Oxygen-Bridged Cu Binuclear Sites for Efficient Electrocatalytic CO2 Reduction to Ethanol at Ultralow Overpotential.

Electrocatalytic CO2 reduction (CO2RR) to alcohols offers a promising strategy for converting waste CO2 into valuable fuels/chemicals but usually requires large overpotentials. Herein, we report a catalyst comprising unique oxygen-bridged Cu binuclear sites (CuOCu-N4) with a Cu···Cu distance of 3.0-3.1 Å and concomitant conventional Cu-N4 mononuclear sites on hierarchical nitrogen-doped carbon nanocages (hNCNCs). The catalyst exhibits a state-of-the-art low overpotential of 0.19 V (versus reversible hydrogen electrode) for ethanol and an outstanding ethanol Faradaic efficiency of 56.3% at an ultralow potential of -0.30 V, with high-stable Cu active-site structures during the CO2RR as confirmed by operando X-ray adsorption fine structure characterization. Theoretical simulations reveal that CuOCu-N4 binuclear sites greatly enhance the C-C coupling at low potentials, while Cu-N4 mononuclear sites and the hNCNC support increase the local CO concentration and ethanol production on CuOCu-N4. This study provides a convenient approach to advanced Cu binuclear site catalysts for CO2RR to ethanol with a deep understanding of the mechanism.

Quantifying uncertainty in spikes estimated from calcium imaging data.

In recent years, a number of methods have been proposed to estimate the times at which a neuron spikes on the basis of calcium imaging data. However, quantifying the uncertainty associated with these estimated spikes remains an open problem. We consider a simple and well-studied model for calcium imaging data, which states that calcium decays exponentially in the absence of a spike, and instantaneously increases when a spike occurs. We wish to test the null hypothesis that the neuron did not spike-i.e., that there was no increase in calcium-at a particular timepoint at which a spike was estimated. In this setting, classical hypothesis tests lead to inflated Type I error, because the spike was estimated on the same data used for testing. To overcome this problem, we propose a selective inference approach. We describe an efficient algorithm to compute finite-sample $p$-values that control selective Type I error, and confidence intervals with correct selective coverage, for spikes estimated using a recent proposal from the literature. We apply our proposal in simulation and on calcium imaging data from the $\texttt{spikefinder}$ challenge.

Artificial intelligence-assisted system for the assessment of Forrest classification of peptic ulcer bleeding: a multicenter diagnostic study.

BACKGROUND: Inaccurate Forrest classification may significantly affect clinical outcomes, especially in high risk patients. Therefore, this study aimed to develop a real-time deep convolutional neural network (DCNN) system to assess the Forrest classification of peptic ulcer bleeding (PUB). METHODS: A training dataset (3868 endoscopic images) and an internal validation dataset (834 images) were retrospectively collected from the 900th Hospital, Fuzhou, China. In addition, 521 images collected from four other hospitals were used for external validation. Finally, 46 endoscopic videos were prospectively collected to assess the real-time diagnostic performance of the DCNN system, whose diagnostic performance was also prospectively compared with that of three senior and three junior endoscopists. RESULTS: The DCNN system had a satisfactory diagnostic performance in the assessment of Forrest classification, with an accuracy of 91.2% (95%CI 89.5%-92.6%) and a macro-average area under the receiver operating characteristic curve of 0.80 in the validation dataset. Moreover, the DCNN system could judge suspicious regions automatically using Forrest classification in real-time videos, with an accuracy of 92.0% (95%CI 80.8%-97.8%). The DCNN system showed more accurate and stable diagnostic performance than endoscopists in the prospective clinical comparison test. This system helped to slightly improve the diagnostic performance of senior endoscopists and considerably enhance that of junior endoscopists. CONCLUSION: The DCNN system for the assessment of the Forrest classification of PUB showed satisfactory diagnostic performance, which was slightly superior to that of senior endoscopists. It could therefore effectively assist junior endoscopists in making such diagnoses during gastroscopy.

Risk factors for SARS-CoV-2 infection at a UK electricity-generating company: a test-negative design case-control study.

OBJECTIVES: Identify workplace risk factors for SARS-CoV-2 infection, using data collected by a UK electricity-generating company. METHODS: Using a test-negative design case-control study, we estimated the OR of infection by job category, site, test reason, sex, vaccination status, vulnerability, site outage and site COVID-19 weekly risk rating, adjusting for age, test date and test type. RESULTS: From an original 80 077 COVID-19 tests, there were 70 646 included in the final analysis. Most exclusions were due to being visitor tests (5030) or tests after an individual first tested positive (2968).Women were less likely to test positive than men (OR=0.71; 95% CI 0.58 to 0.86). Test reason was strongly associated with positivity and although not a cause of infection itself, due to differing test regimes by area, it was a strong confounder for other variables. Compared with routine tests, tests due to symptoms were highest risk (94.99; 78.29 to 115.24), followed by close contact (16.73; 13.80 to 20.29) and broader-defined work contact 2.66 (1.99 to 3.56). After adjustment, we found little difference in risk by job category, but some differences by site with three sites showing substantially lower risks, and one site showing higher risks in the final model. CONCLUSIONS: In general, infection risk was not associated with job category. Vulnerable individuals were at slightly lower risk, tests during outages were higher risk, vaccination showed no evidence of an effect on testing positive, and site COVID-19 risk rating did not show an ordered trend in positivity rates.

Identifying employee, workplace and population characteristics associated with COVID-19 outbreaks in the workplace: a population-based study.

OBJECTIVES: To identify risk factors that contribute to outbreaks of COVID-19 in the workplace and quantify their effect on outbreak risk. METHODS: We identified outbreaks of COVID-19 cases in the workplace and investigated the characteristics of the individuals, the workplaces, the areas they work and the mode of commute to work, through data linkages based on Middle Layer Super Output Areas in England between 20 June 2021 and 20 February 2022. We estimated population-level associations between potential risk factors and workplace outbreaks, adjusting for plausible confounders identified using a directed acyclic graph. RESULTS: For most industries, increased physical proximity in the workplace was associated with increased risk of COVID-19 outbreaks, while increased vaccination was associated with reduced risk. Employee demographic risk factors varied across industry, but for the majority of industries, a higher proportion of black/African/Caribbean ethnicities and living in deprived areas, was associated with increased outbreak risk. A higher proportion of employees in the 60-64 age group was associated with reduced outbreak risk. There were significant associations between gender, work commute modes and staff contract type with outbreak risk, but these were highly variable across industries. CONCLUSIONS: This study has used novel national data linkages to identify potential risk factors of workplace COVID-19 outbreaks, including possible protective effects of vaccination and increased physical distance at work. The same methodological approach can be applied to wider occupational and environmental health research.

Degradation of ß-lactam antibiotics by Fe(III)/HSO3- system and their quantitative structure-activity relationship.

ß-lactam antibiotics, extensively used worldwide, pose significant risks to human health and ecological safety due to their accumulation in the environment. Recent studies have demonstrated the efficacy of transition metal-activated sulfite systems, like Fe(Ⅲ)/HSO3-, in removing PPCPs from water. However, research on their capability to degrade ß-lactam antibiotics remains sparse. This paper evaluates the degradation of 14 types of ß-lactam antibiotics in Fe(Ⅲ)/HSO3- system and establishes a QSAR model correlating molecular descriptors with degradation rates using the MLR method. Using cefazolin as a case study, this research predicts degradation pathways through NPA charge and Fukui function analysis, corroborated by UPLC-MS product analysis. The investigation further explores the influence of variables such as HSO3- dosage, substrate concentration, Fe(Ⅲ) dosage, initial pH and the presence of common seen water matrices including humic acid and bicarbonate on the degradation efficiency. Optimal conditions for cefazolin degradation in Fe(Ⅲ)/HSO3- system were determined to be 93.3 µM HSO3-, 8.12 µM Fe(Ⅲ) and an initial pH of 3.61, under which the interaction of Fe(Ⅲ) dosage with initial pH was found to significantly affect the degradation efficiency. This study not only provides a novel degradation approach for ß-lactam antibiotics but also expands the theoretical application horizon of the Fe(Ⅲ)/HSO3- system.

A tempo-spatial controllable microfluidic shear-stress generator for in-vitro mimicking of the thrombus.

Pathological conditions linked to shear stress have been identified in hematological diseases, cardiovascular diseases, and cancer. These conditions often exhibit significantly elevated shear stress levels, surpassing 1000 dyn/cm2 in severely stenotic arteries. Heightened shear stress can induce mechanical harm to endothelial cells, potentially leading to bleeding and fatal consequences. However, current technology still grapples with limitations, including inadequate flexibility in simulating bodily shear stress environments, limited range of shear stress generation, and spatial and temporal adaptability. Consequently, a comprehensive understanding of the mechanisms underlying the impact of shear stress on physiological and pathological conditions, like thrombosis, remains inadequate. To address these limitations, this study presents a microfluidic-based shear stress generation chip as a proposed solution. The chip achieves a substantial 929-fold variation in shear stress solely by adjusting the degree of constriction in branch channels after PDMS fabrication. Experiments demonstrated that a rapid increase in shear stress up to 1000 dyn/cm2 significantly detached 88.2% cells from the substrate. Long-term exposure (24 h) to shear stress levels below 8.3 dyn/cm2 did not significantly impact cell growth. Furthermore, cells exposed to shear stress levels equal to or greater than 8.3 dyn/cm2 exhibited significant alterations in aspect ratio and orientation, following a normal distribution. This microfluidic chip provides a reliable tool for investigating cellular responses to the wide-ranging shear stress existing in both physiological and pathological flow conditions.

Predicting Bloodstream Infection in High-risk Groups of Liver Failure Patients with Artificial Liver Support System.

Background: Liver failure is a rare, life-threatening disease that has a high mortality rate and affects many organ systems. Bloodstream bacterial infection has played a key role in liver failure patients with plasma exchange-centered artificial liver support systems, but the predicted risk factors of infection have not been fully understood. Objective: We aimed to predict bloodstream bacterial infection in high-risk groups of liver failure patients during a plasma exchange-centered artificial liver support system. Design: This was a prospective cohort study. Setting: This study was performed in Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School. Participants: 118 liver failure patients with plasma exchange-centered artificial liver support system therapy from Nanjing Drum Tower Hospital from November 2019 to November 2020 were selected. Interventions: We used a stepwise binary logistic regression model to select the optimal risk factors of infection with minimum Akaike information criterion, and the Nomogram prognostic model for bloodstream infection was constructed for visualization. Primary Outcome Measures: Risk factors of bloodstream infection (2) predictive accuracy of the constructed nomogram model. Results: Among the 118 liver failure patients, 22 (18.64%) were diagnosed with bloodstream bacterial infection. The univariable and multivariate logistic regression analyses suggested that culture level, glucocorticoids use, number of punctures, blood platelet counts, white blood cell counts, and indwelling catheter time were the sex predictors of bloodstream infection for liver failure patients during plasma exchange-centered artificial liver support system (P = .042, P = .013, P = .025, P = .003, P = .024 and P = .026). The nomogram predictive model was established with high prediction accuracy, of which the area under the curve was 0.935 (95% confidence interval: 0.884-0.986), the sensitivity was 0.955, and the specificity was 0.854. Conclusion: The constructed nomogram prognostic model can recognize the risk factors and accurately predict bloodstream infection for liver failure patients during plasma exchange-centered artificial liver support system.

The Association Between Social Network Characteristics and Tuberculosis Infection Among Adults in 9 Rural Ugandan Communities.

BACKGROUND: Social network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies. METHODS: We assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social network structure and characteristics of first-degree contacts (sex, human immunodeficiency virus [HIV] status, tuberculosis infection) were associated with revalent tuberculosis infection (positive tuberculin skin test [TST] result) after adjusting for individual-level risk factors (age, sex, HIV status, tuberculosis contact, wealth, occupation, and Bacillus Calmette-Guérin [BCG] vaccination) with targeted maximum likelihood estimation. RESULTS: Among 3 335 residents sampled for TST, 32% had a positive TST results and 4% reported a tuberculosis contact. The social network contained 15 328 first-degree contacts. Persons with the most network centrality (top 10%) (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.1]) and the most (top 10%) male contacts (1.5 [1.3-1.9]) had a higher risk of prevalent tuberculosis, than those in the remaining 90%. People with ≥1 contact with HIV (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.6]) and ≥2 contacts with tuberculosis infection were more likely to have tuberculosis themselves (2.6 [ 95% confidence interval: 2.2-2.9]). CONCLUSIONS: Social networks with higher centrality, more men, contacts with HIV, and tuberculosis infection were positively associated with tuberculosis infection. Tuberculosis transmission within measurable social networks may explain prevalent tuberculosis not associated with a household contact. Further study on network-informed tuberculosis case finding interventions is warranted.

High-Dispersive Pd Nanoparticles on Hierarchical N-Doped Carbon Nanocages to Boost Electrochemical CO2 Reduction to Formate at Low Potential.

Electrochemical CO2 reduction reaction (CO2 RR) to value-added chemicals/fuels is an effective strategy to achieve the carbon neutral. Palladium is the only metal to selectively produce formate via CO2 RR at near-zero potentials. To reduce cost and improve activity, the high-dispersive Pd nanoparticles on hierarchical N-doped carbon nanocages (Pd/hNCNCs) are constructed by regulating pH in microwave-assisted ethylene glycol reduction. The optimal catalyst exhibits high formate Faradaic efficiency of >95% within -0.05-0.30 V and delivers an ultrahigh formate partial current density of 10.3 mA cm-2 at the low potential of -0.25 V. The high performance of Pd/hNCNCs is attributed to the small size of uniform Pd nanoparticles, the optimized intermediates adsorption/desorption on modified Pd by N-doped support, and the promoted mass/charge transfer kinetics arising from the hierarchical structure of hNCNCs. This study sheds light on the rational design of high-efficient electrocatalysts for advanced energy conversion.

Reconstruction of reverse transsulfuration pathway enables cysteine biosynthesis and enhances resilience to oxidative stress in Chinese Hamster Ovary cells.

Cysteine is a critically important amino acid necessary for mammalian cell culture, playing key roles in nutrient supply, disulfide bond formation, and as a precursor to antioxidant molecules controlling cellular redox. Unfortunately, its low stability and solubility in solution make it especially problematic as an essential medium component that must be added to Chinese hamster ovary and other mammalian cell cultures. Therefore, CHO cells have been engineered to include the capacity of endogenously synthesizing cysteine by overexpressing multiple enzymes, including cystathionine beta-synthase (CBS), cystathionine gamma-lyase (CTH) and glycine N-methyltransferase (GNMT) to reconstruct the reverse transsulfuration pathway and overcome a key metabolic bottleneck. Some limited cysteine biosynthesis was obtained by overexpressing CBS and CTH for converting homocysteine to cysteine but robust metabolic synthesis from methionine was only possibly after incorporating GNMT which likely represents a key bottleneck step in the cysteine biosynthesis pathway. CHO cells with the reconstructed pathway exhibit the strong capability to proliferate in cysteine-limited and cysteine-free batch and fed-batch cultures at levels comparable to wildtype cells with ample cysteine supplementation, providing a selectable marker for CHO cell engineering. GNMT overexpression led to the accumulation of sarcosine byproduct, but its accumulation did not affect cell growth. Furthermore, pathway reconstruction enhanced CHO cells' reduced and glutathione levels in cysteine-limited conditions compared to unmodified cells, and greatly enhanced survivability and maintenance of redox homeostasis under oxidative stress induced by addition of menadione in cysteine-deficient conditions. Such engineered CHO cell lines can potentially reduce or even eliminate the need to include cysteine in culture medium, which not only reduces the cost of mammalian media but also promises to transform media design by solving the challenges posed by low stability and solubility of cysteine and cystine in future mammalian biomanufacturing processes.

Pan-immune-inflammation and its dynamics: predictors of survival and immune-related adverse events in patients with advanced NSCLC receiving immunotherapy.

OBJECTIVES: Pan-immune-inflammation value (PIV) is defined by the neutrophil, platelet, monocyte, and lymphocyte counts and is associated with immune-checkpoint inhibitor (ICI) therapy outcomes in advanced non-small cell lung cancer (aNSCLC). However, PIV is dynamic under therapy and its longitudinal assessment may help predict efficacy. This study investigated the impact of baseline PIV and its dynamics on ICI efficacy and its immune-related adverse events (irAEs). The study additionally attempted to understand the biological significance of PIV. PATIENTS AND METHODS: This retrospective study analyzed the clinical data of 269 consecutive patients with aNSCLC. PIV was calculated at baseline and at weeks 3-4 to determine its association with overall survival (OS), progression-free survival (PFS), and irAEs. RESULTS: Results revealed that low baseline PIV was positively correlated with the incidence of irAEs. Moreover, a low PIV at baseline was significantly associated with a prolonged PFS (median PFS: 10 vs. 7 months, p = 0.0005) and OS (median OS: 29 vs. 21 months, p < 0.0001). When the PIV at baseline and weeks 3-4 was considered together, its low dynamics correlated with a higher incidence of irAEs (p = 0.001), a longer PFS (median PFS, 9 vs. 6 months, p = 0.012), and a longer OS (median OS; 28 vs. 21 months, p = 0.002). CONCLUSION: Thus, PIV at baseline and its dynamics are novel and potent predictors of irAEs, PFS, and OS in patients with aNSCLC receiving immunotherapy. Moreover, the PIV dynamics may be an effective, novel surrogate marker to dynamically observe the efficacy of immunotherapy.

Bayesian phylodynamic analysis reveals the evolutionary history and the dispersal patterns of citrus tristeza virus in China based on the p25 gene.

BACKGROUND: Citrus tristeza virus (CTV) is one of the most serious threats to the citrus industry, and is present in both wild and cultivated citrus. The origin and dispersal patterns of CTV is still poorly understood in China. METHODS: In this study, 524 CTV suspected citrus samples from China were collected, including 354 cultivated citrus samples and 174 wild citrus samples. Finally, 126 CTV coat protein sequences were obtained with time-stamped from 10 citrus origins in China. Bayesian phylodynamic inference were performed for CTV origin and dispersal patterns study in China. RESULT: We found that CTV was mainly distributed in southern and coastal areas of China. The substitution rate of CTV was 4.70 × 10- 4 subs/site/year (95% credibility interval: 1.10 × 10- 4 subs/site/year ~ 9.10 × 10- 4 subs/site/year), with a slight increasing trend in CTV populations between 1990 and 2006. The CTV isolates in China shared a most common recent ancestor around 1875 (95% credibility interval: 1676.57 ~ 1961.02). The CTV in China was originated from wild citrus in Hunan and Jiangxi, and then spread from the wild citrus to cultivated citrus in the growing regions of Sichuan, Chongqing, Hubei, Fujian, Zhejiang, Guangxi and Guangdong provinces. CONCLUSIONS: This study has proved that CTV in China was originated from wild citrus in Hunan and Jiangxi. The spatial-temporal distribution and dispersal patterns has uncovered the population and pandemic history of CTV, providing hints toward a better understanding of the spread and origin of CTV in China.

Reinvestigation on the Mechanism for Algae Inactivation by the Ultraviolet/Peracetic Acid Process: Role of Reactive Species and Performance in Natural Water.

This study provided an in-depth understanding of enhanced algae inactivation by combining ultraviolet and peracetic acid (UV/PAA) and selecting Microcystis aeruginosa as the target algae species. The electron paramagnetic resonance (EPR) tests and scavenging experiments provided direct evidence on the formed reactive species (RSs) and indicated the dominant role of RSs including singlet oxygen (1O2) and hydroxyl (HO•) and organic (RO•) radicals in algae inactivation. Based on the algae inactivation kinetic model and the determined steady-state concentration of RSs, the contribution of RSs was quantitatively assessed with the second-order rate constants for the inactivation of algae by HO•, RO•, and 1O2 of 2.67 × 109, 3.44 × 1010, and 1.72 × 109 M-1 s-1, respectively. Afterward, the coexisting bi/carbonate, acting as a shuttle, that promotes the transformation from HO• to RO• was evidenced to account for the better performance of the UV/PAA system in algae inactivation under the natural water background. Subsequently, along with the evaluation of the UV/PAA preoxidation to modify coagulation-sedimentation, the possible application of the UV/PAA process for algae removal was advanced.

Non-Radical Activation of Peracetic Acid by Powdered Activated Carbon for the Degradation of Sulfamethoxazole.

Environmental-friendly and low-cost catalysts for peracetic acid (PAA) activation are vital to promote their application for micropollutant degradation in water. In this study, powdered activated carbon (PAC) was reported to improve the degradation of sulfamethoxazole (SMX). The improvement of SMX degradation in the PAC/PAA system was expected to be because of the PAA activation rather than the co-existing H2O2 activation. Non-radical oxidation pathways, including the mediated electron-transfer process and singlet oxygen (1O2), were evidenced to play the dominant roles in the degradation of micro-organic pollutants. The graphitization of PAC, persistent free radicals, and electron-donating groups like C-OH were proposed to contribute to the activation of PAA. High SMX degradation could be achieved in the acidic and neutral conditions in the PAC/PAA system. Overall, higher dosages of PAC (0-0.02 g/L) and PAA (0-100 µM) benefited the degradation of SMX. The presence of HCO3- could lower the SMX degradation significantly, while Cl-, PO43-, and humic acid (HA) only reduced the SMX degradation efficiency a little. Overall, this study offered an efficient non-radical PAA activation method using PAC, which can be effectively used to degrade micro-organic pollutants.

Surface sampling for SARS-CoV-2 RNA in workplace outbreak settings in the UK, 2021-22.

AIMS: To utilize environmental surface sampling to evaluate areas of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contamination within workplaces to identify trends and improve local coronavirus disease 2019 (COVID-19) control measures. METHODS AND RESULTS: Surface sampling was undertaken at 12 workplaces that experienced a cluster of COVID-19 cases in the workforce between March 2021 and March 2022. A total of 7.4% (61/829) samples collected were positive for SARS-CoV-2 RNA by the quantitative PCR (qPCR) with only 1.8% (15/829) of samples identified with crossing threshold (Ct) values <35.0. No sample returned whole-genome sequence inferring RNA detected was degraded. CONCLUSIONS: Few workplace surface samples were positive for SARS-CoV-2 RNA and positive samples typically contained low levels of nucleic acid. Although these data may infer a low probability of fomite transmission within the workplace, Ct values may have been lower at the time of contamination. Workplace environmental sampling identified lapses in COVID-19 control measures within individual sites and showed trends throughout the pandemic.

A SARS-CoV-2 outbreak in a plastics manufacturing plant.

BACKGROUND: A SARS-CoV-2 outbreak with an attack rate of 14.3% was reported at a plastics manufacturing plant in England. METHODS: Between 23rd March and 13th May 2021, the COVID-OUT team undertook a comprehensive outbreak investigation, including environmental assessment, surface sampling, molecular and serological testing, and detailed questionnaires, to identify potential SARS-CoV-2 transmission routes, and workplace- and worker-related risk factors. RESULTS: While ventilation, indicated using real-time CO2 proxy measures, was generally adequate on-site, the technical office with the highest localized attack rate (21.4%) frequently reached peaks in CO2 of 2100ppm. SARS-CoV-2 RNA was found in low levels (Ct ≥35) in surface samples collected across the site. High noise levels (79dB) were recorded in the main production area, and study participants reported having close work contacts (73.1%) and sharing tools (75.5%). Only 20.0% of participants reported using a surgical mask and/or FFP2/FFP3 respirator at least half the time and 71.0% expressed concerns regarding potential pay decreases and/or unemployment due to self-isolation or workplace closure. CONCLUSIONS: The findings reinforce the importance of enhanced infection control measures in manufacturing sectors, including improved ventilation with possible consideration of CO2 monitoring, utilising air cleaning interventions in enclosed environments, and provision of good-quality face masks (i.e., surgical masks or FFP2/FFP3 respirators) especially when social distancing cannot be maintained. Further research on the impacts of job security-related concerns is warranted.

Characteristics, sources and health risk assessment of trace metals and polycyclic aromatic hydrocarbons in PM2.5 from Hefei, China.

Trace metals (TRs) and polycyclic aromatic hydrocarbons (PAHs) are major toxic components of fine particulate matter (PM2.5) and related to various health adverse outcomes. The study aims to get a better understanding of the contents, sources and risks of PM2.5-bounded TRs and PAHs in Hefei, China, during the period of 2019-2021. We collected 504 samples and measured twelve TRs and sixteen priority PAHs by inductively coupled plasma mass spectrometry and high-performance liquid chromatography. The annual mass concentrations of PM2.5 was fluctuated in the year of 2019-2021 at 50.95, 47.48 and 59.38 µg/m3, with seasonal variations in rank order of winter > spring > autumn > summer. The median concentrations of PM2.5-bounded Æ©TRs and Æ©PAHs were also fluctuated, 132.85, 80.93 and 120.27 ng/m3 for Æ©TRs, 2.57, 5.85 and 2.97 ng/m3 for Æ©PAHs, in the year of 2019, 2020 and 2021, respectively. Seasonal variations of Æ©TRs and Æ©PAHs show the highest concentration in winter. Positive matrix factorization was used for identified pollution emission sources, and TRs mainly originated from coal combustion, traffic emission and fugitive dust, while PAHs stemmed from biomass, diesel, gasoline and coal combustion. Health risk assessment indicated that adults were more vulnerable than children, the carcinogenic risk assessment of As and Cr manifested a certain degree of cancer risk (1.0 × 10-6 < CR < 1.0 × 10-4) in adults group, and health risks of TRs were higher than PAHs in Hefei. These findings suggest that PM2.5-bounded TRs and PAHs should be considered when making emission control strategies for air pollution, and winter, combustion sources and adults should achieve more policy attention to decrease exposure risks in Hefei.

The Composite-Template Method to Construct Hierarchical Carbon Nanocages for Supercapacitors with Ultrahigh Energy and Power Densities.

3D hierarchical carbon nanocages (hCNC) are becoming new platforms for advanced energy storage and conversion due to their unique structural characteristics, especially the combination of multiscale pore structure with high conductivity of sp2 carbon frameworks, which can promote the mass/charge synergetic transfer in various electrochemical processes. Herein, the MgO@ZnO composite-template method is developed to construct hCNC and nitrogen-doped hCNC (hNCNC), which integrates the advantages of the in situ MgO template method and ZnO self-sacrificing template method. The hierarchical MgO template provides the scaffold for depositing carbon nanocages, while the self-sacrificing ZnO template helps create abundant micropores while promoting the graphitization degree, so that the microstructures of the products are effectively regulated. The optimized hCNC and hNCNC have an increased specific surface area and conductivity, which can further boost the mass/charge synergetic transfer. As the electrode materials of supercapacitors, the optimal hCNC(hNCNC) exhibits a high specific capacitance of 281(348) F g-1 in KOH and 276(297) F g-1 in EMIMBF4 electrolytes at 1 A g-1 . The ultrahigh energy and power densities are realized, accompanied by a high-rate capability and long cycling stability. The record-high energy densities of 141.8-71.4 Wh kg-1 are achieved in EMIMBF4 at power densities of 10.0-250.4 kW kg-1 .

A genome-scale nutrient minimization forecast algorithm for controlling essential amino acid levels in CHO cell cultures.

Mammalian cell culture processes rely heavily on empirical knowledge in which process control remains a challenge due to the limited characterization/understanding of cell metabolism and inability to predict the cell behaviors. This study facilitates control of Chinese hamster ovary (CHO) processes through a forecast-based feeding approach that predicts multiple essential amino acids levels in the culture from easily acquired viable cell density data. Multiple cell growth behavior forecast extrapolation approaches are considered with logistic curve fitting found to be the most effective. Next, the nutrient-minimized CHO genome-scale model is combined with the growth forecast model to generate essential amino acid forecast profiles of multiple CHO batch cultures. Comparison of the forecast with the measurements suggests that this algorithm can accurately predict the concentration of most essential amino acids from cell density measurement with error mitigated by incorporating off-line amino acids concentration measurements. Finally, the forecast algorithm is applied to CHO fed-batch cultures to support amino acid feeding control to control the concentration of essential amino acids below 1-2 mM for lysine, leucine, and valine as a model over a 9-day fed batch culture while maintaining comparable growth behavior to an empirical-based culture. In turn, glycine production was elevated, alanine reduced and lactate production slightly lower in control cultures due to metabolic shifts in branched-chain amino acid degradation. With the advantage of requiring minimal measurement inputs while providing valuable and in-advance information of the system based on growth measurements, this genome model-based amino acid forecast algorithm represent a powerful and cost-effective tool to facilitate enhanced control over CHO and other mammalian cell-based bioprocesses.