Emerging Directions for Carbon Capture Technologies: A Synergy of High-Throughput Theoretical Calculations and Machine Learning.

As the world grapples with the challenges of energy transition and industrial decarbonization, the development of carbon capture technologies presents a promising solution. The Scalable Modeling, Artificial Intelligence (AI), and Rapid Theoretical calculations, referred as SMART here, is an interdisciplinary approach that combines high-throughput calculation and data-driven modeling with expertise from chemical, materials, environmental, computer and data science and engineering, leading to the development of advanced capabilities in simulating and optimizing carbon capture processes. This perspective discusses the state-of-the-art material discovery research enabled by high-throughput calculation and data-driven modeling. Further, we propose a framework for material discovery, and illustrate the synergies among deep learning models, pretrained models, and comprehensive data sets, emerging as a robust framework for data-driven design and development in carbon capture. In essence, the adoption of the SMART approach promises a revolutionary impact on efforts in energy transition and industrial decarbonization.

Randomised Controlled Trial of Self-Affirmation Intervention on Students' Academic Performance: Promising Impacts on Students from Migrant Hukou Status.

Purpose: Drawing from the sociocultural-self model, this study aims to examine the influence of self-affirmation on the academic outcomes of lower-class migrant students, as well as the psychological mechanism underlying this phenomenon. Patients and Methods: A field experiment was conducted at a comprehensive secondary school in the southern region of China. Our study sample comprised 1534 immigrant students from diverse regions across the country, with an average proportion of 59.6% of students registered with a rural hukou. The hukou system plays a pivotal role in measuring social class in China, thus it was used as a proxy for lower and higher social class, with rural hukou students considered to be lower-class and urban hukou students considered to be higher-class. Prior to the English test, students in the self-affirmed group were engaged in a brief writing exercise that focused on their core values, whereas the control group wrote about a neutral topic. Results: The primary outcome of interest was the effect of self-affirmation on English test scores, whereas the secondary outcome was the students' survey stereotype threat. The results exhibit that self-affirmation more significantly improved the English test performance of lower-class students compared to higher-class students, and this positive effect was mediated by reducing stereotype threat. Conclusion: Our findings unravel the impact of self-affirmation on the academic performance of migrant students from different social classes and signify the mediating role of stereotype threat in this process. The present study extends previous findings to students from immigrant families in the Chinese cultural context, and these findings demonstrate that self-affirmation can constitute a promising intervention for stereotype threat and achievement gaps due to social class differences in immigrant family groups. Considering that this intervention takes only about 15 minutes of time, entails almost zero cost, does no harm, and that it focuses on disadvantaged immigrant students, it may provide valuable insights for educational policies to be implemented in a new type of migrant city such as Shenzhen.

AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS).

Zero-carbon energy and negative emission technologies are crucial for achieving a carbon neutral future, and nanomaterials have played critical roles in advancing such technologies. More recently, due to the explosive growth in data, the adoption and exploitation of artificial intelligence (AI) as part of the materials research framework have had a tremendous impact on the development of nanomaterials. AI has enabled revolutionary next-generation paradigms to significantly accelerate all stages of material discovery and facilitate the exploration of the enormous design space. In this review, we summarize recent advancements of AI applications in nanomaterials discovery, with a special emphasis on the selected applications of AI and nanotechnology for the net-zero emission future including the development of solar cells, hydrogen energy, battery materials for renewable energy, and CO2 capture and conversion materials for carbon capture, utilization and storage (CCUS) technologies. In addition, we discuss the limitations and challenges of current AI applications in this area by identifying the gaps that exist in current development. Finally, we present the prospect for future research directions in order to facilitate the large-scale applications of artificial intelligence for advancements in nanomaterials.

Intensive care unit-acquired pneumonia caused by Klebsiella pneumoniae in China: Risk factors and prediction model of mortality.

Intensive care unit (ICU)-acquired pneumonia (ICUAP) is a major concern owing to its associated high mortality rate. Few studies have focused on ICUAP caused by Klebsiella pneumoniae (KP). This study aimed to investigate the risk factors for ICUAP-associated death due to KP and to develop a mortality prediction model. Patients with KP-associated ICUAP at Renji Hospital were enrolled from January 2012 to December 2017. The patients were registered from the ICU units of the Surgery, Gynecology and Obstetrics, Neurosurgery, Emergency and Geriatric Departments, and were followed for 30 days. A multivariate analysis was performed to analyze the differences between 30-day survivors and nonsurvivors, and to determine the independent risk factors. Receiver operator characteristic (ROC) curves were also used to determine the predictive power of the model. Among the 285 patients with KP-associated ICUAP, the median age was 70.55 years, and 61.6% were men. Fifty patients died. The nonsurvivors had a lower Glasgow coma score (GCS), platelet count, and albumin concentrations, but higher lactate concentrations, than the survivors. The nonsurvivors were also more likely to be admitted to the ICU for respiratory failure and surgery, and they received less appropriate empirical antimicrobial therapy than the survivors. A lower GCS (odds ratio [OR] = 0.836, 95% confidence interval [CI]: 0.770-0.907), lower albumin concentrations (OR = 0.836, 95% CI: 0.770-0.907), higher lactate concentrations (OR = 1.167, 95% CI: 1.0013-1.344) and inappropriate empirical treatment (OR = 2.559, 95% CI: 1.080-6.065) were independent risk factors for mortality in patients with KP-associated ICUAP. ROC curve analysis showed that the risk of death was higher in patients with 2 or more independent risk factors. The predictive model was effective, with an area under the ROC curve of 0.823 (95% CI: 0.773-0.865). The number of independent risk factors is positively correlated with the risk of death. Our model shows excellent predictive performance.

Pancancer Analysis of Revealed TDO2 as a Biomarker of Prognosis and Immunotherapy.

Background: Tryptophan 2,3-dioxygenase (TDO) encoded by TDO2, a rate-limiting enzyme in the kynurenine pathway, catabolizes tryptophan to kynurenine, evades immune surveillance, and promotes tumor growth. Although accumulating evidence suggests a crucial role of TDO2 during tumor formation and development, systematic evaluation of TDO2 across human cancers has rarely been reported. Methods: To shed more light on the role of TDO2 in human cancer, we explored the expression profiles of TDO2 and identified its prognostic value in pancancer analysis through TCGA, CCLE, and GTEx databases. We further utilized TCGA data to evaluate the association between TDO2 and tumor immunological features, such as mismatch repair (MMR), tumor immune infiltration, immune checkpoint-related genes, tumor mutational burden (TMB), microsatellite instability (MSI), and DNA methyltransferase (DNMT). Results: TDO2 exhibited different expression levels in various cancer cell lines. Frequently, TDO2 was detected to be highly expressed in the majority of cancers. In addition, high TDO2 expression was correlated with an unfavorable prognosis for patients in KIRP, LGG, TGCT, and UVM. Moreover, high TDO2 expression level positively correlated with higher immune infiltration, especially dendritic cells. Additionally, there is a close relationship between TDO2 and immune checkpoint-related gene markers, such as LAIR1, CD276, NRP1, CD80, and CD86. Finally, correlation analysis has demonstrated a high-correlation between TDO2 and TMB, MSI, MMR, and DNMT of multiple cancer types. Conclusion: Therefore, our results suggest that TDO2 can function as a potential prognostic biomarker due to its role in tumor immunity regulation.

Hydrogen Transfer Coupling with 100% Atom Economy: Synthesis of 2-Indolyltetrahydronaphthyridine Derivatives.

An iridium-catalyzed hydrogen transfer strategy, enabling straightforward access to tetrahydropyridine derivatives from aryl-1,8-naphthyridines and indolines was developed. This method has unprecedented advantages, including high step economy. In addition, it does not produce any byproducts or require an external high-pressure H2 gas source. The method offers an important platform for the transformation of 1,8-naphthyridines and indolines into functionalized products.

Exploration of the Molecular Mechanism of Danzhi Xiaoyao Powder in Endometrial Cancer through Network Pharmacology.

Endometrial cancer (EC) is a common malignant tumor of the female reproductive system. Current treatments such as surgery and long-term hormone therapy are ineffective and have side effects. Danzhi Xiaoyao powder (DXP) can inhibit the growth of EC cells and induce apoptosis, but the pharmacological and molecular mechanisms of anticancer effects are still unclear. In this study, active components and potential targets of DXP were obtained from public databases. Protein effects and regulatory pathways of common targets were analyzed by protein-protein interaction (PPI), GO and KEGG. The results of network pharmacology showed that there are 87 common targets between EC and DXP. GO enrichment analysis showed that these targets were associated with response to oxidative stress, response to nutrient levels, hormone receptor binding and nuclear hormone receptor binding, etc. The results of KEGG analysis indicated that IL-17, TNF, PI3K/AKT, and RAS/RAF/MEK/ERK (ERK) signaling pathway were enriched in the anti-EC of DXP. Additionally, we cultured HEC-1B and KLE cells for validate experiments. DXP showed an inhibition of proliferation, migration, and cell cycle of both cells. Moreover, the expression of RAS, p-RAF, p-MEK, ERK, and p-ERK related proteins were downregulated. In conclusion, DXP might inhibit the proliferation of EC cells via apoptosis. Furthermore, DXP-induced inhibition of EC development might involve RAS/RAF/MEK/ERK pathway.

Household waste management in Singapore and Shanghai: Experiences, challenges and opportunities from the perspective of emerging megacities.

Due to rapid economic development and urbanisation, emerging megacities with dense populations have witnessed a significant increase in waste generation. Megacities face challenges in developing sustainable waste management systems. Considerable heterogeneity exists across megacities in management strategies. The two selected emerging megacities, Singapore (a city-state) and Shanghai, have similar developmental characteristics, but their waste management modes differ strikingly. This study assessed the two modes in terms of management strategies, environmental effects, economic costs, and social outcomes. Environmental footprint analysis and cost quantification were employed for the assessment based on public data. The research results would permit a deeper understanding of the long-term sustainability of each mode while considering the feasibility of implementation across different contexts. It was found that the waste management system in Singapore had a relatively lower environmental impact than Shanghai before Shanghai's new waste segregation and recycling policy in 2019. However, when the effect of fossil fuel substitution is taken into account, the environmental burden in Shanghai can be lowered more substantially than the one in Singapore. Although Shanghai had more economic burden for the waste segregation at source, it tended to implement the circular economy principles (e.g., reduce, reuse, and recycling) better and improve its sense of community significantly. Based on the practical experiences from the two representative megacities, suggestions for better waste management practices were provided for Singapore, Shanghai, and other emerging megacities with similar circumstances. In addition, challenges and opportunities related to household waste segregation and recycling were identified to guide future practices in emerging megacities.

Fucoxanthin prevents cell growth and induces apoptosis in endometrial cancer HEC-1A cells by the inhibition of the PI3K/Akt/mTOR pathway.

Endometrial cancer is the major type of gynecological cancer and ranks as the sixth most common cancer in women. Endometrial cancer usually is diagnosed in an advanced stage, complicating the treatments in many cases. The present research was focused on unveiling the in vitro anticancer role of fucoxanthin against the endometrial cancer HEC-1A cells by inhibiting the phosphatidylinositol-3-kinase/Akt/mammalian target of rapamycin (PI3K/Akt/mTOR) signaling axis. The cytotoxicity of fucoxanthin against the endometrial cancer HEC-1A cells was studied using the MTT test. The level of reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP) status, and apoptotic cell death in the 7.5 and 10 µM administered HEC-1A cells were assayed using fluorescent staining techniques. The messenger RNA expression was analyzed using RT-PCR for PI3K/Akt/mTOR signaling molecules, proapoptotic (Bax and caspase-3) antiapoptotic (cyclin D1 and Bcl-2) genes, and inflammatory markers like tumour necrosis factor α (TNFα), nuclear factor kappa B (NF-κB), Cox-2, and interleukin (IL)-6. The cell viability assay proved that fucoxanthin effectively prevented HEC-1A cell viability, where the IC50 was 7.5 µM. Fucoxanthin at 7.5 and 10 µM remarkably improved ROS production and apoptosis and decreased the MMP in HEC-1A cells. The fucoxanthin effectively inhibited the PI3K/Akt/mTOR cascade along with the expression of TNF-α, NF-κB, Cox-2, and IL-6 and antiapoptotic genes cyclin D1 and Bcl-2 in the HEC-1A cells. Fucoxanthin treatment also enhanced the Bax and caspase-3 expressions in the HEC-1A cells. Our results from this work unveiled that fucoxanthin triggered growth inhibition and apoptosis in endometrial cancer HEC-1A cells. Besides, fucoxanthin inhibited the PI3K/Akt/mTOR cascade and improved apoptotic marker expressions in the HEC-1A cells.

Prediction of Soil Heavy Metal Immobilization by Biochar Using Machine Learning.

Biochar application is a promising strategy for the remediation of contaminated soil, while ensuring sustainable waste management. Biochar remediation of heavy metal (HM)-contaminated soil primarily depends on the properties of the soil, biochar, and HM. The optimum conditions for HM immobilization in biochar-amended soils are site-specific and vary among studies. Therefore, a generalized approach to predict HM immobilization efficiency in biochar-amended soils is required. This study employs machine learning (ML) approaches to predict the HM immobilization efficiency of biochar in biochar-amended soils. The nitrogen content in the biochar (0.3-25.9%) and biochar application rate (0.5-10%) were the two most significant features affecting HM immobilization. Causal analysis showed that the empirical categories for HM immobilization efficiency, in the order of importance, were biochar properties > experimental conditions > soil properties > HM properties. Therefore, this study presents new insights into the effects of biochar properties and soil properties on HM immobilization. This approach can help determine the optimum conditions for enhanced HM immobilization in biochar-amended soils.

Pyroptosis: A Developing Foreland of Ovarian Cancer Treatment.

Ovarian cancer (OVCA) has the second highest mortality among all gynecological cancers worldwide due to its complexity and difficulty in early-stage diagnosis and a lack of targeted therapy. Modern strategies of OVCA treatment involve debulking surgery combined with chemotherapy. Nonetheless, the current treatment is far from satisfactory sometimes and therefore the demand for novel therapeutic measures needs to be settled. Pyroptosis is a notable form of programmed cell death characterized by influx of sodium with water, swelling of cells, and finally osmotic lysis, which is distinctive from numerous classes of programmed cell death. So far, four major pathways underlying mechanisms of pyroptosis have been identified and pyroptosis is indicated to be connected with a variety of disorders including cancerous diseases. Interestingly enough, pyroptosis plays an important role in ovarian cancer with regard to long non-coding RNAs and several regulatory molecules, as is shown by previously published reports. In this review, we summarized major pathways of pyroptosis and the current research foundations of pyroptosis and ovarian cancer, anticipating enriching the thoughts for the treatment of ovarian cancer. What is more, some problems yet unsolved in this field were also raised to hopefully propose several potential threads of OVCA treatment and research directions in future.

Wet wastes to bioenergy and biochar: A critical review with future perspectives.

The ever-increasing rise in the global population coupled with rapid urbanization demands considerable consumption of fossil fuel, food, and water. This in turn leads to energy depletion, greenhouse gas emissions and wet wastes generation (including food waste, animal manure, and sewage sludge). Conversion of the wet wastes to bioenergy and biochar is a promising approach to mitigate wastes, emissions and energy depletion, and simultaneously promotes sustainability and circular economy. In this study, various conversion technologies for transformation of wet wastes to bioenergy and biochar, including anaerobic digestion, gasification, incineration, hydrothermal carbonization, hydrothermal liquefaction, slow and fast pyrolysis, are comprehensively reviewed. The technological challenges impeding the widespread adoption of these wet waste conversion technologies are critically examined. Eventually, the study presents insightful recommendations for the technological advancements and wider acceptance of these processes by establishing a hierarchy of factors dictating their performance. These include: i) life-cycle assessment of these conversion technologies with the consideration of reactor design and catalyst utilization from lab to plant level; ii) process intensification by integrating one or more of the wet waste conversion technologies for improved performance and sustainability; and iii) emerging machine learning modeling is a promising strategy to aid the product characterization and optimization of system design for the specific to the bioenergy or biochar application.

Restoring mammary gland structures and functions with autogenous cell therapy.

In somatic cell reprogramming, cells must escape the somatic cell-specific gene expression program to adopt other cell fates. Here, in vitro chemical induction with RepSox generated chemically induced mammary epithelial cells (CiMECs) with milk secreting functions from goat ear fibroblasts (GEFs). Transplanted CiMECs regenerated the normal mammary gland structure with milk-secreting functions in nude mice. Single-cell RNA sequencing revealed that during the reprogramming process, GEFs may sequentially undergo embryonic ectoderm (EE)-like and different MEC developmental states and finally achieve milk secreting functions, bypassing the pluripotent state. Mechanistically, Smad3 upregulation induced by transforming growth factor ß (TGFß) receptor 1 (TGFßR1) downregulation led to GEF reprogramming into CiMECs without other reprogramming factors. The TGFßR1-Smad3 regulatory effects will provide new insight into the TGFß signaling pathway regulation of somatic cell reprogramming. These findings suggest an innovative strategy for autogenous cell therapy for mammary gland defects and the production of transgenic mammary gland bioreactors.

Ferroptosis in Ovarian Cancer: A Novel Therapeutic Strategy.

Ovarian cancer (OVCA) is one of the most lethal malignancies with a five-year relative survival below 50% by virtue of its high recurrence rate and inadequate early detection methods. For OVCA patients, modern approaches include debulking surgery, chemotherapies, angiogenesis inhibitors, poly ADP-ribose polymerase (PARP) inhibitors, and immunotherapies depending on the histological type and staging of the tumor. However, in most cases, simple standard treatment is not satisfactory. Thus, a more effective way of treatment is needed. Ferroptosis is a newly recognized type of regulated cell death marked by lipid peroxidation, iron accumulation and glutathione deprivation, having a connection with a variety of disorders and showing great potential in anti-tumor therapy. Intriguingly, a possible connection between ferroptosis and OVCA is shown on the basis of previously published findings. Furthermore, a growing number of ferroptosis protection pathways have been identified during the past few years with increasing ferroptosis regulators being discovered. In this review, we summarized several major pathways involved in ferroptosis and the study foundation of ferroptosis and ovarian cancer, hoping to provide clues regarding OVCA treatment. And some important issues were also raised to point out future research directions.

Clinical characteristics and risk factors for mortality in patients with coronavirus disease 2019 in intensive care unit: a single- center, retrospective, observational study in China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a potentially life-threatening contagious disease which has spread all over the world. Risk factors associated with the clinical outcomes of COVID-19 pneumonia in intensive care unit (ICU) have not yet been well determined. METHODS: This was a retrospective, single-centered, observational study, in which 47 patients with confirmed COVID-19 were consecutively enrolled from February 24 to April 5, 2020. The patients were registered from the ICU of Leishenshan Hospital in Wuhan, China. Clinical characteristics and outcomes were collected and compared between survivors and non-survivors. Multivariable logistic regression was performed to analyze the risk factors of death in patients with COVID-19. RESULTS: The study cohort included 47 adult patients with an average age of 70.55±12.52 years, and 30 (63.8%) patients were men. Totally 15 (31.9%) patients died. When compared to survivors, nonsurvivors showed a higher proportion of septic shock [6 (40%) patients vs. 3 (9.4%) patients], disseminated intravascular coagulation [3 (21.4%) vs. 0], and had higher score of APACHE II (25.07±8.03 vs. 15.56±5.95), CURB-65 {3 [2-4] vs. 2 [1-3]}, Sequential Organ Failure Assessment (SOFA) {7 [5-9] vs. 3 [1-6]}, higher level of D-dimer {5.74 [2.32-18] vs 2.05 [1.09-4.00]} and neutrophil count {9.4 [7.68-14.54] vs. 5.32 [3.85-9.34]}. SOFA score (OR 1.47; 95% CI: 1.01-2.13; P=0.0042) and the lymphocyte count (OR 0.02; 95% CI: 0.00-0.86; P=0.042) on admission were independently risk factors for mortality. Patients with higher lymphocyte count (>0.63×109 /L) and lower SOFA score (≤4) on admission had a significantly better prognosis than those with lower lymphocyte count (≤0.63×109 /L) and higher SOFA score (>4) in overall survival. CONCLUSIONS: Higher SOFA score and lower lymphocyte count at admission were connected with poor prognosis of patients with COVID-19 in ICU. Lymphocyte count may serve as a promising prognostic biomarker.

Meteorological factors, governmental responses and COVID-19: Evidence from four European countries.

With the global lockdown, meteorological factors are highly discussed for COVID-19 transmission. In this study, national-specific and region-specific data sets from Germany, Italy, Spain and the United Kingdom were used to explore the effect of temperature, absolute humidity and diurnal temperature range (DTR) on COVID-19 transmission. From February 1st to November 1st, a 7-day COVID-19 case doubling time (Td), meteorological factors with cumulative 14-day-lagged, government response index and other factors were fitted in the distributed lag nonlinear models. The overall relative risk (RR) of the 10th and the 25th percentiles temperature compared to the median were 0.0074 (95% CI: 0.0023, 0.0237) and 0.1220 (95% CI: 0.0667, 0.2232), respectively. The pooled RR of lower (10th, 25th) and extremely high (90th) absolute humidity were 0.3266 (95% CI: 0.1379, 0.7734), 0.6018 (95% CI: 0.4693, 0.7718) and 0.3438 (95% CI: 0.2254, 0.5242), respectively. While the DTR did not have a significant effect on Td. The total cumulative effect of temperature (10th) and absolute humidity (10th, 90th) on Td increased with the change of lag days. Similarly, a decline in temperature and absolute humidity at cumulative 14-day-lagged corresponded to the lower RR on Td in pooled region-specific effects. In summary, the government responses are important factors in alleviating the spread of COVID-19. After controlling that, our results indicate that both the cold and the dry environment also likely facilitate the COVID-19 transmission.

Airborne particulate matter, population mobility and COVID-19: a multi-city study in China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, which has caused numerous deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution and population mobility on COVID-19 across China. METHODS: We obtained daily confirmed cases of COVID-19, air particulate matter (PM2.5, PM10), weather parameters such as ambient temperature (AT) and absolute humidity (AH), and population mobility scale index (MSI) in 63 cities of China on a daily basis (excluding Wuhan) from January 01 to March 02, 2020. Then, the Generalized additive models (GAM) with a quasi-Poisson distribution were fitted to estimate the effects of PM10, PM2.5 and MSI on daily confirmed COVID-19 cases. RESULTS: We found each 1 unit increase in daily MSI was significantly positively associated with daily confirmed cases of COVID-19 in all lag days and the strongest estimated RR (1.21, 95% CIs:1.14 ~ 1.28) was observed at lag 014. In PM analysis, we found each 10 µg/m3 increase in the concentration of PM10 and PM2.5 was positively associated with the confirmed cases of COVID-19, and the estimated strongest RRs (both at lag 7) were 1.05 (95% CIs: 1.04, 1.07) and 1.06 (95% CIs: 1.04, 1.07), respectively. A similar trend was also found in all cumulative lag periods (from lag 01 to lag 014). The strongest effects for both PM10 and PM2.5 were at lag 014, and the RRs of each 10 µg/m3 increase were 1.18 (95% CIs:1.14, 1.22) and 1.23 (95% CIs:1.18, 1.29), respectively. CONCLUSIONS: Population mobility and airborne particulate matter may be associated with an increased risk of COVID-19 transmission.

Clinical characteristics and risk factors of catheter-associated urinary tract infections caused by Klebsiella Pneumoniae.

BACKGROUND: The clinical characteristics and risk factors of catheter-associated urinary tract infections (CAUTIs) caused by Klebsiella pneumoniae (KP) have not been well investigated. METHODS: This retrospective study performed at a university teaching hospital in China from January 2012 to November 2017 analyzed data for 227 patients with urinary tract infection (UTI) caused by KP. Patients' demographic characteristics and clinical outcomes were recorded. Risk factors were analyzed using a binary logistic regression model. RESULTS: Of 227 patients with Klebsiella pneumoniae-related urinary tract Infection (KP-UTI), the infection was catheter-associated in 90 patients. More than half of them were male (60%), over 60 years old, hospitalized in general ward, always acquired in hospital, and got a longer hospitalization more than one month. The Klebsiella pneumoniae-related catheter-associated urinary tract infections (KP-CAUTIs) patients always combined with lots of chronic comorbidities. A high proportion of invasive device, extendedspectrum ß-lactamase (ESBL) expression and multidrug resistance (MDR) were found in KP-CAUTIs patients. When taken antimicrobial activity into consideration, KP-CAUTIs patients performed resistance to most antibiotics in varying degrees. Logistic regression analysis revealed that after grouping by ESBL expression and in-hospital mortality among patients with KP-CAUTI, complicated urinary tract infection (cUTI) was an independent risk factor for ESBL positive KP-CAUTIs [odds ratio (OR) 59.256; 95% CI, 3.417-1,027.628; P=0.005], whereas congestive heart failure was identified as an independent risk factor for in-hospital mortality (OR 25.592; 95% CI, 2.376-275.629; P=0.008) in KP-CAUTI patients. CONCLUSIONS: Patients with KP-CAUTI displayed distinctive characteristics. cUTI and congestive heart failure were independently associated with ESBL expression and in-hospital mortality in patients with KPCAUTI.

Association of air pollution with outpatient visits for respiratory diseases of children in an ex-heavily polluted Northwestern city, China.

BACKGROUND: A great number of studies have confirmed that children are a particularly vulnerable population to air pollution. METHODS: In the present study, 332,337 outpatient visits of 15 hospitals for respiratory diseases among children (0-13 years), as well as the simultaneous meteorological and air pollution data, were obtained from 2014 to 2016 in Lanzhou, China. The generalized additive model was used to examine the effects of air pollutants on children's respiratory outpatient visits, including the stratified analysis of age, gender and season. RESULTS: We found that PM2.5, NO2 and SO2 were significantly associated with the increased total respiratory outpatient visits. The increments of total respiratory outpatient visits were the highest in lag 05 for NO2 and SO2, a 10 µg/m3 increase in NO2 and SO2 was associated with a 2.50% (95% CI: 1.54, 3.48%) and 3.50% (95% CI: 1.51, 5.53%) increase in total respiratory outpatient visits, respectively. Those associations remained stable in two-pollutant models. Through stratification analysis, all air pollutants other than PM10 were significantly positive associated with the outpatients of bronchitis and upper respiratory tract infection. Besides, both NO2 and SO2 were positively related to the pneumonia outpatient visits. PM2.5 and SO2 were significantly related to the outpatient visits of other respiratory diseases, while only NO2 was positively associated with the asthma outpatients. We found these associations were stronger in girls than in boys, particularly in younger (0-3 years) children. Interestingly, season stratification analysis indicated that these associations were stronger in the cold season than in the transition or the hot season for PM10, PM2.5 and SO2. CONCLUSIONS: Our results indicate that the air pollution exposure may account for the increased risk of outpatient visits for respiratory diseases among children in Lanzhou, particularly for younger children and in the cold season.