Developing a regional scale construction and demolition waste landfill landslide risk rapid assessment approach.

In recent years, construction and demolition waste (CDW) landfills landslide accidents have occurred globally, with consequences varying due to surrounding environmental factors. Risk monitoring is crucial to mitigate these risks effectively. Existing studies mainly focus on improving risk assessment accuracy for individual landfills, lacking the ability to rapidly assess multiple landfills at a regional scale. This study proposes an innovative approach utilizing deep learning models to quickly locate suspected landfills and develop risk assessment models based on surrounding environmental factors. Shenzhen, China, with significant CDW disposal pressure, is chosen as the empirical research area. Empirical findings from this study include: (1) the identification of 52 suspected CDW landfills predominantly located at the administrative boundaries within Shenzhen, specifically in the Longgang, Guangming, and Bao'an districts; (2) landfills at the lower risk of landslides are typically found near the northern borders adjacent to cities like Huizhou and Dongguan; (3) landfills situated at the internal administrative junctions generally exhibit higher landslide risks; (4) about 70 % of these landfills are high-risk, mostly located in densely populated areas with substantial rainfall and complex topographies. This study advances landfill landslide risk assessments by integrating computer vision and environmental analysis, providing a robust method for governments to rapidly evaluate risks at CDW landfills regionally. The adaptable models can be customized for various urban and broadened to general landfills by adjusting specific indicators, enhancing environmental safety protocols and risk management strategies effectively.

Exploring the environmental risks and seasonal variations of potentially toxic elements (PTEs) in fine road dust in resource-based cities based on Monte Carlo simulation, geo-detector and random forest model.

The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM10) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM10 and PM2.5) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg.

Cost-related medication nonadherence in adults with COPD in the United States 2013-2020.

BACKGROUND: Cost-related medication nonadherence (CRN) is associated with poor prognosis among patients with chronic obstructive pulmonary disease (COPD), a population that requires long-term treatment for secondary prevention. In this study, we aimed to estimate the prevalence and sociodemographic characteristics of CRN in individuals with COPD in the US. METHODS: In a nationally representative survey of US adults in the National Health Interview Survey (2013-2020), we identified individuals aged ≥18 years with a self-reported history of COPD. Cross-sectional study. RESULTS: Of the 15,928 surveyed individuals, a weighted 18.56% (2.39 million) reported experiencing CRN, including 12.50% (1.61 million) missing doses, 13.30% (1.72 million) taking lower than prescribed doses, and 15.74% (2.03 million) delaying filling prescriptions to save costs. Factors including age < 65 years, female sex, low family income, lack of health insurance, and multimorbidity were associated with CRN. CONCLUSIONS: In the US, one in six adults with COPD reported CRN. The influencing factors of CRN are multifaceted and necessitating more rigorous research. Targeted interventions based on the identified influencing factors in this study are recommended to enhance medication adherence among COPD patients.

Safety assessment, whole genome sequence, and metabolome analysis of Streptococcus thermophilus CICC 20372 for bone cement fermentation.

Bone is a kind of meat processing by-product with high nutritional value but low in calorie, which is a typical food in China and parts of East Asian countries. Microbial fermentation by lactic acid bacteria showed remarkable advantages to increase the absorption of nutrients from bone cement by human body. Streptococcus thermophilus CICC 20372 is proven to be a good starter for bone cement fermentation. No genes encoding virulence traits or virulence factors were found in the genome of S. thermophilus CICC 20372 by a thorough genomic analysis. Its notable absence of antibiotic resistance further solidifies the safety. Furthermore, the genomic analysis identified four types of gene clusters responsible for the synthesis of antimicrobial metabolites. A comparative metabolomic analysis was performed by cultivating the strain in bone cement at 37 °C for 72 h, with the culture in de Man, Rogosa, and Sharpe (MRS) medium as control. Metabolome analysis results highlighted the upregulation of pathways involved in 2-oxocarboxylic acid metabolism, ATP-binding cassette (ABC) transporters, amino acid synthesis, and nucleotide metabolism during bone cement fermentation. S. thermophilus CICC 20372 produces several metabolites with health-promoting function during bone cement fermentation, including indole-3-lactic acid, which is demonstrated ameliorative effects on intestinal inflammation, tumor growth, and gut dysbiosis. In addition, lots of nucleotide and organic acids were accumulated at higher levels, which enriched the fermented bone cement with a variety of nutrients. Collectively, these features endow S. thermophilus CICC 20372 a great potential strain for bone food processing.

Investigations of Water Transport in Shale Reservoir with Dual-Wettability by Using Monte Carlo Method.

How liquids transport in the shale system has been the focus because of fracturing fluid loss. In this study, a single-nanopore model is established for liquid transport in shale while considering the slip effect and effective viscosity of confined fluids. Then, the fractal Monte Carlo (FMC) model is proposed to upscale the single-pore model into shale porous media. The effects of different transport mechanisms, shale wettability, and pore characteristic parameters on confined liquid flow in shale rock are investigated. Results show that FMC permeabilities are 2-3 orders of magnitude larger than intrinsic and slip-corrected permeabilities in organic matter. However, the slip effect and effective viscosity have little influence on water flow in inorganic matter. With the contact angle of organic pore (θom) increasing and contact angle of inorganic pore (θin) decreasing, the effective permeability of the whole shale matrix grows in number. The enhancement factor in the situation of θom = 170° and θin = 20° is 4 orders of magnitude larger than the case of θom = 130° and θin = 40°, although the close effective macroscopic contact angle (θeff = 80°) occurs in these two cases, which indicates that shale microscopic wettability has a significant impact on the confined liquid transport. Moreover, with the increase of porosity and maximum pore diameters, shale permeability increases rapidly, but the enhancement factor has the opposite trend. Compared with the tiny impact of the variance of minimum inorganic pore diameters, minimum organic pore diameters have more significant impacts on liquid flow in shale systems, and the enhancement factor also rapidly increases up to 30 times for the case of 0.5 nm because of the strong slip effect.

SIGHR: Side information guided high-dimensional regression.

In this work, we develop a novel Bayesian regression framework that can be used to complete variable selection in high dimensional settings. Unlike existing techniques, the proposed approach can leverage side information to inform about the sparsity structure of the regression coefficients. This is accomplished by replacing the usual inclusion probability in the spike and slab prior with a binary regression model which assimilates this extra source of information. To facilitate model fitting, a computationally efficient and easy to implement Markov chain Monte Carlo posterior sampling algorithm is developed via carefully chosen priors and data augmentation steps. The finite sample performance of our methodology is assessed through numerical simulations, and we further illustrate our approach by using it to identify genetic markers associated with the nicotine metabolite ratio; a key biological marker associated with nicotine dependence and smoking cessation treatment.

Source-specific probabilistic risk evaluation of potentially toxic metal(loid)s in fine dust of college campuses based on positive matrix factorization and Monte Carlo simulation.

Contamination, hazard level and source of 10 widely concerned potentially toxic metal(loid)s (PTMs) Co, As, Pb, Cr, Cu, Zn, Ni, Mn, Ba, and V in fine dust with particle size below 63 µm (FD63) were investigated to assess the environmental quality of college campuses and influencing factors. PTMs sources were qualitatively analyzed using statistical methods and quantitatively apportioned using positive matrix factorization. Probabilistic contamination degrees of PTMs were evaluated using enrichment factor and Nemerow integrated enrichment factor. Eco-health risk levels of content-oriented and source-oriented for PTMs were evaluated using Monte Carlo simulation. Mean levels of Zn (643.8 mg kg-1), Pb (146.0 mg kg-1), Cr (145.9 mg kg-1), Cu (95.5 mg kg-1), and Ba (804.2 mg kg-1) in FD63 were significantly larger than soil background values. The possible sources of the concerned PTMs in FD63 were traffic non-exhaust emissions, natural source, mixed source (auto repair waste, paints and pigments) and traffic exhaust emissions, which accounted for 45.7%, 25.4%, 14.5% and 14.4% of total PTMs contents, respectively. Comprehensive contamination levels of PTMs were very high, mainly caused by Zn pollution and non-exhaust emissions. Combined ecological risk levels of PTMs were low and moderate, chiefly caused by Pb and traffic exhaust emissions. The non-cancer risks of the PTMs in FD63 to college students fell within safety level, while the carcinogenic PTMs in FD63 had a certain cancer risks to college students. The results of source-specific health risk assessment indicated that Cr and As were the priority PTMs, and the mixed source was the priority pollution source of PTMs in FD63 from college campuses, which should be paid attention to by the local government.

Optical Coherence Tomography Assessment of Coronary Lesions Associated With Microvascular Dysfunction in ST-Segment Elevation Myocardial Infarction.

BACKGROUND: Microvascular reperfusion following percutaneous coronary intervention (PCI) is associated with the prognosis of patients with ST-segment elevation myocardial infarction (STEMI). We investigated how plaque characteristics detected by optical coherence tomography (OCT) in STEMI patients affect the status of the microcirculation during PCI.Methods and Results: This retrospective, single-center study was a post hoc analysis basedon the multicenter SALVAGE randomized control trial (NCT03581513) that enrolled 629 STEMI patients, and finally we enrolled 235 patients who underwent PCI and pre-intervention OCT. Microvascular perfusion was evaluated using the Thrombolysis in Myocardial Infarction (TIMI) myocardial perfusion frame count (TMPFC). Patients were divided into 3 groups based on the change in TMPFC from before to after PCI: improving TMPFC (n=11; 4.7%), stable TMPFC (n=182; 77.4%), and worsening TMPFC group (n=42; 17.9%). The proportion of patients with a microcirculation dysfunction before reperfusion was 11.9%, which increased significantly by (P=0.079) 8.5% to 20.4% after reperfusion. Compared with plaque characteristics in the stable and worsening TMPFC groups, the improving TMPFC group had fewer thrombi (90.7% and 90.5% vs. 89.4%, respectively; P=0.018), a lower proportion of plaque rupture (66.5% and 66.3% vs. 54.5%, respectively; P=0.029), and a lower proportion of lipid-rich plaques (89.6% and 88.1% vs. 63.6%, respectively; P=0.036). CONCLUSIONS: PCI may not always achieve complete myocardial reperfusion. Thrombi, plaque rupture, and lipid-rich plaques detected by OCT can indicate microcirculation dysfunction during the reperfusion period.

Correction: Deng et al. Assessment of the Macrophage Scavenger Receptor CD163 in Mediating Glaesserella parasuis Infection of Host Cells. Vet. Sci. 2023, 10, 235.

In the original publication [...].

Cost-related medication nonadherence in US adults with asthma: The National Health Interview Survey, 2013-2020.

BACKGROUND: Asthma is a chronic disease that needs long-term control for secondary prevention. Health-related expenditures resulting from asthma are rising in the United States, and medication nonadherence is associated with adverse health outcomes in patients with asthma. OBJECTIVE: To estimate the prevalence and risk factors of cost-related medication nonadherence (CRN) in individuals with asthma in the United States. METHODS: We identified patients aged above or equal to 18 years with a history of asthma in nationally representative cross-sectional data, the National Health Interview Survey 2013 to 2020. Participants were considered to have experienced CRN if at any time in the 12 months they reported skipping doses, taking less medication, or delaying filling a prescription to save money. The weighted prevalence of CRN was estimated overall and by subgroups. Logistic regression was used to identify CRN-related characteristics. RESULTS: Of the 26,539 National Health Interview Survey participants with a history of asthma, 4360 (15.77%; representing 3.92 million of the US population) reported CRN, with 10.12% (weighted 2.51 million) of patients skipping doses to save money, 10.82% (weighted 2.69 million) taking less medication to save money, and 13.35% (weighted 3.31 million) delaying filling a prescription to save money. The subgroups young, women, low income, no health insurance, currently smoking, and with comorbidities had a higher prevalence of CRN. The results of this sensitivity analysis did not differ from the overall results. CONCLUSION: In the United States, 1 in 6 adults with a history of asthma is nonadherence with medications due to costs. Removing financial barriers to accessing medication can improve medication adherence in patients with asthma.

Ascertaining priority control pollution sources and target pollutants in toxic metal risk management of a medium-sized industrial city.

Re-suspended surface dust (RSD) often poses higher environmental risks due to its specific physical characteristics. To ascertain the priority pollution sources and pollutants for the risk control of toxic metals (TMs) in RSD of medium-sized industrial cities, this study took Baotou City, a representative medium-sized industrial city in North China, as an example to systematically study TMs pollution in RSD. The levels of Cr (242.6 mg kg-1), Pb (65.7 mg kg-1), Co (54.0 mg kg-1), Ba (1032.4 mg kg-1), Cu (31.8 mg kg-1), Zn (81.7 mg kg-1), and Mn (593.8 mg kg-1) in Baotou RSD exceeded their soil background values. Co and Cr exhibited significant enrichment in 94.0 % and 49.4 % of samples, respectively. The comprehensive pollution of TMs in Baotou RSD was very high, mainly caused by Co and Cr. The main sources of TMs in the study area were industrial emissions, construction, and traffic activities, accounting for 32.5, 25.9, and 41.6 % of the total TMs respectively. The overall ecological risk in the study area was low, but 21.5 % of samples exhibited moderate or higher risk. The carcinogenic risks of TMs in the RSD to local residents and their non-carcinogenic risks to children cannot be ignored. Industrial and construction sources were priority pollution sources for eco-health risks, with Cr and Co being the target TMs. The south, north and west of the study area were the priority control areas for TMs pollution. The probabilistic risk assessment method combining of Monte Carlo simulation and source analysis can effectively identify the priority pollution sources and pollutants. These findings provide scientific basis for TMs pollution control in Baotou and constitute a reference for environmental management and protection of residents' health in other similar medium-sized industrial cities.

Assessment of knowledge, cultural beliefs, and behavior regarding medication safety among residents in Harbin, China.

BACKGROUND: Medication misuse or overuse is significantly associated with poor health outcomes. Information regarding the knowledge, cultural beliefs, and behavior about medication safety in the general population is important. AIM: To conduct a survey on medication habits and explored the potential factors impacting medication safety. METHODS: The current survey included adults from 18 districts and counties in Harbin, China. A questionnaire on medication safety was designed based on knowledge, cultural beliefs, and behavior. Both univariate and multivariate analyses were used to explore the factors that impacted medication safety. RESULTS: A total of 394 respondents completed the questionnaires on medication safety. The mean scores for knowledge, cultural beliefs, and behavior about medication safety were 59.41 ± 19.33, 40.66 ± 9.24, and 60.97 ± 13.69, respectively. The medication knowledge score was affected by age (P = 0.044), education (P < 0.001), and working status (P = 0.015). Moreover, the cultural beliefs score was significantly affected by education (P < 0.001). Finally, education (P = 0.003) and working status (P = 0.011) significantly affected the behavior score. CONCLUSION: The knowledge, cultural beliefs, and behavior about medication safety among the general population was moderate. Health education should be provisioned for the elderly, individuals with a low education level, and the unemployed to improve medication safety in Harbin, China.

Assessment of the Macrophage Scavenger Receptor CD163 in Mediating Glaesserella parasuis Infection of Host Cells.

The macrophage CD163 surface glycoprotein is a member of the SRCR family class B, which has been identified as the key trigger in host-pathogen interactions, but its specific roles in sensing Glaesserella parasuis (G. parasuis) infection are largely unknown. Here, we investigated porcine CD163 in mediating the adhesion and immune response of G. parasuis using in vitro host-bacteria interaction models. CD163-overexpressing Chinese hamster ovary K1 cells (CHO-K1) showed obvious subcellular localization in the cytoplasm, especially in the cytomembrane. Although detection using scanning electron microscopy (SEM) confirmed the bacterial adhesion, there was no significant difference in the adhesion of G. parasuis to CHO-K1 cells between the presence and absence of CD163. In addition, similar results were observed in 3D4/21 cells. Meanwhile, bindings of G. parasuis to nine synthetic peptides, the bacterial binding motifs within SRCR domains of CD163, were weak based on a solid-phase adhesion assay and agglutination assay. Moreover, CD163 had no effect on the expression of G. parasuis-induced inflammatory cytokines (IL-6, INF-γ, IL-10, IL-4 and TGF-ß) in CHO-K1 cells. In conclusion, these findings indicate that porcine CD163 plays a minor role in sensing G. parasuis infection.

Predictive Value of Cardiovascular Health Score for Health Outcomes in Patients with PCI: Comparison between Life's Simple 7 and Life's Essential 8.

The American Heart Association recently published an updated algorithm for quantitative assessments of cardiovascular health (CVH) metrics, namely Life's Essential 8 (LE8). This study aimed to compare the predictive value between Life's Simple 7 (LS7) and LE8 and predict the likelihood of major adverse cardiac events (MACEs) in patients undergoing percutaneous coronary intervention (PCI) to determine the utility of the LE8 in predicting CVH outcomes. A total of 339 patients with acute coronary syndrome (ACS) who had undergone PCI were enrolled to assess the CVH scores using the LS7 and LE8. Multivariable Cox regression analysis was employed to evaluate the predictive value of the two different CVH scoring systems at 2 years for MACEs. Multivariable Cox regression analysis revealed that both the LS7 and LE8 scores were protective factors for MACEs (HR = 0.857, [95%CI: 0.78-0.94], HR = 0.964, [95%CI: 0.95-0.98]; p < 0.05, respectively). Receiver operator characteristic analysis indicated that the area under the curve (AUC) of LE8 was higher than that of LS7 (AUC: 0.662 vs. 0.615, p < 0.05). Lastly, in the LE8 score, diet, sleep health, serum glucose levels, nicotine exposure, and physical activity were found to be correlated with MACEs (HR = 0.985, 0.988, 0.993, 0.994, 0.994, respectively). Our study established that LE8 is a more reliable assessment system for CVH. This population-based prospective study reports that an unfavorable cardiovascular health profile is associated with MACEs. Future research is warranted to evaluate the effectiveness of optimizing diet, sleep health, serum glucose levels, nicotine exposure, and physical activity in reducing the risk of MACEs. In conclusion, our findings corroborated the predictive value of Life's Essential 8 and provided further evidence for the association between CVH and the risk of MACEs.

Metabolic Engineering of Escherichia coli for High-Level Production of (R)-Acetoin from Low-Cost Raw Materials.

Acetoin is an important four-carbon platform chemical with versatile applications. Optically pure (R)-acetoin is more valuable than the racemate as it can be applied in the asymmetric synthesis of optically active α-hydroxy ketone derivatives, pharmaceuticals, and liquid crystal composites. As a cytotoxic solvent, acetoin at high concentrations severely limits culture performance and impedes the acetoin yield of cell factories. In this study, putative genes that may improve the resistance to acetoin for Escherichia coli were screened. To obtain a high-producing strain, the identified acetoin-resistance gene was overexpressed, and the synthetic pathway of (R)-acetoin was strengthened by optimizing the copy number of the key genes. The engineered E. coli strain GXASR-49RSF produced 81.62 g/L (R)-acetoin with an enantiomeric purity of 96.5% in the fed-batch fermentation using non-food raw materials in a 3-L fermenter. Combining the systematic approach developed in this study with the use of low-cost feedstock showed great potential for (R)-acetoin production via this cost-effective biotechnological process.

Assessment of stromal SCD-induced drug resistance of PDAC using 3D-printed zPDX model chips.

Lipid metabolism is extensively reprogrammed in pancreatic ductal adenocarcinoma (PDAC). Stearoyl-coenzyme A desaturase (SCD) is a critical lipid regulator that was unexplored in PDAC. Here, we characterized the existence of cancer-associated fibroblasts (CAFs) with high SCD expression, and revealed them as an unfavorable prognostic factor. Therefore, primary CAFs and pancreatic cancer cells were harvested and genetically labeled. The mixture of CAFs and cancer cells were co-injected into scd-/-; prkdc-/-, or hIGF1/INS-expressing zebrafish to generate patient-derived xenograft models (zPDX). The models were aligned in 3D-printed chips for semi-automatic drug administration and high-throughput scanning. The results showed that chaperoning of the SCD-high CAFs significantly improved the drug resistance of pancreatic cancer cells against gemcitabine and cisplatin, while the administration of SCD inhibitors neutralized the protective effect. Our studies revealed the prognostic and therapeutic value of stromal SCD in PDAC, and proposed the application of zPDX model chips for drug testing.

Automatic assessment of calcified plaque and nodule by optical coherence tomography adopting deep learning model.

Optical coherence tomography (OCT) has become the best imaging tool to assess calcified plaque and nodule. However, every OCT pullback has numerous images, and artificial analysis requires too much time and energy. Thus, it is unsuitable for clinical application. This study aimed to develop and validate an automatic assessment of calcified plaque and nodule by OCT using deep-learning model. The OCT images of calcified plaque and nodule were labeled by two expert readers based on the consensus. A deep-learning model with a MultiScale and MultiTask u-net network (MS-MT u-net) was developed. Then, with the ground truth labeled by expert readers as reference, the diagnostic accuracy and agreement of the model was validated. For the pixelwise evaluation of calcified plaque, the model had a high performance with precision (93.95%), recall (88.95%), and F1 score (91.38%). For the lesion-level evaluation of calcified plaque, the quantitative metrics by the model excellently correlated with the ground truth (calcium score, r = 0.90, p < 0.01; calcified volume, r = 0.99, p < 0.01). For calcified nodules, the model showed excellent diagnostic performance including sensitivity (91.7%), specificity (89.3%), and accuracy (91.0%). We developed a novel deep-learning model to identify the attributes of calcified plaque and nodule. This model provided excellent diagnostic accuracy and agreement with the ground truth, thereby reducing the subjectivity of manual measurements and substantially saving time. These findings can help practitioners efficiently adopt appropriate therapeutic strategies to treat calcified lesions.

Risk Stratification in Acute Coronary Syndrome by Comprehensive Morphofunctional Assessment With Optical Coherence Tomography.

Background: Artificial intelligence enables simultaneous evaluation of plaque morphology and computational physiology from optical coherence tomography (OCT). Objectives: This study sought to appraise the predictive value of major adverse cardiovascular events (MACE) by combined plaque morphology and computational physiology. Methods: A total of 604 patients with acute coronary syndrome who underwent OCT imaging in ≥1 nonculprit vessel during index coronary angiography were retrospectively enrolled. A novel morphologic index, named the lipid-to-cap ratio (LCR), and a functional parameter to evaluate the physiologic significance of coronary stenosis from OCT, namely, the optical flow ratio (OFR), were calculated from OCT, together with classical morphologic parameters, like thin-cap fibroatheroma (TCFA) and minimal lumen area. Results: The 2-year cumulative incidence of a composite of nonculprit vessel-related cardiac death, cardiac arrest, acute myocardial infarction, and ischemia-driven revascularization (NCV-MACE) at 2 years was 4.3%. Both LCR (area under the curve [AUC]: 0.826; 95% CI: 0.793-0.855) and OFR (AUC: 0.838; 95% CI: 0.806-0.866) were superior to minimal lumen area (AUC: 0.618; 95% CI: 0.578-0.657) in predicting NCV-MACE at 2 years. Patients with both an LCR of >0.33 and an OFR of ≤0.84 had significantly higher risk of NCV-MACE at 2 years than patients in whom at least 1 of these 2 parameters was normal (HR: 42.73; 95% CI: 12.80-142.60; P < 0.001). The combination of thin-cap fibroatheroma and OFR also identified patients at higher risk of future events (HR: 6.58; 95% CI: 2.83-15.33; P < 0.001). Conclusions: The combination of LCR with OFR permits the identification of a subgroup of patients with 43-fold higher risk of recurrent cardiovascular events in the nonculprit vessels after acute coronary syndrome.

Assessment of Hematologic and Biochemical Parameters for Healthy Commercial Pigs in China.

Hematologic and biochemical data are useful for indicating disease diagnosis and growth performance in swine. However, the assessment of these parameters in healthy commercial pigs is rare in China. Thus, blood samples were collected from 107 nursery pigs and 87 sows and were analyzed for 25 hematologic and 14 biochemical variables. After the rejection of the outliers and the detection of the data distribution, the correlations between the blood parameters were analyzed and the hematologic/biochemical RIs were preliminarily established using the 95% percentile RI. Correlation analysis showed that albumin was the hub parameter among the blood parameters investigated, and genes overlapping with key correlated variables were discovered. Most of the hematologic and biochemical parameters were significantly different between nursery pigs and sows. The 95% RIs of white blood cells and red blood cells were 7.18-24.52 × 109/L and 5.62-7.84 × 1012/L, respectively, for nursery pigs, but 9.34-23.84 × 109/L and 4.98-8.29 × 1012/L for sows. The 95% RIs of total protein and albumin were 43.16-61.23 g/dL and 19.35-37.86 g/dL, respectively, for nursery pigs, but 64.96-88.68 g/dL and 31.91-43.28 g/dL for sows. In conclusion, our study highlights the variability in blood parameters between nursery pigs and sows and provides fundamental data for the health monitoring of commercial pigs in China.