Advanced Receptor Models for Exploiting Highly Time Resolved Data Acquired in the EPA Supersite Project

Receptor models have been widely used in air quality studies to identify pollution sources and estimate their contributions. A common problem for most current receptor models is insufficient consideration of realistic constraints such as can be obtained from emission inventories, chemical composition profiles of the sources, and the physics of plume dispersion. In addition, poor resolving of collinear sources was often found. With the high quality time-, composition-, and size-resolved measurements during the EPA Supersite project, efforts towards resolving nearby industrial sources were made by combinative use of Positive Matrix Factorization (PMF) and the Pseudo-Deterministic Receptor Model (PDRM). The PMF modeling of Baltimore data in September 2001 revealed coal-fired and oil-fired power plants (CFPP and OFPP, respectively) with significant cross contamination, as indicated by the high Se/Ni ratio in the OFPP profile. Nevertheless, the PMF results provided a good estimate of background and the PMF-constrained emission rates well seeded the trajectory-driven PDRM modeling. Using NOx as the tracer gas for χ/Q tuning, ultimately resolved emissions from individual stacks exhibited acceptable tracer ratios and the emission rates of metals generally agreed with the TRI estimates. This approach was later applied to two metal pollution episodes in St. Louis during in November 2001 and March 2002 and met a similar success. As NOx measurements were unavailable at those metal-production facilities, highly-specific tracer metals (i.e., Cd, Zn, and Cu) for the corresponding units were used to tune χ/Qs and their contributions were well resolved with the PMF-seeded PDRM. Opportunistically a PM2.5 excursion during a windless morning in November 2002 allowed the extraction of an in-situ profile of vehicular emissions in Baltimore. The profiles obtained by direct peak observation, windless model linear regression (WMA), PMF, and UNMIX were comparable and the WMA profile showed the best predictions for non-traffic tracers. Besides, an approach to evaluate vehicular emission factors was developed by receptor measurements under windless conditions. Using SVOC tracers, seasonal variations of traffic and other sources including coal burning, heating, biomass burning, and vegetation were investigated by PMF and in particular the November traffic profile was consistent with the WMA profile obtained earlier

The Change of Systemic Immune-Inflammation Index Independently Predicts Survival of Colorectal Cancer Patients after Curative Resection

Background. The systemic immune-inflammation index (SII) has an important role in predicting survival in some solid tumors. However, little information is available concerning the change of the SII (∆SII) in colorectal cancer (CRC) after curative resection. This study was designed to evaluate the role of ∆SII in CRC patients who received surgery. Methods. A total 206 patients were enrolled in this study. Clinicopathologic characteristics and survival were assessed. The relationships between overall survival (OS), disease-free survival (DFS), and ∆SII were analyzed with both univariate Kaplan-Meier and multivariate Cox regression methods. Results. Based on the patient data, the receiver operating characteristic (ROC) optimal cutoff value of ∆SII was 127.7 for OS prediction. The 3-year and 5-year OS rates, respectively, were 60.4% and 36.7% in the high-∆SII group (>127.7) and 87.6% and 79.8% in the low-∆SII group (≤127.7). The 3-year and 5-year DFS rates, respectively, were 54.1% and 34.1% in the high-∆SII group and 80.3% and 78.5% in the low-∆SII group. In the univariate analysis, smoking, pathological stages III-IV, high-middle degree of differentiation, lymphatic invasion, vascular invasion, and the high-ΔSII group were associated with poor OS. Adjuvant therapy, pathological stages III-IV, vascular invasion, and ΔSII were able to predict DFS. Multivariate analysis revealed that pathological stages III-IV (HR=0.442, 95% CI=0.236-0.827, p=0.011), vascular invasion (HR=2.182, 95% CI=1.243-3.829, p=0.007), and the high-ΔSII group (HR=4.301, 95% CI=2.517-7.350, p<0.001) were independent predictors for OS. Adjuvant therapy (HR=0.415, 95% CI=0.250-0.687, p=0.001), vascular invasion (HR=3.305, 95% CI=1.944-5.620, p<0.001), and the high-ΔSII group (HR=4.924, 95% CI=2.992-8.102, p<0.001) were significant prognostic factors for DFS. Conclusions. The present study demonstrated that ∆SII was associated with the clinical outcome in CRC patients undergoing curative resection, supporting the role of ∆SII as a prognostic biomarker

Structural basis for bacterial lipoprotein relocation by the transporter LolCDE

Lipoproteins in the outer membrane of Gram-negative bacteria are involved in various vital physiological activities, including multidrug resistance. Synthesized in the cytoplasm and matured in the inner membrane, lipoproteins must be transported to the outer membrane through the Lol pathway mediated by the ATP-binding cassette transporter LolCDE in the inner membrane via an unknown mechanism. Here, we report cryo-EM structures of Escherichia coli LolCDE in apo, lipoprotein-bound, LolA-bound, ADP-bound and AMP-PNP-bound states at a resolution of 3.2–3.8 Å, covering the complete lipoprotein transport cycle. Mutagenesis and in vivo viability assays verify features of the structures and reveal functional residues and structural characteristics of LolCDE. The results provide insights into the mechanisms of sorting and transport of outer-membrane lipoproteins and may guide the development of novel therapies against multidrug-resistant Gram-negative bacteria

Structural insights into outer membrane asymmetry maintenance in Gram-negative bacteria by MlaFEDB

The highly asymmetric outer membrane of Gram-negative bacteria functions in the defense against cytotoxic substances, such as antibiotics. The Mla pathway maintains outer membrane lipid asymmetry by transporting phospholipids between the inner and outer membranes. It comprises six Mla proteins, MlaFEDBCA, including the ABC transporter MlaFEDB, which functions via an unknown mechanism. Here we determine cryo-EM structures of Escherichia coli MlaFEDB in an apo state and bound to phospholipid, ADP or AMP-PNP to a resolution of 3.3–4.1 Å and establish a proteoliposome-based transport system that includes MlaFEDB, MlaC and MlaA–OmpF to monitor the transport direction of phospholipids. In vitro transport assays and in vivo membrane permeability assays combined with mutagenesis identify functional residues that not only recognize and transport phospholipids but also regulate the activity and structural stability of the MlaFEDB complex. Our results provide mechanistic insights into the Mla pathway, which could aid antimicrobial drug development