Microbial Biotransformation of 1-Methyl-L-tryptophan into Herbicidal Indole Alkaloids by Endophytic Fungus Nigrospora chinensis GGY-3.

Indole alkaloids are privileged secondary metabolites, and their production may be achieved by the microbial biotransformation of tryptophan analogues. By feeding 1-methyl-L-tryptophan (1-MT) into the culture of endophytic Nigrospora chinensis GGY-3, six novel (1-6) and seven known indole alkaloids (7-13) were generated. Their structures were elucidated by means of NMR spectroscopy, experimental electronic circular dichroism (ECD) spectra, and X-ray crystallography analysis. A Friedel-Crafts reaction was proposed as the key reaction responsible for the formation of the new compounds. Racemates 4 and 6 were separated into isomers by chiral HPLC, with their absolute configurations determined by X-ray and ECD calculation. Compounds 3, 4, and 8 display good herbicidal activity against dicotyledon weed Eclipta prostrata, of which 4 and 8 exhibited 88.50% and 100% inhibition rates on the radicle at 200 µg/mL, respectively, a similar effect compared to the positive control penoxsulam.

Substantial Underestimation of Fine-Mode Aerosol Loading from Wildfires and Its Radiative Effects in Current Satellite-Based Retrievals over the United States.

Wildfires generate abundant smoke primarily composed of fine-mode aerosols. However, accurately measuring the fine-mode aerosol optical depth (fAOD) is highly uncertain in most existing satellite-based aerosol products. Deep learning offers promise for inferring fAOD, but little has been done using multiangle satellite data. We developed an innovative angle-dependent deep-learning model (ADLM) that accounts for angular diversity in dual-angle observations. The model captures aerosol properties observed from dual angles in the contiguous United States and explores the potential of Greenhouse gases Observing Satellite-2's (GOSAT-2) measurements to retrieve fAOD at a 460 m spatial resolution. The ADLM demonstrates a strong performance through rigorous validation against ground-based data, revealing small biases. By comparison, the official fAOD product from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Multiangle Imaging Spectroradiometer (MISR) during wildfire events is underestimated by more than 40% over western USA. This leads to significant differences in estimates of aerosol radiative forcing (ARF) from wildfires. The ADLM shows more than 20% stronger ARF than the MODIS, VIIRS, and MISR estimates, highlighting a greater impact of wildfire fAOD on Earth's energy balance.

Deep Learning with Pretrained Framework Unleashes the Power of Satellite-Based Global Fine-Mode Aerosol Retrieval.

Fine-mode aerosol optical depth (fAOD) is a vital proxy for the concentration of anthropogenic aerosols in the atmosphere. Currently, the limited data length and high uncertainty of the satellite-based data diminish the applicability of fAOD for climate research. Here, we propose a novel pretrained deep learning framework that can extract information underlying each satellite pixel and use it to create new latent features that can be employed for improving retrieval accuracy in regions without in situ data. With the proposed model, we developed a new global fAOD (at 0.5 µm) data from 2001 to 2020, resulting in a 10% improvement in the overall correlation coefficient (R) during site-based independent validation and a 15% enhancement in non-AERONET site areas validation. Over the past two decades, there has been a noticeable downward trend in global fAOD (-1.39 × 10-3/year). Compared to the general deep-learning model, our method reduces the global trend's previously overestimated magnitude by 7% per year. China has experienced the most significant decline (-5.07 × 10-3/year), which is 3 times greater than the global trend. Conversely, India has shown a significant increase (7.86 × 10-4/year). This study bridges the gap between sparse in situ observations and abundant satellite measurements, thereby improving predictive models for global patterns of fAOD and other climate factors.

A Vision-Language Model-Based Traffic Sign Detection Method for High-Resolution Drone Images: A Case Study in Guyuan, China.

As a fundamental element of the transportation system, traffic signs are widely used to guide traffic behaviors. In recent years, drones have emerged as an important tool for monitoring the conditions of traffic signs. However, the existing image processing technique is heavily reliant on image annotations. It is time consuming to build a high-quality dataset with diverse training images and human annotations. In this paper, we introduce the utilization of Vision-language Models (VLMs) in the traffic sign detection task. Without the need for discrete image labels, the rapid deployment is fulfilled by the multi-modal learning and large-scale pretrained networks. First, we compile a keyword dictionary to explain traffic signs. The Chinese national standard is used to suggest the shape and color information. Our program conducts Bootstrapping Language-image Pretraining v2 (BLIPv2) to translate representative images into text descriptions. Second, a Contrastive Language-image Pretraining (CLIP) framework is applied to characterize not only drone images but also text descriptions. Our method utilizes the pretrained encoder network to create visual features and word embeddings. Third, the category of each traffic sign is predicted according to the similarity between drone images and keywords. Cosine distance and softmax function are performed to calculate the class probability distribution. To evaluate the performance, we apply the proposed method in a practical application. The drone images captured from Guyuan, China, are employed to record the conditions of traffic signs. Further experiments include two widely used public datasets. The calculation results indicate that our vision-language model-based method has an acceptable prediction accuracy and low training cost.

Combining physical mechanisms and deep learning models for hourly surface ozone retrieval in China.

As surface ozone (O3) gains increasing attention, there is an urgent need for high temporal resolution and accurate O3 monitoring. By taking advantage of the progress in artificial intelligence, deep learning models have been applied to satellite based O3 retrieval. However, the underlying physical mechanisms that influence surface O3 into model construction have rarely been considered. To overcome this issue, we considered the physical mechanisms influencing surface O3 and used them to select relevant variable features for developing a novel deep learning model. We used a wide and deep model architecture to account for linear and non-linear relationships between the variables and surface O3. Using the developed model, we performed hourly inversions of surface O3 retrieval over China from 2017 to 2019 (9:00-17:00, local time). The validation results based on sample-based (site-based) methods yielded an R2 of 0.94 (0.86) and an RMSE of 12.79 (19.13) µg/m3, indicating the accuracy of the models. The average surface O3 concentrations in China in 2017, 2018, and 2019 were 82, 78, and 87 µg/m3, respectively. There was a diurnal pattern in surface O3 in China, with levels rising significantly from 55 µg/m3 at 9:00 a.m. to 96 µg/m3 at 15:00. Between 15:00 and 16:00, the O3 concentration remained stable at 95 µg/m3 and decreased slightly thereafter (16:00-17:00). The results of this study contribute to a deeper understanding of the physical mechanisms of ozone and facilitate further studies on ozone monitoring, thereby enhancing our understanding of the spatiotemporal characteristics of ozone.

Exploring Global Land Coarse-Mode Aerosol Changes from 2001-2021 Using a New Spatiotemporal Coaction Deep-Learning Model.

Coarse-mode aerosol optical depths (cAODs) are critical for understanding the impact of coarse particle sizes, especially dust aerosols, on climate. Currently, the limited data length and high uncertainty of satellite products diminish the applicability of cAOD for climate research. Here, we propose a spatiotemporal coaction deep-learning model (SCAM) for the retrieval of global land cAOD (500 nm) from 2001-2021. In contrast to conventional deep-learning models, the SCAM considers the impacts of spatiotemporal feature interactions and can simultaneously describe linear and nonlinear relationships for retrievals. Based on these unique characteristics, the SCAM considerably improved global daily cAOD accuracies and coverages (R = 0.82, root-mean-square error [RMSE] = 0.04). Compared to official products from the multiangle imaging spectroradiometer (MISR), the moderate resolution imaging spectroradiometer (MODIS), and the polarization and directionality of Earth's reflectances (POLDER) instrument, as well as the physical-deep learning (Phy-DL) derived cAOD, the SCAM cAOD improved the monthly R from 0.44 to 0.88 and more accurately captured over the desert regions. Based on the SCAM cAOD, daily dust cases decreased over the Sahara, Thar Desert, Gobi Desert, and Middle East during 2001-2021 (>3 × 10-3/year). The SCAM-retrieved cAOD can contribute considerably to resolving the climate change uncertainty related to coarse-mode aerosols. Our proposed method is highly valuable for reducing uncertainties regarding coarse aerosols and climate interactions.

A fluorometric assay for rapid enrichment and determination of bacteria by using zirconium-metal organic frameworks as both capture surface and signal amplification tag.

A fluorometric assay was introduced to determine Acinetobacter baumannii (A. baumannii) in blood samples by utilizing Zr-MOFs both as functional coating for magnetic Fe3O4 nanoparticles to provide modification surface (Zr-mMOF) and as fluorescein carrier to produce fluorescence signals (F@UIO-66-NH2). Through strong Zr-O-P bonding, two distinct terminal phosphate-labeled A. baumannii and lipopolysaccharide (LPS) specific aptamers were attached onto Zr-MOFs to fabricate the magnetic core-shell capture probe (denoted as Zr-mMOF-p-Ab-Apt) and signal probe (denoted as F@UIO-66-NH2-p-LPS-Apt), respectively. After successive incubation with A. baumannii in blood samples and magnetic separation, the sandwich-type composite of capture probe/A. baumannii cells/signal probe was treated with high concentration of anionic phosphate ions to destroy the nano-structure of UIO-66-NH2 in the signal probe and fast release of fluorescein to produce amplified fluorescence signals. Due to the high aptamer modification efficiency of Zr-mMOF-p-Ab-Apt (up to 93%) and its strong affinity to A. baumannii, the enrichment efficiency of this capture probe has reached to 96.7%. Further, due to the high fluorescein loading efficiency of UIO-66-NH2 and our novel amplification strategy to destroy F@UIO-66-NH2-p-LPS-Apt to release and amplify fluorescein signals at 512 nm in the presence of high concentration of anionic phosphate ions, the sensitivity of this method has reached 10 cfu mL-1. This method allows enrichment and determination of A. baumannii within ~2.5 h. The limit of detection of A. baumannii in blood samples is 10 cfu mL-1 with a linear range of 101-105 cfu mL-1. This indicates the potential of this assay for diagnosis of bloodstream infection in early stage. Graphical abstractSchematic representation of sandwich-type fluorometric assay for Acinetobacter baumannii in blood samples with the capture probe (Zr-mMOF-p-Ab-Apt) and signal probe (F@UIO-66-NH2-p-LPS-Apt). The limit of detection is down to 10 cfu mL-1 with a linear range of 101-105 cfu mL-1.

Chromatin remodeling: demethylating H3K4me3 of type I IFNs gene by Rbp2 through interacting with Piasy for transcriptional attenuation.

Type I IFNs (IFNIs) are involved in the course of antiviral and antimicrobial activities; however, robust inductions of these can lead to host immunopathology. We have reported that the Pias (protein inhibitor of activated signal transducer and activator of transcription) family member, Piasy, possesses the ability to suppress IFNI transcriptions in mouse embryonic fibroblasts (MEFs), yet the specific molecular mechanism by which it acts remains elusive. Here, we identify that the H3K4me3 levels, one activation mark of genes, in MEFs that were stimulated by poly(I:C) were impaired by Piasy in the IFN-ß gene. Piasy bound to the promoter region of the IFN-ß gene in MEFs. Meanwhile, retinoblastoma binding protein 2 (Rbp2) was proven to be the only known and novel H3K4me3 demethylase that interacted with Piasy. Overexpression of Rbp2, but not its enzymatically inactive mutant Rbp2H483G/E485Q, retarded the transcription activities of IFNI, whereas small interfering RNA-mediated or short hairpin RNA-mediated knockdown of Rbp2 enhanced IFNI promoter responses. Above all, coexpression of Piasy and Rbp2 led to statistically less IFNI induction than overexpression of either Piasy or Rbp2 alone. Mechanistically, Piasy bound to the Jmjc domain (451-503 aa) of Rbp2 via its PINIT domain (101-218 aa), which is consistent with the domain required for their attenuation of transcription and H3K4me3 levels of IFNI genes. Our study demonstrates that Piasy may prevent exaggerated transcription of IFNI by Rbp2-mediated demethylation of H3K4me3 of IFNI, avoiding excessive immune responses.-Yu, X., Chen, H., Zuo, C., Jin, X., Yin, Y., Wang, H., Jin, M., Ozato, K., Xu, S. Chromatin remodeling: demethylating H3K4me3 of type I IFNs gene by Rbp2 through interacting with Piasy for transcriptional attenuation.

The inactivation of the non-enveloped enterovirus 71 (EV71) by a novel disinfectant gel formulation for topical use.

BACKGROUND: Hand-foot-mouth disease may cause severe central nervous system complications and even death, that is induced mainly by enterovirus 71 (EV71), which is a non-enveloped virus. Inactivation of the EV71 on hands could effectively inhibit the transmission. However, the inactivations of the EV71 by conventional disinfectants including the alcohols are poor, due to the high stability of the EV71. A novel pyridyl imidazolidinone compound (TJAB1099) was designed to specifically inhibit EV71 replication in vitro. It may potentially be developed as formulations applied on hands for EV71 transmission control. METHODS: The stress stability of TJAB1099 was first evaluated after storing in high temperature (60 °C, RH 10%), high humidity (25 °C, RH90%), and the high-intensity photolysis (4500 Lx ± 500 Lx) for 15 days, respectively. A wash-free antimicrobial gel containing the TJAB1099 was developed using the copolymer carrier. The antiviral activity, the acute oral toxicity, and the local irritation of the antimicrobial gel were evaluated accordingly. RESULTS: The results indicated that the TJAB1099 was stable during the storage in high temperature and humidity. However, a significant change (p < .0001) was detected when TJAB1099 stored in the high-intensity photolysis. The antimicrobial gel containing 1 µM TJAB1099 could inhibit EV71 significantly higher than the ethanol (75%) (p < .0001) and commercialized disinfectant products (p < .0001). The results of acute oral toxicity and the local irritation suggest that the TJAB1099 containing antimicrobial gel was not causing skin irritations and acute oral toxicity symptoms. CONCLUSIONS: The results suggest that the antimicrobial gel containing TJAB1099 was safe and could effectively inhibit EV71 transmission in vitro.

PCR-sequencing is a complementary method to amplification refractory mutation system for EGFR gene mutation analysis in FFPE samples.

Amplification Refractory Mutation System (ARMS) is the most popular technology for EGFR gene mutation analysis in China. Cutoff Ct or ΔCt values were used to differentiate low mutation abundance cases from no mutation cases. In this study, all of 359 NSCLC samples were tested by ARMS. Seventeen samples with larger Ct or ΔCt than cutoff values were retested by PCR-sequencing. TKI treatment responses were monitored on the cases with ARMS negative and PCR-sequencing positive results. One exon 18 G719X case, 67 exon 19 deletion cases, 2 exon 20 insertion cases, 1 exon 20 T790M case, 60 exon 21 L858R cases, 5 exon 21 L861Q cases and 201 wild type cases were identified by ARMS. Another 22 cases were evaluated as wild type but had later amplification fluorescent curves. Seventeen out of these 22 cases were retested by PCR-sequencing. It turns out that 3 out of 3 cases with exon 19 deletion later amplifications, 2 out of 2 cases with L858R later amplifications and 4 out of 12 cases with T790M later amplifications were identified as mutation positive. Two cases with exon 19 deletion and L858R respectively were treated by TKI and got responses. Our study indicated that PCR-sequencing might be a complementary way to confirm ARMS results with later amplifications.

Coverage of the left subclavian artery without revascularization during thoracic endovascular repair is feasible: a prospective study.

BACKGROUND: To effectively isolate thoracic aortic lesions in thoracic endovascular aortic repair (TEVAR), an adequate proximal landing zone length is required. The left subclavian artery (LSCA) and other branches of the aortic arch commonly impose limitations on proximal landing zone length, restricting the use of TEVAR. In this study, we investigated the outcomes of LSCA coverage during TEVAR. METHODS: Between March 2009 and February 2010, we recruited patients with thoracic dissection, aneurysm or trauma from a single center for TEVAR. We categorized patients into 3 groups: full coverage, partial coverage, or noncoverage of the LSCA. We measured pre- and postoperative blood pressures and evaluated complications during follow-up. RESULTS: We recruited 111 patients for our study: 55 (50%) and 25 (23%) patients had full and partial LSCA coverage, respectively. The upper left arm blood pressures before and after the operations were significantly different between the full-coverage group and the other groups (P < 0.0001). Follow-up occurred between 6 and 20 months, and the mean follow-up time was 10.4 months. Thirteen patients (24%) in the full-coverage group and 2 patients (8%) in the partial-coverage group suffered from simple vertebrobasilar ischemia (VBI). Eleven of the patients with VBI (20%) in the full-coverage group and 2 (8%) patients with VBI in the partial-coverage group had left subclavian steal syndrome at follow-up. No paraplegia or stroke was observed. CONCLUSIONS: Intentional coverage of the LSCA to obtain an adequate proximal landing zone for TEVAR can be a treatment option for thoracic aortic lesions, although some patients experienced mil complications.

Pathways linking watershed development and riparian quality to stream water quality and fish communities: Insights from 233 subbasins of the Great Lakes region.

Anthropogenic stressors such as urban development, agricultural runoff, and riparian zone degradation impair stream water quality and biodiversity. However, the intricate pathways that connect these stressors at watershed and riparian scales to stream ecosystems-and their interplay with climate and hydrology-remain understudied. In this study, we used Partial Least Squares (PLS) path modeling to examine these pathways and their collective impacts on stream water quality and fish community structures across 233 watersheds in the Great Lakes region. Our study suggests that moderate levels of watershed development enhance overall fish richness, potentially due to increased water temperature and nutrient availability, but reduces both the percentages and richness of cold water and intolerant taxa. Riparian quality exerts indirect effects on water quality with climate and stream order serving as key mediators. Complementing our SEM analysis, we also used Multiple Linear Regression (MLR) models and identified a significant positive relationship between the proportion of clay and agricultural land with TN concentrations. However, TP concentrations are influenced by a more complex set of interactions involving developed areas, soil, and slope. These findings emphasize the necessity of adopting integrated management strategies to preserve the health and integrity of freshwater ecosystems in the Great Lakes region. These strategies should integrate watershed and riparian protection measures while also taking into account the effects of climate change and specific local conditions.

Nrf-2 as a novel target in radiation induced lung injury.

Radiation-induced lung injury (RILI) is a common and fatal complication of chest radiotherapy. The underlying mechanisms include radiation-induced oxidative stress caused by damage to the deoxyribonucleic acid (DNA) and production of reactive oxygen species (ROS), resulting in apoptosis of lung and endothelial cells and recruitment of inflammatory cells and myofibroblasts expressing NADPH oxidase to the site of injury, which in turn contribute to oxidative stress and cytokine production. Nuclear factor erythroid 2-related factor 2 (Nrf-2) is a vital transcription factor that regulates oxidative stress and inhibits inflammation. Studies have shown that Nrf-2 protects against radiation-induced lung inflammation and fibrosis. This review discusses the protective role of Nrf-2 in RILI and its possible mechanisms.

Unveiling global land fine- and coarse-mode aerosol dynamics from 2005 to 2020 using enhanced satellite-based monthly inversion data.

Accurate fine-mode and coarse-mode aerosol knowledge is crucial for understanding their impacts on the climate and Earth's ecosystems. However, current satellite-based Fine-Mode Aerosol Optical Depth (FAOD) and Coarse-Mode Aerosol Optical Depth (CAOD) methods have drawbacks including inaccuracies, low spatial coverage, and limited temporal duration. To overcome these issues, we developed new global-scale FAOD and CAOD from 2005 to 2020 using a novel deep learning model capable of the synergistic retrieval of two aerosol sizes. After validation with the aerosol robotic network (AERONET) and sky radiometer network (SKYNET), the new monthly FAOD and CAOD showed significant improvements in accuracy and spatial coverage. From 2005 to 2020, the new data showed that China had the greatest decrease in FAOD and CAOD. In contrast, India and South Latin America had a significant increase in FAOD versus North Africa in CAOD. FAOD in the regions of Argentina, Paraguay, and Uruguay in South America have shown an upward trend. The results reveal that FAOD and CAOD display distinct patterns of change in the same regions, particularly on the west coast of the United States where FAOD is increasing, while CAOD is decreasing. Aside from the year 2020 due to the global COVID-19 pandemic, the analysis showed that although China has seen at least an +85% increase in energy consumption and urban expansion in 2019 compared to 2005 due to the needs of development and construction, the implementation of China's air pollution control policies has led to a significant decrease in FAOD (-46%) and CAOD (-65%) after 2013. This research enriches our comprehension of global fine and coarse aerosol patterns, additional investigations are needed to determine the potential global implications of these changes.

Genome Mining and Heterologous Expression Guided the Discovery of Antimicrobial Naphthocyclinones from Streptomyces eurocidicus CGMCC 4.1086.

A type II polyketide synthase biosynthetic gene cluster (nap) was identified in Streptomyces eurocidicus CGMCC 4.1086 via genome mining. The heterologous expression of the cryptic nap gene cluster in Streptomyces albus J1074 generated dimerized aromatic polyketide naphthocyclinones (1-3), whose structures were determined via extensive analysis using nuclear magnetic resonance and high-resolution electrospray ionization mass spectroscopy. The biological pathway of naphthocyclinone synthesis was revealed via in vivo gene deletion, in vitro biochemical reactions, and comparative genomics. Remarkably, 3 played a crucial role in inhibiting Phytophthora capsici and Phytophthora sojae, with EC50 values of 6.1 and 20.2 µg/mL, respectively. Furthermore, 3 exhibited a potent protective effect against P. capsici and P. sojae in greenhouse tests.

Cooperative simultaneous inversion of satellite-based real-time PM2.5 and ozone levels using an improved deep learning model with attention mechanism.

Ground-level fine particulate matter (PM2.5) and ozone (O3) are air pollutants that can pose severe health risks. Surface PM2.5 and O3 concentrations can be monitored from satellites, but most retrieval methods retrieve PM2.5 or O3 separately and disregard the shared information between the two air pollutants, for example due to common emission sources. Using surface observations across China spanning 2014-2021, we found a strong relationship between PM2.5 and O3 with distinct spatiotemporal characteristics. Thus, in this study, we propose a new deep learning model called the Simultaneous Ozone and PM2.5 inversion deep neural Network (SOPiNet), which allows for daily real-time monitoring and full coverage of PM2.5 and O3 simultaneously at a spatial resolution of 5 km. SOPiNet employs the multi-head attention mechanism to better capture the temporal variations in PM2.5 and O3 based on previous days' conditions. Applying SOPiNet to MODIS data over China in 2022, using 2019-2021 to construct the network, we found that simultaneous retrievals of PM2.5 and O3 improved the performance compared with retrieving them independently: the temporal R2 increased from 0.66 to 0.72 for PM2.5, and from 0.79 to 0.82 for O3. The results suggest that near-real time satellite-based air quality monitoring can be improved by simultaneous retrieval of different but related pollutants. The codes of SOPiNet and its user guide are freely available online at https://github.com/RegiusQuant/ESIDLM.

Universal probe-based SNP genotyping with visual readout: a robust and versatile method.

Detection of single nucleotide polymorphisms (SNPs) is critical for personalized clinical diagnosis, treatment, and medication. Current clinical detection methods suffer from primer dimerization and require the redesigning of reaction systems for different targets, resulting in a time-consuming and laborious process. Here, we present a robust and versatile method for SNP typing by using tailed primers and universal small molecule probes in combination with a visualized lateral flow assay (LFA). This approach enables not only rapid typing of different targets, but also eliminates the interference of primer dimers and enhances the accuracy and reliability of the results. Our proposed universal assay has been successfully applied to the typing of four SNP loci of clinical samples to verify the accuracy and universality, and the results are consistent with those obtained by Sanger sequencing. Therefore, our study establishes a new universal "typing formula" using nucleic acid tags and small molecule probes that provides a powerful genotyping platform for genetic analysis and molecular diagnostics.

[Clinical Characteristics of Children with Hemophagocytic Syndrome with Different EB Virus DNA Loads].

OBJECTIVE: To analyze the clinical characteristics of hemophagocytic syndrome (HLH) children with different EB virus (EBV) DNA loads, and to explore the relationship between differential indicators and prognosis. METHODS: Clinical data of 73 children with HLH treated in our hospital from January 2015 to April 2022 were collected. According to EBV DNA loads, the children were divided into negative group (≤5×102 copies/ml), low load group (>5×102-<5×105 copies/ml) and high load group (≥5×105copies/ml）. The clinical symptoms and laboratory indexes of the three groups were compared, and the ROC curve was used to determine the best cut-off value of the different indexes. Cox regression model was used to analyze the independent risk factors affecting the prognosis of children, and to analyze the survival of children in each group. RESULTS: The proportion of female children, the swelling rate of liver and spleen lymph nodes and the involvement rate of blood, liver, circulation and central nervous system in the high load group were higher than those in the negative group. The incidence of disseminated intravascular coagulation(DIC) and central nervous system(CNS) involvement in the high load group were higher than those in the low load group. The liver swelling rate and circulatory system involvement rate in the low load group were higher than those in the negative group(P<0.05). PLT counts in the high load group were significantly lower than those in the negative group, and the levels of GGT, TBIL, CK-MB, LDH, TG, SF, and organ involvement were significantly higher than those in the negative group. The levels of CK, LDH, SF and the number of organ involvement in the high load group were significantly higher than those in the low load group. The levels of GGT and TBIL in low load group were significantly higher than those in negative group. In terms of treatment, the proportion of blood purification therapy in the high and low load group was significantly higher than that in the negative group(P<0.01). ROC curve analysis showed that the best cut-off values of PLT, LDH, TG and SF were 49.5, 1139, 3.12 and 1812, respectively. The appellate laboratory indicators were dichotomized according to the cut-off value, and the differential clinical symptoms were included in the Cox regression model. Univariate analysis showed that LDH>1139 U/L, SF>1812 µg/L, dysfunction of central nervous system, number of organ damage, DIC and no blood purification therapy were the risk factors affecting the prognosis of children (P<0.05); Multivariate analysis shows that PLT≤49.5×109/L and dysfunction of central nervous system were risk factors affecting the prognosis of children (P<0.05). Survival analysis showed that there was no significant difference in the survival rate among the three groups. CONCLUSION: The incidence of adverse prognostic factors in children with HLH in the EBV-DNA high load group is higher, and there is no significant difference in the survival rate of the three groups after blood purification therapy. Therefore, early identification and application of blood purification therapy is of great significance for children with HLH in the high load group.

Nonparametric inference for median costs with censored data.

Increasingly, estimations of health care costs are used to evaluate competing treatments or to assess the expected expenditures associated with certain diseases. In health policy and economics, the primary focus of these estimations has been on the mean cost, because the total cost can be derived directly from the mean cost, and because information about total resources utilized is highly relevant for policymakers. Yet, the median cost also could be important, both as an intuitive measure of central tendency in cost distribution and as a subject of interest to payers and consumers. In many prospective studies, cost data collection is sometimes incomplete for some subjects due to right censoring, which typically is caused by loss to follow-up or by limited study duration. Censoring poses a unique challenge for cost data analysis because of so-called induced informative censoring, in that traditional methods suited for survival data generally are invalid in censored cost estimation. In this article, we propose methods for estimating the median cost and its confidence interval (CI) when data are subject to right censoring. We also consider the estimation of the ratio and difference of two median costs and their CIs. These methods can be extended to the estimation of other quantiles and other informatively censored data. We conduct simulation and real data analysis in order to examine the performance of the proposed methods.

Catalytic decomposition of hydroxylamine nitrate and hydrazine nitrate using Ru/ZSM-5 catalyst under mild reaction conditions.

Hydroxylamine nitrate and hydrazine nitrate are dangerous explosives and toxic chemicals. Catalytic decomposition is an efficient way for disposal of these chemicals. In the current work, a Ru/ZSM-5 catalyst has been fabricated and evaluated for the decomposition of hydroxylamine nitrate and hydrazine nitrate in 1.0 mol L-1 HNO3. The hydroxylamine nitrate and hydrazine nitrate can be thoroughly decomposed under 80 °C. And the Ru/ZSM-5 catalyst can be separated from the reaction mixture and reused at least 130 times with stable catalytic performance. Easy operation, less solid waste generation, and a simple catalytic device make the strategy reported here practical, environmentally friendly, and economically attractive.