Highly Stable Triangular Single-Layer 2D Assemblies: Synthesis and Their Stimuli-Responsive Elastic and Anisotropic Curling.

Synthesis of highly stable two-dimensional single-layer assemblies (SLAs) is a key challenge in supramolecular science, especially those with long-range molecular order and well-defined morphology. Here, thin (thickness <2 nm) triangular AuI -thiolate SLAs with high thermo-, solvato- and mechano- stability have been synthesized via a double-ligand co-assembly strategy. Furthermore, the SLAs show assembly-level elastic and anisotropic deformation responses to external stimuli as a result of the long-range anisotropic molecular packing, which provides SLAs with new application potentials in bio-mimic nanomechanics.

Combined detection of procalcitonin, heparin-binding protein, and interleukin-6 is a promising assay to diagnose and predict acute pancreatitis.

BACKGROUND: Acute pancreatitis (AP), one of the most common clinical emergencies, is characterized by variable clinical features and inadequate diagnostic methods. At present, the commonly used indicators do not have high specificity and do not necessarily reflect disease severity. We therefore aimed to investigate diagnostic and prognostic value of plasma procalcitonin, heparin-binding protein, and interleukin-6 for acute pancreatitis by separate detection and joint detection. METHODS: The study involved 451 participants, including 343 AP patients and 108 healthy controls. We analyzed the association of the three biomarkers with the severity and prognosis of AP. RESULTS: A statistically significant increase in the mean plasma analyte levels was detected in the study group compared to the control group. Multivariate comparison showed that plasma levels of PCT, HBP, and IL-6 were all significantly different among the three groups at different sampling times (1st, 3rd, 7th, and 10th day of admission) (p < 0.01). The combination of the three indicators had significantly higher diagnostic value than either the individual markers or pairwise combinations (p < 0.001). The levels of the three were all significantly higher in severe acute pancreatitis (SAP) patients than in non-SAP patients (p < 0.001); meanwhile, patients with high levels had a worse prognosis than those with low levels (p < 0.05). In multivariate analysis adjusted for age and sex, high levels of PCT, HBP, and IL-6 were found to be independently associated with the development of AP. CONCLUSIONS: It dramatically improved the diagnostic power of AP when PCT, HBP, and IL-6 were combined; high PCT, HBP, and IL-6 levels within 3 days of admission may be the potentially useful indicators for predicting SAP.

Climate modulation of external forcing factors on air quality change in Eastern China: Implications for PM2.5 seasonal prediction.

Meteorological conditions significantly influence the frequency and duration of air pollution events, making the prediction of seasonal variations of PM2.5 concentration crucial for air quality control. This study analyzed the spatiotemporal variations of PM2.5 concentration anomalies over the past 39 years (1980-2018) in winter (November to January) over eastern China based on the empirical orthogonal function (EOF) method. Regression analysis is conducted on external forcing factors such as sea ice, sea temperature, and snow cover in the pre-autumn (September to October) using the time series of the first three modes. Nine key factors were selected, which further led to establishing a model for predicting winter PM2.5 concentration in eastern China using the long short-term memory deep learning algorithm (LSTM). Independent verification revealed that the predicted and observed PM2.5 concentration distributions were consistent, with the absolute value of deviation within 15 µg·m-3 between 2016 and 2018. The correlation coefficients between the predicted and observed values were between 0.42 and 0.93 over eight key cities in the past 10 years (2009-2018). The contribution rates of the nine factors to PM2.5 concentration were calculated to explore their impact on PM2.5 concentration during winter. The Arctic sea ice (ASI) was found to be the key contributor to the winter PM2.5 concentration in eastern China. The predictors can be monitored in real time; hence, the model provides a real-time predictive tool, improving the prospects of predicting seasonal PM2.5 pollution, especially in vulnerable regions such as eastern China.

PM2.5 extended-range forecast based on MJO and S2S using LightGBM.

We developed an extended-range fine particulate matter (PM2.5) prediction model in Shanghai using the light gradient-boosting machine (LightGBM) algorithm based on PM2.5 historical data, meteorological observational data, Subseasonal-to-Seasonal Prediction Project (S2S) forecasts and Madden-Julian Oscillation (MJO) monitoring data. The analysis and prediction results demonstrated that the MJO improved the predictive skill of the extended-range PM2.5 forecast. The MJO indexes, namely, real-time multivariate MJO series 1 (RMM1) and real-time multivariate MJO series 2 (RMM2), ranked the first, and seventh, respectively, in terms of the predictive contribution of all meteorological predictors. When the MJO was not introduced, the correlation coefficients for the forecasts on lead times of 11-40 days ranged from 0.27 to 0.55, and the root mean square errors (RMSEs) ranged from 23.4 to 31.8 µg/m3. After the MJO was introduced, the correlation coefficients for the 11-40 day forecast ranged from 0.31 to 0.56, among which those for the 16-40 day forecast substantially improved, and the RMSEs ranged from 23.2 to 28.7 µg/m3. When comparing the prediction scores, such as percent correct (PC), critical success index (CSI), and equitable threat score (ETS), the forecast model was more accurate when it introduced the MJO. A novel aspect of this study is to investigate the effects of the MJO mechanism on the meteorological conditions of air pollution in eastern China through advanced regression analysis. The MJO indexes RMM1 and RMM2 considerably impacted the geopotential height field of 28°-40° at 300-250 hPa 45 days in advance. When RMM1 increased and RMM2 decreased 45 days in advance, the 500 hPa geopotential height field weakened accordingly, and the bottom of the 500 hPa trough moved southward; thus cold air was more easily transported southward and the upstream air pollutants were transported to eastern China. With a weak ground pressure field and dry air at low altitudes, the westerly wind component increased, which led to the easier formation of a weather configuration favorable for the accumulation and transport of air pollution, thus resulting in an increase in PM2.5 concentration in the region. These findings can guide forecasters regarding the utility of MJO and S2S for subseasonal air pollution outlooks.

MERRA-2 PM2.5 mass concentration reconstruction in China mainland based on LightGBM machine learning.

MERRA-2 developed by the National Aeronautics and Space Administration (NASA) provides the long-term record of surface PM2.5 mass concentration since 1980s, but needs great improvement over mainland China according to recent studies. In this study, a newly developed light gradient boosting machine (LGBM) model is introduced to correct the MERRA-2 PM2.5 record over mainland China by incorporating the meteorological reanalysis and satellite AOD retrievals. A 40-year surface PM2.5 record covering mainland China is reconstructed from 1980 to 2019, providing a new dataset for exploring the interactions between climate variability and air pollution. The new record exhibits not only much better magnitude but also more excellent variabilities of surface PM2.5 loading compared to original MERRA-2 products. The correlation coefficient, the root-mean-square error and the mean error between the observed and reconstructed records are 0.8, less than 28.5 µg·m-3, and 0.33 µg·m-3, respectively, which are much better than those of 0.27, 45.8 µg·m-3, and 1.64 µg·m-3 between the observed and MERRA-2 PM2.5 records. The PM2.5 record with longer term and higher accuracy developed in this study provides a better base for the research on the climate change variability and air pollution in mainland China. However, limitations of the reconstructed record still exist, especially in the Tibetan Plateau and marine regions with very sparse surface measurements, which need further correction in the future studies.

The nitric oxide synthase gene negatively regulates biofilm formation in Staphylococcus epidermidis.

Staphylococcus epidermidis (S. epidermidis) is a clinically important conditioned pathogen that can cause a troublesome chronic implant-related infection once a biofilm is formed. The nitric oxide synthase (NOS) gene, which is responsible for endogenous nitric oxide synthesis, has already been found in the genome of S. epidermidis; however, the specific mechanisms associated with the effects of NOS on S. epidermidis pathogenicity are still unknown. The purpose of the current study was to investigate whether the NOS gene has an impact on biofilm formation in S. epidermidis. Bioinformatics analysis of the NOS gene was performed, and homologous recombination was subsequently employed to delete this gene. The effects of the NOS gene on biofilm formation of S. epidermidis and its underlying mechanisms were analyzed by bacterial growth assays, biofilm semiquantitative determination, Triton X-100-induced autolysis assays, and bacterial biofilm dispersal assays. Additionally, the transcription levels of fbe, aap, icaA, icaR and sigB, which are related to biofilm formation, were further investigated by qRT-PCR following NOS deletion. Phylogenetic analysis revealed that the NOS gene was conserved between bacterial species originating from different genera. The NOS deletion strain of S. epidermidis 1457 and its counterpart were successfully constructed. Disruption of the NOS gene resulted in significantly enhanced biofilm formation, slightly retarded bacterial growth, a markedly decreased autolysis rate, and drastically weakened bacterial biofilm dispersal. Our data showed that the fbe, aap and icaA genes were significantly upregulated, while the icaR and sigB genes were significantly downregulated, compared with the wild strain. Therefore, these data strongly suggested that the NOS gene can negatively regulate biofilm formation in S. epidermidis by affecting biofilm aggregation and dispersal.

Differential diagnosis and clinical management of isolated prolonged activated partial thromboplastin time in a patient with Hashimoto thyroiditis-associated thyroid cancer: A case report.

RATIONALE: Patients preparing for surgery may have isolated, prolonged activated partial thromboplastin time (APTT). Cause analysis is warranted in patients who had neither bleeding symptom nor thromboembolic events because isolated prolongation of APTT may lead to unnecessary delayed surgical intervention or invasive procedure, even ineffective plasma infusion treatments. Here, we report a case of Hashimoto thyroiditis-associated thyroid cancer whose APTT was isolated prolonged and discuss the challenges of diagnosis and clinical management of this patient. PATIENT CONCERNS: A 57-year-old woman was admitted to the hospital due to thyroid cancer. Anticoagulant assay was performed for this patient before surgery, she had normal values for prothrombin time, thrombin time, and fibrinogen, but had isolated prolonged APTT value (20 seconds longer than normal). However, the routine laboratory of the local hospital showed normal APTT and she did not have any abnormal bleeding or thrombotic episodes. Lupus anticoagulant (LA) was strongly positive according to mixing studies and modified dilute Russell viper venom time method, it was responsible for prolonged APTT. DIAGNOSES: Hashimoto thyroiditis-associated thyroid cancer whose APTT was isolated prolonged. INTERVENTIONS: The isolated prolongation of APTT in this patient was due to LA. She had no history of anticoagulant medications and no spontaneous bleeding episodes. There should be no specific intervention before thyroidectomy. OUTCOMES: This thyroid cancer patient had an uneventful surgery and was discharged after a week. LESSONS: Prolonged APTT is not considered an absolute indication for plasma infusion therapy in patients with LA. The correct identification of the cause of APTT prolongation is essential for proper treatment of the individuals.

[A Numerical Study of Typical Heavy Air Pollution Episode of PM2.5 in Shanghai].

To analyze the characteristics and formation mechanism of a heavy air pollution episode in Shanghai City from January 23th to January 24th, 2013, the observed data of PM2.5 concentration and ground meteorological data and the WRF-Chem model were collected. The analysis revealed that the synoptic necessary mechanism of the heavy air pollution episode could be characterized by the following patterns: Accompanied with weak cold front activities, the city experienced weak winds (i. e. stable atmosphere) at first and then northerly winds (i. e. pollutant transport process ), causing the continuous increase and maintaining of pollutant concentration. The detailed results are shown as follows: Firstly, the stable atmosphere circulation pattern which lasted for 10 hours was not good for air pollution dispersion, as a result, local PM2.5 concentrations continued to increase and reached severe pollution level and the high concentrations maintained for 7 hours caused by the stable boundary layer (e. g. static surface winds and low level temperature inversion) during nighttime, and the average PM2.5 concentrations during the stable weather process was 172.4 µg · m⁻³. Secondly, the dispersion condition was slightly improved later on with the arrival of a weak cold front, the upstream pollution transportation occurred at the same time, leading to further increase of PM2.5 concentration (up to 280 µg · m⁻³), and the average PM2.5 concentration during the upstream transportation process was 213.6 µg · m⁻³. Numerical simulation with the WRF-Chem model showed that, average contribution of upstream transportation to local PM2.5 concentrations during the episode was 23% . Among them, the contribution during the stable weather and upstream transportation stage was 17.2% and 32.2% . Our results suggested that there were significant differences in the contribution of upstream transportation to the local PM2.5 concentration of Shanghai due to variation of weather conditions. Therefore, the government can design effective emission control strategy in advance taking pollution weather forecasting into account.