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Rapidly increasing urbanization in recent decades has elevated the subway as the primary public transportation mode in metropolitan areas. Indoor air quality (IAQ) inside subways is an important factor that influences the health of commuters and subway workers. This review discusses the subway IAQ in different cities worldwide by comparing the sources and abundance of particulate matter (PM2.5 and PM10) in these environments. Factors that affect PM concentration and chemical composition were found to be associated with the subway internal structure, train frequency, passenger volume, and geographical location. Special attention was paid to air pollutants, such as transition metals, volatile/semi-volatile organic compounds (VOCs and SVOCs), and bioaerosols, due to their potential roles in indoor chemistry and causing adverse health impacts. In addition, given that the IAQ of subway systems is a public health issue worldwide, we calculated the Gini coefficient of urban subway exposure via meta-analysis. A value of 0.56 showed a significant inequity among different cities. Developed regions with higher per capita income tend to have higher exposure. By reviewing the current advances and challenges in subway IAQ with a focus on indoor chemistry and health impacts, future research is proposed toward a sustainable urban transportation systems.

The concept of passenger-centric design has become increasingly significant in the intelligent automotive industry. Enhancing in-cabin thermal comfort while maintaining energy efficiency is crucial, and to this end, we leverage real-time passenger thermal sensation as a basis for HVAC control strategies. This study introduces a non-invasive, dual-phase prediction model that evaluates passenger thermal comfort by utilizing facial thermal imaging and environmental factors. The proposed model employs a deep learning neural network to extract pertinent features from the facial thermal images for an initial prediction. Then this prediction is refined by integrating it with environmental data through a machine learning algorithm, facilitating real-time personal thermal comfort assessment. Data collection for the model was performed across two distinct seasons, with 22 participants in summer and 18 in winter, gathering facial thermal images, environmental parameters, and thermal sensation votes to construct a comprehensive dataset. Analysis revealed a set of critical environmental factors that correlate strongly with thermal sensation votes, which were used as auxiliary features in the model. The performance of the proposed dual-phase approach, combining deep learning and machine learning techniques, demonstrated robust effectiveness on both summer and winter datasets. This substantiates the method's practicality for real-world application within vehicle environments.

Abstract Excessive alternating current (AC) arcs generated in electric systems will accumulate heat and easily cause fire. This paper studies the thermal characteristics of different numbers of AC arc plasma generated in a short gap of copper-cored wires in the air. The number of AC arcs is controlled in the AC arc experiment and an infrared thermal imager measures the temperature change at the specified position. Based on magnetohydrodynamics (MHD), a two-dimensional axisymmetric AC arc discharge numerical simulation model is established. The volt-ampere characteristic of the AC arc is used to solve the MHD simulation model to obtain the same 'zero current' characteristics as the real AC arc in the experiment. A large amount of heat accumulates in the electrode gaps when the arc generation, and then the heat dissipates in the 'zero current' stage. The continuously generated arc makes the temperature higher. The volume of the space area with a temperature higher than 10,000 K increases with the arc current, but is unrelated to the number of arcs. The volume of the space area with a temperature higher than 524.15 K and the temperature on the electrode are both positively correlated with the number of AC arcs and arc current. The results of this study can provide a reference for the detection standard of AC arc faults and the prevention of electrical fire.

Abstract Biosensors are powerful tools for detecting, real-time imaging, and quantifying molecules, but rapidly constructing diverse genetically encoded biosensors remains challenging. Here, we report a method to rapidly convert enzymes into genetically encoded circularly permuted fluorescent protein-based indicators to detect organic acids (GECFINDER). ANL superfamily enzymes undergo hinge-mediated ligand-coupling domain movement during catalysis. We introduce a circularly permuted fluorescent protein into enzymes hinges, converting ligand-induced conformational changes into significant fluorescence signal changes. We obtain 11 GECFINDERs for detecting phenylalanine, glutamic acid and other acids. GECFINDER-Phe3 and GECFINDER-Glu can efficiently and accurately quantify target molecules in biological samples in vitro. This method simplifies amino acid quantification without requiring complex equipment, potentially serving as point-of-care testing tools for clinical applications in low-resource environments. We also develop a GECFINDER-enabled droplet-based microfluidic high-throughput screening method for obtaining high-yield industrial strains. Our method provides a foundation for using enzymes as untapped blueprint resources for biosensor design, creation, and application.

Reducing transportation-related carbon dioxide (CO2) emissions in China poses significant challenges due to the sector’s growth potential and variations among provinces and transportation modes. This study utilizes the bottom-up approach and the Logarithmic Mean Divisia Index (LMDI) decomposition method to calculate transportation CO2 emissions and explores the temporal-spatial differences across Chinese provinces. The results reveal that national transportation CO2 emissions increased by 50.14% from 2010 to 2019, and emissions from private cars present the fastest growth among all transportation modes by 254% over the decade. Spatially, higher emissions are found in eastern provinces, and neighboring provinces notably distinguish from each other in terms of the emission proportion of different modes and the factor analysis from LMDI. Regarding the heterogeneity of the spatial emission characteristics, a cluster-based evaluation method is proposed for the 31 provinces according to the emission structure and the LMDI decomposition. Four clusters are derived, each featuring varied emission distribution and driving factors. Correspondingly, policy recommendations are proposed to address the characteristics of each cluster, such as controlling car ownership, promoting integrated transport modes, improving fuel economy, and electrifying urban transportation services. The cluster-based analysis method can provide more specific suggestions to province targeting its emission characteristics rather than its location, which is one of the major contributions of this study.

Rationale and objectives: Fuzi, the dried root of Aconitum carmichaelii Debx, is one of the widely used traditional Chinese medicines. Fuzi polysaccharides are considered the most bioactive compounds with immunomodulatory functions, however, the mechanisms have not been evaluated. This study aims to systematically investigate the effects of Fuzi polysaccharides on the gut microbiota and immune function using a mouse model immunosuppressed with cyclophosphamide. Methods: The short-chain fatty acid levels in cecal contents were measured by gas chromatography-mass spectrometry. The gut microbiota 16S rRNA gene were sequenced by next generation sequencing. The mRNA expression levels of NF-κB, IL-6, TNF-α, iNOS and COX-2 were measured using quantitative real-time polymerase chain reaction. The protein expression of occludin and zonula occludens-1 were analyzed by Western blot. The white blood cells were counted using automated hematology analyzer, and CD4+FOXP3+/CD4+ ratio was measured by flow cytometry. Results and Conclusions: Fuzi polysaccharides had the function of elevating the concentration of acetic acid, propionic acid, isobutyric acid, and n-butyric acid in the cecum. Meanwhile, Fuzi polysaccharides could decrease the relative abundance of Helicobacter, Anaerotruncus, Faecalibacterium, Lachnospira, Erysipelotrichaceae_UCG-003, Mucispirillum, and Mycoplasma, and increase the relative abundance of Rhodospirillales, Ruminococcaceae_UCG-013, Mollicutes_RF39, Ruminococcus_1, Christensenellaceae_R-7_group, and Muribaculaceae in the gut. Furthermore, Fuzi polysaccharides exhibited the function of increasing spleen and thymus indices and number of white blood cells and lymphocytes. Fuzi polysaccharides could reverse the decreased mRNA expression of NF-кB, IL-6, and iNOS, differentiation of CD4+FOXP3+ regulatory T cells as well as protein expression of occludin and zonula occludens-1 induced by cyclophosphamide. In addition, the mRNA and protein expression of cytokines were significantly correlated with the abundance of gut microbiota under Fuzi polysaccharides treatment. Collectively, the above results demonstrated that Fuzi polysaccharides could regulate inflammatory cytokines and gut microbiota composition of immunosuppressive mice to improve immunity, thereby shedding light on revealing the molecular mechanism of polysaccharides of traditional Chinese medicines in the future.

A passenger-centered Heating, Ventilation, and Air Conditioning (HVAC) system is an urgent need with the innovative development of intelligent vehicles. A prerequisite for such a system is precise real-time estimation of human thermal comfort. This paper introduces a new method based on deep learning to predict the personal thermal comfort in the vehicle via facial thermal image. Specifically, a deep learning-based ResNet34 coupled with a spatial attention mechanism (SAM-ResNet34) is designed for feature extraction from the facial thermal image. Unlike the existing methods, this method extracts the gray features from the different areas of facial thermal images instead of measuring the facial skin temperature to predict the thermal comfort states. The thermal comfort data were collected from the experiment with 22 subjects. It has highlighted that the model trained with the thermal image dataset can achieve an accuracy as high as 93.75% in the test set. The result suggests that the non-invasive method proposed in this study could accurately predict personal thermal comfort in the vehicular environment and holds great potential to be applied to the HVAC control system of a vehicle in the future.

Bacillus subtilis is one of the commonly used industrial strains for riboflavin production. High-throughput screening is useful in biotechnology, but there are still an insufficient number of articles focusing on improving the riboflavin production of B. subtilis by this powerful tool. With droplet-based microfluidics technology, single cells can be encapsulated in droplets. The screening can be carried out by detecting the fluorescence intensity of secreted riboflavin. Thus, an efficient and high-throughput screening method suitable for riboflavin production strain improvement could be established. In this study, droplet-based microfluidics screening was applied, and a more competitive riboflavin producer U3 was selected from the random mutation library of strain S1. The riboflavin production and biomass of U3 were higher than that of S1 in flask fermentation. In addition, the results of fed-batch fermentation showed that the riboflavin production of U3 was 24.3 g/L, an 18% increase compared with the parent strain S1 (20.6 g/L), and the yield (g riboflavin/100 g glucose) increased by 19%, from 7.3 (S1) to 8.7 (U3). Two mutations of U3 (sinRG89R and icdD28E) were identified through whole genome sequencing and comparison. Then they were introduced into BS168DR (parent of S1) for further analysis, which also caused riboflavin production to increase. This paper provides protocols for screening riboflavin-producing B. subtilis with droplet-based microfluidics technology and reveals mutations in riboflavin overproduction strains.

Streptomyces are an important filamentous bacterium genus in industry, but most of the high-throughput techniques so far can only separate spores or protoplasts. Tu et al. develop an encapsulating method that allows screening of Streptomyces in the filamentous, stationary phase.

Erythromycin is a clinically important drug produced by the rare actinomycete Saccharopolyspora erythraea. In the wide-type erythromycin producer S. erythraea NRRL 23338, there is a lack of systematical method for promoter engineering as well as a well-characterized promoter panel for comprehensive metabolic engineering. Here we demonstrated a systematical promoter acquiring process including promoter characterization, engineering and high-throughput screening by the droplet-microfluidic based platform in S. erythraea NRRL 23338, and rapidly obtained a panel of promoters with 21.5-fold strength variation for expression fine-tuning in the native host. By comparative qRT-PCR of S. erythraea NRRL 23338 and a high-producing strain S0, potential limiting enzymes were identified and overexpressed individually using two screened synthetic promoters. As a result, erythromycin production in the native host was improved by as high as 137.24 folds by combinational gene overexpression. This work enriches the accessible regulatory elements in the important erythromycin-producing strain S. erythraea NRRL 23338, and also provides a rapid and systematic research paradigm of promoter engineering and expression fine-tuning in the similar filamentous actinomycete hosts.

The widespread use of renewable energy resources requires more immediate and effective fire alarms as a preventive measure. The fire is usually weak in the initial stages, which is not conducive to detection and identification. This paper validates a solution to resolve that problem by a flame detection algorithm that is more sensitive to small flames. Based on Yolov3, the parallel convolution structure of Inception is used to obtain multi-size image information. In addition, the receptive field of the convolution kernel is increased with the dilated convolution so that each convolution output contains a range of information to avoid information omission of tiny flames. The model accuracy has improved by introducing a Feature Pyramid Network in the feature extraction stage that has enhanced the feature fusion capability of the model. At the same time, a flame detection database for early fire has been established, which contains more than 30 fire scenarios and is suitable for flame detection under various challenging scenes. Experiments validate the proposed method not only improves the performance of the original algorithm but are also advantageous in comparison with other state-of-the-art object detection networks, and its false positives rate reaches 1.2% in the test set.

The driving ranges of electric vehicles (EVs) will decrease greatly with increased use of the vehicle heating system in a cold climate. Air conditioning heat pump (ACHP) systems, which convert energy stored in the ambient environment into heat, represent a promising approach for increasing the EV driving range. In this work, the performance of an ACHP system in an EV under extremely cold conditions is investigated experimentally. The requirements of an ACHP system for EVs at various ambient temperatures are determined using our capacity matching strategy. A prototype system designed based on these requirements is evaluated. Data collected from experiments performed at a full-scale facility under extreme temperature conditions are analyzed. The results show that the ACHP system proposed for EV applications can satisfy both the cooling and heating requirements for the passenger compartment. The system increased the driving range by 23% when compared with that of an EV using a positive-temperature-coefficient (PTC) heater at −10 °C.

Studying the heat transfer characteristics of alternating current (AC) arc-fault to electrodes is a key issue in electrical fires. In this paper, an instantaneous heat transfer numerical model of AC arc-fault is developed based on the magneto-hydrodynamic principle. The temperature distribution of the AC arc at the microseconds level and the influence of heat transfer on electrodes at the seconds level when the arc heats are studied. The numerical simulation of the axial temperature of the electrodes is verified by experiments, and the temperature variation in the electrodes at different currents and times is discussed. The results show that the arc temperature varies periodically similar to the current at the microseconds level but it does not go out when the current passes zero. The high-temperature region of electrodes diffuses with the increase in current or time. However, the axial temperature gradient of the electrode decreases with time and increases with current. Furthermore, the range of temperature increase in the electrode position decreases with the increase in current and time, but the electrode position near the arc has a higher initial temperature increase.

TDLAS (tunable diode laser absorption spectroscopy) is an important gas analysis method that can be employed to obtain characteristic parameters non-invasively by the infrared absorption spectra of tracer molecules such as CH4, H2O and O2. In this study, a portable H2O-based TDLAS system with a dual optical path was developed with the aim of assessing the combustion characteristics of flammable gases. Firstly, a calculation method of gas characteristics including temperature and velocity combining absorption spectra and a HITRAN database was provided. Secondly, to calibrate and validate this TDLAS system precisely, a pressure vessel and a shock tube were introduced innovatively to generate static or steady flow fields with preset constant temperatures, pressures, or velocities. Static tests within environment pressures up to 2 MPa and steady flow field tests with temperatures up to 1600 K and flow velocities up to 950 m/s were performed for verification. It was proved that this system can provide an accurate values for high temperature and velocity gas flows. Finally, an experimental investigation of CH4/air flames was conducted to test the effectiveness of the system when applied to small diffusion flames. This TDLAS system gave satisfactory flame temperature and velocity data owing to the dual optical path design and high frequency scanning, which compensated for scale effects and pulsation of the flame. This work demonstrates a valuable new approach to thermal hazard analysis in specific environments.

Abstract Background Recombinant human Fibroblast growth factor 21 (rhFGF21) is an endocrine hormone that has profound effects on treatment of metabolic diseases. However, rhFGF21 is prone to form inclusion body when expressed in bacteria, which results in, the downstream process of purification of bioactive rhFGF21 is time-consuming and labor intensive. The aim of this work is to explore a new method for improving the soluble expression and secretion level of rhFGF21 in B. subtilis. Results A codon optimized rhFGF21 gene was expressed under the control of a strong inducible promoter P malA in B. subtilis. A mini-cistron cassette (from gsiB) was located upstream of rhFGF21 in expression vector (pMATEFc5), which could reduce the locally stabilized mRNA secondary structure of transcripts and enhance the efficiency of translation initiation. Then various chaperones were further overexpressed to improve the expression efficiency of rhFGF21. Results showed that overexpression of the chaperone DnaK contributed to the increase of solubility of rhFGF21. Moreover, an extracellular proteases deficient strain B. subtilis Kno6cf was used to accumulate the secreted rhFGF21 solidly. In addition, eleven signal peptides from B. subtilis were evaluated and the SP dacB appeared the highest secretion yield of rhFGF21 in B. subtilis. Finally, the combinatorial optimized strain achieved an about ninefold increase of the soluble rhFGF21 production after 24 h of flask fermentation in comparison with the initial production strain. Conclusion This work provided a comprehensive strategy for secretory expressing the heterologous protein rhFGF21 in B. subtilis. To our knowledge, this is the first report of the highly efficient production of rhFGF21 in B. subtilis and this approach may provide some suggestions for heterologous proteins production in B. subtilis.

Concerning the issues regarding driving mileage reduction for electric vehicles (EVs) in cold climates, a heat pump system with low global warming potential refrigerant R290/R1234yf is employed as one of the promising solutions. Different from the widely used mobile refrigerant R134a, R290 and R1234yf are both flammable or explosive. The application of R290/R1234yf in the mobile heat pump system is hindered by unexpected refrigerant leakage with the existence of fire and explosion risk. In this study, the combustion characteristics of R290/R1234yf in a potential leakage process from an air-conditioning heat pump system for EVs were investigated. Firstly, thermodynamic behaviours of R290/R1234yf used in a typical heat pump system were analysed based on a special experimental facility designed for EVs. Then the leakage and combustion characteristics of R290/R1234yf including flame shape, temperature, radiation etc. were obtained by the experimental method under different initial temperature and mass flow rate conditions. It was found that R290/R1234yf leaked is difficult to ignite at low temperatures, while the blow-off phenomenon of the jet flame would occur at high temperature with high leakage mass flow rate. In addition, the results showed that combustion intensity would be enhanced by the leakage mass flow rate between 30 and 60°C. These results could provide guidance for fire detection and rescue system design for new energy vehicles.

Fire propagation and burning characteristics of upward flame spread over flexible polyurethane (FPU) foam board were investigated under coupling effects of pressure and orientation. As a further comparative research of our previous work, three pressures (70, 85 and 100 kPa) and four fuel surface inclination angles (0°, 30°, 60°, 90°) were applied, respectively, as before, to study the variation of typical parameters including flame spread rate (FSR), burning rate, heat transfer components, flame length, etc. First, a phenomenological interpretation was taken to show the special spreading process with melting flow combustion and flash burning observed. Second, an overall theoretical analysis was proposed to reveal the individual or coupling effects of pressure and inclined burning surface on spreading behavior. A semi-quantitative correlation was developed and formulated to show the tendency of FSR as a function of pressure, inclination and other burning parameters, which was validated by data in paper. Meanwhile, comparison of detailed differences between upward and downward spread was conducted to give a full insight on FPU fire development. At last, comprehensive discussions of coupling effects on variation of spreading characteristics and heat transfer mechanisms were performed based on fire dynamics.

Emission models are important tools for traffic emission and air quality estimates. Existing instantaneous emission models employ the steady-state “engine emissions map” to estimate emissions for individual vehicles. However, vehicle emissions vary significantly, even under the same driving conditions. Variability in the emissions at a specific driving condition depends on various influencing factors. It is important to gain insight into the effects of these factors, to enable detailed modeling of individual vehicle emissions. This study employs a portable emissions measurement system (PEMS), to collect vehicle emissions including the corresponding parameters of engine condition, vehicle activity, catalyst temperature, geography, and meteorology, to analyze the variability in emission rates as a function of those factors, across different vehicle specific power (VSP) categories. We observe that carbon dioxide, carbon monoxide, nitrogen oxides, and particle number emissions are strongly correlated with engine parameters (engine speed, torque, load, and air-fuel ratio) and vehicle activity parameters (vehicle speed and acceleration). In the same VSP bin, emissions per second on highways and ramps are higher than those on arterial roads, and the emissions when the vehicle is traveling downhill tend to be higher than the emissions during uphill traveling, because of higher observed speeds and accelerations. Morning emissions are higher than afternoon emissions, due to lower temperatures.

AC arc faults are one of the most important causes of residential electrical wiring fires, which may produce extremely high temperatures and easily ignite surrounding combustible materials. The global interest in machine learning-based methods for arc fault diagnosis applications is increasing due to continuous challenges in efficiency and accuracy. In this paper, a temporal domain visualization convolutional neural network (TDV-CNN) methodology is proposed. The current transformer and high-speed data acquisition system are used to collect the current of a series of arc faults, then the signal is filtered by a digital filter and converted into a gray image in time sequence before being fed into TDV-CNN. Five different electric loads were selected for experimental validation with various signal characteristics, including vacuum cleaner, fluorescent lamp, dimmer, heater, and desktop computer. The experimental results confirm that the classification accuracy of the five loads’ work states in the ten categories could reach 98.7% or even higher by adjusting parameters perfectly. The methodology is believed to be reliable for series arc detection with relatively high accuracy and also has important potential applications in other fault diagnosis fields.

The effect of altitude on typical combustible burning and related smoke detector response signals was investigated by comparison experiments at altitudes of 40 m and 3650 m based on EN54 standard tests. Point-type light scattering photoelectric smoke detectors and ionization smoke detectors were used for four kinds of EN54 fire tests, including two kinds of smouldering fires with wood (test fire no. 2 in EN54 standard or TF2) and cotton (TF3), and two kinds of flaming fires with polyurethane (TF4) and n-heptane (TF5). First, the influence of altitude or ambient pressure on mass loss for smouldering combustion (TF2 or TF3) was insignificant, while a significant decrease in the mass burning rate was found for flaming tests (TF4 and TF5) as reported in our previous studies. Second, for photoelectric smoke detectors in flaming fire tests, the effect of altitude was similar to that of the burning rate, whereas for the ionization smoke detectors, the response signal at high altitudes was shown to be ‘enhanced’ by the detection principle of the ionization chamber, leading to an even larger value than at normal altitude for smouldering conditions. Third, to provide a reference for smoke detector design in high-altitude areas, the differences between signal speed in rising and peak values at two locations are discussed. Also, relationship between ion chamber signals and smoke optical densities are presented by utilization of an ionization smoke detector and smoke concentration meter. Moreover, a hierarchical diagram is illustrated to provide a better understanding of the effects of altitude on combustible burning behaviour and the mechanisms of detector response.

The characteristics of a series direct current (DC) arc-fault including both electrical and thermal parameters were investigated based on an arc-fault simulator to provide references for multi-parameter electrical fire detection method. Tests on arc fault behavior with three different initial circuit voltages, resistances and arc gaps were conducted, respectively. The influences of circuit conditions on arc dynamic image, voltage, current or power were interpreted. Also, the temperature rises of electrode surface and ambient air were studied. The results showed that, first, significant variations of arc structure and light emitting were observed under different conditions. A thin outer burning layer of vapor generated from electrodes with orange light was found due to the extremely high arc temperature. Second, with the increasing electrode gap in discharging, the arc power was shown to have a non monotonic relationship with arc length for constant initial circuit voltage and resistance. Finally, the temperature rises of electrode surface caused by heat transfer from arc were found to be not sensitive with increasing arc length due to special heat transfer mechanism. In addition, temperature of ambient air showed a large gradient in radial direction of arc.

Both experimental and theoretical methods were proposed to assess the effects of adjacent, parallel, and symmetric exterior wall structures on the combustion and flame spreading characteristics of rigid polyurethane (PUR) foam insulation. During the combustion of PUR specimens, the flame leading edge was found to transfer from a unique inverted ‘W’ shape to an inverted ‘V’ during flame propagation. This phenomenon is attributed to edge effects related to boundary layer theory. The effects of the adjacent façade angle on flame spreading rate and flame height were shown to be nonlinear, as a result of the combined influences of heat transfer, radiation angle, and the chimney restriction effects. A critical angle around 90 degree with maximum thermal hazards outwards by parallel fire was observed and consistent with the mass loss rate and flame height tendencies. For narrow spacing configurations or angles (e.g., 60 and 90 degrees), phenomenological two-pass processing in conjunction showed that increased preheating lengths were associated with enhanced heat transfer. The results of this study have implications concerning the design of safe façade structures for high-rise buildings, and provide a better understanding of downward flame spreading over PUR.

Introduction: Hypertriglyceridemia is the most prevalent dyslipidemia in patients with chronic kidney disease (CKD). However, research about fibrate treatment in CKD patients is limited, and assessing its benefits becomes challenging due to the frequent concurrent use of statins. Thus, this study is aimed to investigate the role of fibrate in CKD stage 3 patients with hypertriglyceridemia who did not receive other lipid-lowering agents. Methods: This study enrolled patients newly diagnosed CKD3 with LDLC< 100mg/dL and had never received statin or other lipid-lowering agents from Chang Gung Research Database. The participants were categorized into 2 groups based on the use of fibrate: fibrate group and non-fibrate group (triglyceride >200mg/dL but not receiving fibrate treatment). The inverse probability of treatment weighting was performed to balance baseline characteristics. Results: Compared with the non-fibrate group (n=2020), the fibrate group (n=705) exhibited significantly lower risks of major adverse cardiac and cerebrovascular events (MACCEs) (10.4% vs. 12.8%, hazard ratios [HRs]: 0.69, 95% confidence interval [CI]: 0.50 to 0.95), AMI (2.3% vs. 3.9%, HR: 0.52, 95% CI: 0.37 to 0.73), and ischemic stroke (6.3% vs. 8.0%, HR: 0.67, 95% CI: 0.52 to 0.85). The risk of all-cause mortality (5.1% vs. 4.5%, HR: 1.09, 95% CI: 0.67 to 1.79) and death from CV (2.8% vs. 2.3%, HR: 1.07, 95% CI: 0.29 to 2.33) did not significantly differ between the 2 groups. Conclusion: This study suggests that, in moderate CKD patients with hypertriglyceridemia but LDL-C < 100mg/dL who did not take other lipidlowering agents, fibrates may be beneficial in reducing cardiovascular events. [ABSTRACT FROM AUTHOR]