. Generated using multiple technologies (e.g., GPS, cellular network-and WiFi-based), multi-sourced data contain high variances in their temporal and spatial properties. In this study, we propose a "Divide, Conquer and Integrate" (DCI) framework to extract trips from multi-sourced data. We evaluate the proposed framework by applying it to an app-based data, which is multi-sourced and has high variances in both location accuracy and observation interval (i.e. time interval between two consecutive observations). On a manually labeled sample of the app-based data, the framework outperforms the state-of-the-art SVM model that is designed for GPS data. The effectiveness of the framework is also illustrated by consistent mobility patterns obtained from the app-based data and an externally collected household travel survey data for the same region and the same period.