Quantitative assessment, molecular docking and novel metabolic pathways reveal the interaction mechanisms between norfloxacin biodegradation and environmental implications.

Norfloxacin (NOR) is widely used in medicine and animal husbandry, but its accumulation in the environment poses a substantial threat to ecological and human health. Traditional physical, chemical, and rudimentary biological methods often fall short in mitigating NOR contamination, necessitating innovative biological approaches. This study proposes an engineered bacterial consortium found in marine sediment as a strategy to enhance NOR degradation through inter-strain co-metabolism of diverse substrates. Strategically supplementing the engineered bacterial consortium with exogenous carbon sources and metal ions boosted the activity of key degradation enzymes like laccase, manganese peroxidase, and dehydrogenase. Iron and amino acids demonstrated synergistic effects, resulting in a remarkable 70.8% reduction in NOR levels. The innovative application of molecular docking elucidated enzyme interactions with NOR, uncovering potential biodegradation mechanisms. Quantitative assessment reinforced the efficiency of NOR degradation within the engineered bacterial consortium. Four metabolic routes are herein proposed: acetylation, defluorination, ring scission, and hydroxylation. Notably, this study discloses distinctive, co-operative metabolic pathways for NOR degradation within the specific microbial community. These findings provide new ways of understanding and investigating the bioremediation potential of NOR contaminants, which may lead to the development of more sustainable and effective environmental management strategies.

A decision tree model to help treatment decision-making for severe spontaneous intracerebral hemorrhage.

BACKGROUND: Surgical treatment demonstrated a reduction in mortality among patients suffering from severe spontaneous intracerebral hemorrhage (SSICH). However, which SSICH patients could benefit from surgical treatment was unclear. This study aimed to establish and validate a decision tree (DT) model to help determine which SSICH patients could benefit from surgical treatment. MATERIALS AND METHODS: SSICH patients from a prospective, multicenter cohort study were analyzed retrospectively. The primary outcome was the incidence of neurological poor outcome (modified Rankin scale as 4-6) on the 180th day posthemorrhage. Then, surgically-treated SSICH patients were set as the derivation cohort (from a referring hospital) and validation cohort (from multiple hospitals). A DT model to evaluate the risk of 180-day poor outcome was developed within the derivation cohort and validated within the validation cohort. The performance of clinicians in identifying patients with poor outcome before and after the help of the DT model was compared using the area under curve (AUC). RESULTS: One thousand two hundred sixty SSICH patients were included in this study (middle age as 56, and 984 male patients). Surgically-treated patients had a lower incidence of 180-day poor outcome compared to conservatively-treated patients (147/794 vs. 128/466, P <0.001). Based on 794 surgically-treated patients, multivariate logistic analysis revealed the ischemic cerebro-cardiovascular disease history, renal dysfunction, dual antiplatelet therapy, hematoma volume, and Glasgow coma score at admission as poor outcome factors. The DT model, incorporating these above factors, was highly predictive of 180-day poor outcome within the derivation cohort (AUC, 0.94) and validation cohort (AUC, 0.92). Within 794 surgically-treated patients, the DT improved junior clinicians' performance to identify patients at risk for poor outcomes (AUC from 0.81 to 0.89, P <0.001). CONCLUSIONS: This study provided a DT model for predicting the poor outcome of SSICH patients postsurgically, which may serve as a useful tool assisting clinicians in treatment decision-making for SSICH.

A novel integrated optimization model for carbon emission prediction: A case study on the group of 20.

Carbon emission is a central factor in the study of the greenhouse effect and a crucial consideration in environmental policy making. Therefore, it is essential to establish carbon emission prediction models to provide scientific guidance for leaders in implementing effective carbon reduction policies. However, existing research lacks comprehensive roadmaps that integrate both time series prediction and analysis of influencing factors. This study combines the environmental Kuznets curve (EKC) theory to classify and qualitatively analyzes research subjects based on national development patterns and levels. Considering the autocorrelated characteristics of carbon emissions and their correlation with other influencing factors, we propose an integrated carbon emission prediction model named SSA-FAGM-SVR. This model optimizes the fractional accumulation grey model (FAGM) and support vector regression (SVR) using the sparrow search algorithm (SSA), considering both time series and influencing factors. The model is subsequently applied to predict the carbon emissions of the G20 for the next 10 years. The results demonstrate that this model significantly improves prediction accuracy compared to other mainstream prediction algorithms, exhibiting strong adaptability and high accuracy.

An Efficient Privacy-Preserving Public Auditing Protocol for Cloud-Based Medical Storage System.

The booming Internet of Things makes smart healthcare a reality, while cloud-based medical storage systems solve the problems of large-scale storage and real-time access of medical data. The integrity of medical data outsourced in cloud-based medical storage systems has become crucial since only complete data can make a correct diagnosis, and public auditing protocol is a key technique to solve this problem. To guarantee the integrity of medical data and reduce the burden of the data owner, we propose an efficient privacy-preserving public auditing protocol for the cloud-based medical storage systems, which supports the functions of batch auditing and dynamic update of data. Detailed security analysis shows that our protocol is secure under the defined security model. In addition, we have conducted extensive performance evaluations, and the results indicate that our protocol not only remarkably reduces the computational costs of both the data owner and the third-party auditor (TPA), but also significantly improves the communication efficiency between the TPA and the cloud server. Specifically, compared with other related work, the computational cost of the TPA in our protocol is negligible and the data owner saves more than 2/3 of computational cost. In addition, as the number of challenged blocks increases, our protocol saves nearly 90% of communication overhead between the TPA and the cloud server.

Resistance to pydiflumetofen in Botrytis cinerea: risk assessment and detection of point mutations in sdh genes that confer resistance.

BACKGROUND: Gray mold caused by Botrytis cinerea Pers. is one of the most significant airborne diseases. It can infest a wide range of crops, causing significant losses in yield and quality worldwide. Pydiflumetofen, a new generation succinate dehydrogenase inhibitor (SDHI), is currently being registered in China to control gray mold in a variety of crops. The baseline sensitivity, resistance risk, and resistance mechanism of Botrytis cinerea to pydiflumetofen were assessed in this study. RESULTS: A total of 138 strains of B. cinerea from 10 different regions were tested for their sensitivity to pydiflumetofen, and the mean EC50 value was 0.0056 µg mL-1 . Eight mutants were obtained by fungicide adaption from five sensitive parental isolates, and the resistance factor (RF) ranged from 51 to 135. The mutants exhibited strong adaptive traits in conidial production, conidial germination, and pathogenicity. Positive cross-resistance was only observed between other SDHIs (i.e. boscalid, fluopyram, and isopyrazam). Two different types of pydiflumetofen-resistant mutants were identified: point mutation P225L in sdhB and double mutation G85A and I93V in sdhC. The in vivo control efficacy of pydiflumetofen on the resistant mutants carrying P225L in sdhB as well as G85A and I93V in sdhC was significantly decreased to 52.62% and 32.27%, respectively. CONCLUSION: The fitness was significantly higher for all pydiflumetofen-resistant mutants than the corresponding parental. Two types of point mutations, sdhB-P225L and sdhC-G85A and I93V, might confer resistance to pydiflumetofen in B. cinerea. A precautionary resistance management strategy should be implemented. © 2021 Society of Chemical Industry.

Functional assessment of cryopreserved clinical grade hESC-RPE cells as a qualified cell source for stem cell therapy of retinal degenerative diseases.

The biosafety and efficiency of transplanting retinal pigment epithelial (RPE) cells derived from both human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) have been evaluated in phase I and phase II clinical trials. For further large-scale application, cryopreserved RPE cells must be used; thus, it is highly important to investigate the influence of cryopreservation and thawing on the biological characteristics of hESC-RPE cells and their post-transplantation vision-restoring function. Here, via immunofluorescence, qPCR, transmission electron microscopy, transepithelial electrical resistance, and enzyme-linked immunosorbent assays (ELISAs), we showed that cryopreserved hESC-RPE cells retained the specific gene expression profile, morphology, ultrastructure, and maturity-related functions of induced RPE cells. Additionally, cryopreserved hESC-RPE cells exhibited a polarized monolayer, tight junction, and gap junction structure and an in vitro nanoparticle phagocytosis capability similar to those of induced hESC-RPE cells. However, the level of pigment epithelium-derived factor (PEDF) secretion was significantly decreased in cryopreserved hESC-RPE cells. Royal College of Surgeons rats with cryopreserved hESC-RPE cells engrafted into the subretinal space exhibited a significant decrease in the b-wave amplitude compared with rats engrafted with induced hESC-RPE cells at 4 weeks post transplantation. However, the difference disappeared at 8 weeks and 12 weeks post operation. No significant difference in the outer nuclear layer (ONL) thickness was observed between the two groups. Our data showed that even after cryopreservation and thawing, cryopreserved hESC-RPE cells are still qualified as a donor cell source for cell-based therapy of retinal degenerative diseases.

Monitoring and detection of leprosy patients in Southwest China: A retrospective study, 2010-2014.

More than 100 counties, mainly in southwest China, report incidence rates of leprosy >1/100,000. The current study analysed the epidemiology of leprosy in southwest China to improve our understanding of the transmission pattern and improve control programs. 207 counties were selected in southwest China. Leprosy patients and their household contacts were recruited. The data from the medical interview and the serological antileprosy antibody of the leprosy patients were analysed. A total of 2,353 new cases of leprosy were interviewed. The distribution of leprosy patients was partly associated with local natural and economic conditions, especially several pocket areas. A total of 53 from 6643 household contacts developed leprosy, and the incidence rate of leprosy in the household contacts was 364/100,000 person-years. We found that NDO-BSA attained higher positive rates than MMP-II and LID-1 regardless of clinical types, disability and infection time in leprosy patients. By means of combination of antigens, 88.4% patients of multibacillary leprosy were detected, in contrast to 59.9% in paucibacillary leprosy. Household contacts should be given close attention for the early diagnosis, disruption of disease transmission and precise control. Applications of serology for multi-antigens were recommended for effective coverage and monitoring in leprosy control.

Does economic development improve urban greening? Evidence from 289 cities in China using spatial regression models.

Significant differences in urban greening have occurred in Chinese cities, accompanied by China's rapid urbanization. However, there are relatively few studies on the spatial differentiation of urban greening in China at the city level. In addition, there is no unanimous conclusion on the main factors influencing the spatial differentiation of urban greening. Based on 2014 emission inventory data from 289 cities, the spatial differentiation pattern and spatial correlation characteristics of the urban green space ratio, urban green coverage rate, and public green area per capita were calculated and analyzed using global and local Moran's I. We then used ordinary least squares, spatial error model, spatial autoregression, and geographically weighted regression to quantify the impact and spatial variations of China's economy on urban greening. The results showed (1) a significant spatial dependence and heterogeneity existed in urban greening values, and the patterns showed influences of both the stage of economic development and spatial agglomeration; (2) regression models revealed per capita GDP had a positive effect on the urban green space ratio and public green area per capita while the urbanization rate, secondary industry, urban land, and population density had opposite effects on these two greening indexes; and (3) geographically weighted regression revealed per capita GDP had a greater influence on urban greening in the northwestern region than in the southeastern region. The study could constitute a valuable reference for mid-to-long-term green space planning policy in diverse parts of China and could further assist in coordinating the development of urban greening and economic growth.

[Long-term changes of land use/cover in the Three Gorges Reservoir Area of the Yangtze River, China.] / 长江三峡库区土地利用/覆盖的长期变化.

Understanding the temporal and spatial dynamics of land use/cover (LUC) can contri-bute to reveal the impacts of climate change and human activities on ecosystems and thus be an important prerequisite for ecosystem management. As an ecologically vulnerable area in China, the Three Gorges Reservoir Area (TGRA) of the Yangtze River presented significant complexity in the response to environmental changes. However, there is a general lack of understanding in the underlying mechanism. In this study, we interpreted the time series remote sensing images derived from the Landsat sensors to map the LUC of the TGRA, and aimed to analyze the long-term changes in the distribution and structure of LUC and elucidate the evolution process of LUC, which could provide a scientific basis to understand the complexity of ecosystem changes and regional ecosystem management in ecologically fragile regions. The results showed that the TGRA presented the significant changes in spatial heterogeneity of LUC structure from 1990 to 2015. Meanwhile, the landscape changed from farmland to woodland (forest and shrubland). Farmland decreased from 66.2% to 40.4%, but woodland increased from 31.3% to 53.5%, buildings and water area increased gradually. Forest gradually spread to the middle of the TGRA, while the buildings presented a scattered expansion. In the altitude zone of 500-1000 m and slope zone of 15°-25°, woodland increased noticeably, and the coniferous forest, mixed forest and shrubland had a higher growth rate. In the study period, due to the urban construction and the various ecological restoration projects in the TGRA, the LUC structure varied with the dam's impoundment and was characterized by the ecosystem restoration. Ecological restoration projects were helpful to reduce the negative impacts of urban construction and economic development on the environment.

Cadmium Accumulation Characteristics in Turnip Landraces from China and Assessment of Their Phytoremediation Potential for Contaminated Soils.

Heavy metal (HM) pollution is a global environmental problem that threatens ecosystem and human health. Cadmium (Cd) pollution is the most prominent HM pollution type because of its high toxicity, strong migration, and the large polluted area globally. Phytoremediation of contaminated soil is frequently practiced because of its cost-effectiveness and operability and because it has no associated secondary pollution. High-accumulation plants, including those identified as hyperaccumulators, play an important role in phytoremediation. Therefore, screening of plants to identify hyperaccumulators is important for continued phytoremediation. In the present study, we investigated the Cd tolerance and accumulation capabilities of 18 turnip landraces from China under a soil experiment with known Cd level. The results indicated that turnip has a high capacity for Cd accumulation. Furthermore, significant differences in Cd tolerance and accumulation characteristics were found among different landraces when they grew at 50 mg kg-1 (dry weight) Cd concentration. Among the studied landraces, five turnip landraces met the requirements of Cd hyperaccumulators and three landraces were identified as potential candidates. However, the total Cd content accumulated by individual plant of different turnip landraces was dependent on both the Cd accumulation capacity and plant biomass. Compared with some reported Cd hyperaccumulators, turnip not only shows a high Cd-accumulation capacity but also has rapid growth and a wide distribution area. These advantages indicate that turnip may have considerable potential for phytoremediation of Cd-contaminated soil. Furthermore, the study also indicates that it is not advisable to consume turnip cultivated in an environment that exceeds safe Cd levels.

Quality assessment of Fructus xanthii based on fingerprinting using high-performance liquid chromatography.

Because almost every traditional Chinese medicine (TCM) is a multicomponent system, QC of TCMs always involves various difficulties. As a current popular quality assessment approach, focusing on qualitative and quantitative analysis of certain compounds contained in herbal medicine has been widely used for the sake of expediency rather than being a practical and realistic way. However, this method does not take the existence of other constituents into account. Comparatively, the chromatographic fingerprint of the components is a more suitable approach to holistically assess the quality of herbal drugs. Fructus xanthii is a well-known herbal drug listed in all editions of the Chinese Pharmacopoeia. However, there is no quality evaluation method given in its monograph, even for the above-mentioned expediency. This paper reports an HPLC fingerprinting method for quality evaluation of F. xanthii. The HPLC profiles of 27 batches of commercial samples were further analyzed using chemometric methods, including similarity evaluation and principal component analysis. As a result, the established HPLC fingerprint contained 23 characteristic peaks; therein, 13 peaks were unambiguously assigned by comparing their retention times and UV spectra with those of reference compounds, and five peaks were tentatively identified on the basis of their MS/MS fragmentation patterns and UV spectra. Moreover, it could be clearly observed that caffeoylquinic acid and its analogs predominate in F. xanthii. Except for three samples identified as outliers, 24 other commercial samples displayed similar HPLC profiles, indicating that the quality of the herbs from different markets is stable and consistent.

[Nonpoint source pollution model, AnnAGNPS, assessment for a mixed forested watershed in Three Gorges Reservoir area].

Watershed models provide a cost-effective and efficient means of estimating the pollutant loadings entering surface waters, especially when combined with traditional water quality sampling and analyses. But there have often been questions about the accuracy or certainty of models and their predictions. The main goal of this study was to evaluate the performance of AnnAGNPS (Annualized AGricultural NonPoint Source)Pollution Model, in simulating runoff, sediment loading and nutrient loadings under Three Gorges Reservoir area. Most of model input parameters were sourced from Zigui Forest Ecology Station in Three Gorges Reservoir area, State Forestry Administration. Data year 2003 was used for calibration while data year 2004 was used for validation of the model. The whole evaluation consisted of determining the coefficient of determination (R2), Nash-Sutcliffe coefficient of efficiency (E), and the percentage volume error (VE). Results showed that the model predicted the daily runoff volume within the range of acceptable accuracy. The runoff on a daily basis was underpredicted by 5.0% with R2 of 0.93 (p < 0.05) during calibration and underpredicted by 6.7% with R2 of 0.90 (p < 0.05) during validation. But sediment loading was able to produce a moderate result. The model underpredicted the event-based sediment loading by 15.1% with R2 of 0.63 (p < 0.05) during calibration and 26.7% with R2 of 0.59 (p < 0.05) during validation. For the events of small magnitude, the model generally overpredicted sediment loading, while the opposite was true for larger events. Nitrogen loading prediction was slightly better with R2 = 0.68 (p < 0.05), and phosphorus loading performance was slightly poor with R2 = 0.65 (p < 0.05). In general, the model performs well in simulating runoff compare to sediment loading and nutrient loadings, and as a watershed management tools it can be used for Three Gorges Reservoir area conditions that with mixed types of land uses and steep slopes.