Spatial effect of carbon neutrality target on high-quality economic development-Channel analysis based on total factor productivity.

This study utilizes panel data from 30 provinces in mainland China from 2011 to 2020 to investigate the impact of carbon-neutral development on economic high-quality development by constructing an economic high-quality development index and a carbon-neutral development index. Firstly, the study examines the effects of carbon-neutral development on economic high-quality development using baseline regression and spatial Durbin regression. The results indicate that carbon-neutral development has a positive direct effect on economic high-quality growth, but there are negative spatial spillover effects. Secondly, this study employs total factor productivity (TFP) as an intermediate variable in the mediation model regression. The findings demonstrate that carbon-neutral development significantly improves TFP, and the significant improvement in TFP promotes high-quality economic growth. Lastly, the study conducts regional heterogeneity analysis and finds a significant promoting effect of carbon-neutral development on economic high-quality development in the eastern and central regions of China, while it is not significant in the western region. Therefore, it is recommended that China, in the process of achieving carbon-neutral growth, consider the geographical connections between different regions to prevent negative spillover effects. Additionally, regional heterogeneity should be taken into account when formulating relevant policies to promote economic high-quality development.

Can green finance and environmental regulations promote carbon emission reduction? Evidence from China.

Carbon reduction has become a major challenge for China's economy in its transition toward sustainability. The government has been monitoring the behavior of enterprises through regulations to protect the environment, while green finance has rapidly developed in recent years as a new tool to reduce carbon emissions. Despite these measures, few studies have explored the interaction between these two drivers of carbon reduction. Therefore, this study aimed to examine the impact of green finance and environmental regulations on carbon emissions. To determine whether their coordination can lead to greater carbon reduction, the spatial spillover effect of this impact was also investigated. The results show that green finance can reduce carbon emissions and that the interaction of green finance with environmental regulations plays a significant positive role in reducing carbon emissions. Finally, this study concludes that the carbon reduction effects of green finance and environmental regulations have positive spillover effects on adjacent areas.

[Heavy Metal Pollution and Health Risk Assessment in Karst Basin Around a Lead-Zinc Mine].

Water quality is one of the most important environmental issues in the sustainable development of karst areas. To investigate heavy metal pollution and assess health risk in karst water basins around mines, 18 groups of water samples were collected from the river and groundwater in the Sidi River karst basin, and the concentrations of nine types of heavy metals(Cu, Pb, Zn, Cd, Mn, Fe, As, Cr, and Sr) were determined. Sample data were analyzed using principal component analysis, correlation analysis, water quality index, the Nemerow comprehensive pollution index, hazard quotient, and hazard index. The results showed that the Sidi River was slightly alkaline. The farther the river water samples were from the tailings reservoir, the lower were the concentrations of Cu, Pb, Zn, Cd, Mn, Fe, As, and Sr in the river water. Principal component and correlation analyses showed that heavy metals in the Sidi River karst basin mainly came from mine discharge(55.42%), carbonate weathering dissolution(21.41%), and human activities(14.72%). Eighty-two percent of the samples in the river and all the samples in the groundwater were excellent water. The Nemerow comprehensive pollution index in the river was 4.12 with strong pollution. All the hazard indices were below 1, and Pb, Zn, As, Cd, and Cr were potentially threatening metals in the Sidi River karst basin. The concentration of heavy metals changed significantly after entering the karst conduit, indicating that the unique properties of the karst aquifer affected the spatial variation of the heavy metal concentration. The results of this study can provide data reference for water resource prevention and human health protection in the Sidi River karst basin and similar karst basins.

Hidden Markov random field models for cell-type assignment of spatially resolved transcriptomics.

MOTIVATION: The recent development of spatially resolved transcriptomics (SRT) technologies has facilitated research on gene expression in the spatial context. Annotating cell types is one crucial step for downstream analysis. However, many existing algorithms use an unsupervised strategy to assign cell types for SRT data. They first conduct clustering analysis and then aggregate cluster-level expression based on the clustering results. This workflow fails to leverage the marker gene information efficiently. On the other hand, other cell annotation methods designed for single-cell RNA-seq data utilize the cell-type marker genes information but fail to use spatial information in SRT data. RESULTS: We introduce a statistical spatial transcriptomics cell assignment model, SPAN, to annotate clusters of cells or spots into known types in SRT data with prior knowledge of predefined marker genes and spatial information. The SPAN model annotates cells or spots from SRT data using predefined overexpressed marker genes and combines a mixture model with a hidden Markov random field to model the spatial dependency between neighboring spots. We demonstrate the effectiveness of SPAN against spatial and nonspatial clustering algorithms through extensive simulation and real data experiments. AVAILABILITY AND IMPLEMENTATION: https://github.com/ChengZ352/SPAN.

Risk assessment of venous thromboembolism in head and neck cancer patients and its establishment of a prediction model.

IMPORTANCE: Venous thromboembolism (VTE) is closely relevant to head and neck cancer (HNC) prognosis, but little data exist on the risk prediction of VTE in patients with HNC. OBJECTIVE: To study the risk factors regarding VTE in HNC patients and construct a nomogram model for its prediction. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional retrospective study was implemented to comparatively analyze 220 HNC patients from January 2018 to December 2021. The Lasso algorithm was used to optimize the selection of variables. A nomogram model for predicting HNC-associated VTE was established using multivariate logistic regression analysis. Internal validation of the model was performed by bootstrap resampling (1000 times). Calibration plot and decision curve analysis (DCA) were applied to evaluate the calibration capability of the prediction model. MAIN OUTCOME AND MEASURE: The demographics, medical history, blood biochemical indicators, and modalities of treatment were included for analysis. RESULTS: The incidence of HNC-associated VTE was 2.8% (55/1967) in authors' affiliation. Five variables of risk factors, including surgery, radiochemotherapy, D-dimer, aspartate transaminase, and globulin, were screened and selected as predictors by Lasso algorithm. A prediction model that incorporated these independent predictors was developed and presented as the nomogram. The model showed good discrimination with a C-index of 0.972 (95% CI: 0.934-0.997), and had an area under the receiver operating characteristic curve value of 0.981 (p < 0.001, 95% CI: 0.964-0.998). The calibration curve displayed good agreement of the predicted probability with the actual observed probability for HNC-associated VTE. The DCA plot showed that the application of this nomogram was associated with net benefit gains in clinical practice. CONCLUSIONS AND RELEVANCE: The high-performance nomogram model developed in this study may help early diagnose the risk of VTE in HNC patients and to guide individualized decision-making on thromboprophylaxis.

Optimizing Agronomic, Environmental, Health and Economic Performances in Summer Maize Production through Fertilizer Nitrogen Management Strategies.

Although nitrogen (N) fertilizer application plays an essential role in improving crop productivity, an inappropriate management can result in negative impacts on environment and human health. To break this dilemma, a 12-year field experiment (2008-2019) with five N application rates was conducted on the North China Plain (NCP) to evaluate the integrated impacts of optimizing N management (Opt. N, 160 kg N ha-1 on average) on agronomic, environmental, health, and economic performances of summer maize production. Over the 12-year study, the Opt. N treatment achieved the maximal average grain yield (10.6 Mg ha-1) and grain protein yield (793 kg ha-1) among five N treatments. The life cycle assessment methodology was applied to determine the negative impacts on environmental and human health, and both of them increased with the N rate. Compared with the farmers' conventional N rate (250 kg N ha-1), the Opt. N treatment reduced acidification, eutrophication, global warming, and energy depletion potentials by 29%, 42%, 35%, and 18%, respectively, and reduced the health impact by 32% per Mg of grain yield or grain protein yield produced. Both the Opt. N and Opt. N*50-70% treatments resulted in high private profitability (2038 USD ha-1), ecosystem economic benefit (1811 USD ha-1), and integrated compensation benefit (17,548 USD ha-1). This study demonstrates the potential benefits of long-term optimizing of N management to maintain high maize yields and grain quality, to reduce various environmental impacts and health impacts, and to enhance economic benefits. These benefits can be further enhanced when Opt. N was combined with advanced agronomic management practices. The results also suggest that reducing the optimal N rate from 160 to 145 kg N ha-1 is achievable to further reduce the negative impacts while maintaining high crop productivity. In conclusion, optimizing the N management is essential to promote sustainable summer maize production on the NCP.

Effects of osseous structure based on three-dimensional reconstructive imaging evaluation in the assessment of temporomandibular joint disc position.

OBJECTIVES: This pilot morphological study aimed to investigate the association between anterior disc displacement (ADD) and the status of the mandibular condyle and articular fossa. MATERIALS AND METHODS: Thirty-four patients were divided into a normal articular disc position group and an ADD with and without reduction group. Images reconstructed were used to determine multiple group comparisons of these three different types of disc position, and the diagnostic efficacy for the morphological parameters with significant group difference was analyzed to assess. RESULTS: The condylar volume (CV), condylar superficial area (CSA), superior joint space (SJS), and medial joint space (MJS) all exhibited obvious changes (P < 0.05). Additionally, they all had a reliable diagnostic accuracy in differentiating between normal disc position and ADD with an AUC value from 0.723 to 0.858. Among them, the CV, SJS, and MJS (P < 0.05) had a significantly positive impact on the groups by analysis of multivariate logistic ordinal regression model. CONCLUSIONS: The CV, CSA, SJS, and MJS are significantly associated with different disc displacement types. The condyle in ADD exhibited altered dimensions. These could be promising biometric markers for assessing ADD. CLINICAL RELEVANCE: The morphological changes of mandibular condyle and glenoid fossa were significantly influenced by the status of disc displacement, and condyles with disc displacement had three-dimensionally altered condylar dimensions, irrespective of age and sex.

Impact of environmental regulations on the industrial eco-efficiency in China-based on the strong porter hypothesis and the weak porter hypothesis.

As an important indicator of sustainable development, industrial eco-efficiency (IEE) has aroused growing attention from governments all over the world including China, in recent decades. The Chinese government has introduced numerous environmental regulations; however, the environmental pollution issue does not appear to have been solved. Moreover, although several earlier studies have shown that environmental regulations may promote innovation, there is no consensus on their ultimate effects on IEE. Therefore, this study took a critical look at the connection between environmental regulations and IEE in 36 Chinese sub-sectors from 2009 to 2018. Based on the weak Porter hypothesis (weak PH) and strong Porter hypothesis (strong PH), this paper constructed two panel regression models and conducted group analysis by pollution intensity to check the relationships among environmental regulations, technological innovation, and IEE. It was found that environmental regulations can improve technological innovation and IEE, but these impacts vary across different pollution groups. Specifically, environmental regulations have a U-shaped or inverted U-shaped relationship with technological innovation and IEE. Of the 36 sub-sectors, 26 prove the existence of the Weak PH while 10 verify the Strong PH, indicating that environmental regulations generally advocate technological innovation for most sub-sectors but only promote IEE in a few sub-sectors at present. Finally, differentiated policy implications for environmental regulations and technological innovation are provided for decision-makers.

Dissolved Heavy Metal Pollution and Assessment of a Karst Basin around a Mine, Southwest China.

Karst water quality is one of the most important environmental issues in karst areas. The study's purpose was to investigate dissolved heavy metal pollution and health risk assessment in karst water basins around mines. River water and groundwater samples were analyzed by principal component analysis, correlation analysis, water quality index, hazard quotient, and hazard index. Median concentrations of dissolved heavy metals in the Sidi River were similar to the world average with a slightly alkaline characteristic. The concentrations of most dissolved heavy metals in river water were higher than those in groundwater. The concentrations of Zn, Pb, and Cd around the mine exceeded the limits of drinking water indicators. The poor water quality samples with high water quality index values were distributed around the mine. Lead (Pb), Zn, As, Cd, and Cr were potentially threatening metals in the study area. The pollution level of dissolved heavy metals in the Sidi River was at a medium level compared with other rivers worldwide. Principal component analysis and correlation analysis showed that Cu, Pb, Zn, Cd, Mn, Fe, As, and Sr mainly came from mine drainage; Ca2+, Mg2+, and Cr mainly came from the contribution of carbonate rocks; Na+ and K+ were related to local human agricultural activities. The concentrations of dissolved heavy metals in groundwater were affected by karst aquifers. The results of this study can provide a data reference for water resources prevention and human health protection in the Sidi River's karst basin and similar karst basins.

Identification of Landslides in Mountainous Area with the Combination of SBAS-InSAR and Yolo Model.

Landslides have been frequently occurring in the high mountainous areas in China and poses serious threats to peoples' lives and property, economic development, and national security. Detecting and monitoring quiescent or active landslides is important for predicting risks and mitigating losses. However, traditional ground survey methods, such as field investigation, GNSS, and total stations, are only suitable for field investigation at a specific site rather than identifying landslides over a large area, as they are expensive, time-consuming, and laborious. In this study, the feasibility of using SBAS-InSAR to detect landslides in the high mountainous areas along the Yunnan Myanmar border was tested first, with fifty-four IW mode Sentinel-1A ascending scenes from 12 January 2019 to 8 December 2020. Next, the Yolo deep-learning model with Gaofen-2 images captured on 5 December 2020 was tested. Finally, the two techniques were combined to achieve better performance, given each of them has intrinsic limitations on landslide detection. The experiment indicated that the combination could improve the match rate between detection results and references, which implied that the performance of landslide detection can be improved with the fusion of time series SAR images and optical images.

A detailed assessment of liver function in patients with hepatocellular carcinoma via the modified albumin-bilirubin (mALBI) grade.

Recently, the albumin-bilirubin (ALBI) score, a continuous index consisting of only albumin and bilirubin, has been developed for objectively assessing liver function in patients with hepatocellular carcinoma (HCC). However, the ALBI score was arbitrarily categorized into three ALBI grades based on two artificially predetermined cutoff points with no explanation and statistical grounds, causing a considerable loss of discriminatory ability. This study aims to propose a modified ALBI (mALBI) grade for offering a detailed evaluation of hepatic reserve and specify its role during clinical practice in the HCC setting. The study population comprised 3540 HCC patients treated with mainstream therapies including hepatectomy (n=2056), thermal ablation (n=550), and transcatheter arterial chemoembolization (n=934) from 2002 to 2017. The ALBI score was stratified into four mALBI grades through a recently proposed statistical method aiming to select the optimal cutoff points of a continuous predictive variable by maximizing the discriminative ability in a multivariable Cox regression model. The mALBI grade had an overall better discriminatory ability than the ALBI grade in predicting overall survival through Harrell's C-index (0.614 vs. 0.598, P<0.001). Both visual inspections of Kaplan-Meier curves and calculation of hazard ratios displayed a more subtle evaluation of liver function using the mALBI grade. Moreover, the newly identified cut-point (ALBI score = -2.29) between the mALBI grade 2a and 2b was much closer to a 30% retention rate of indocyanine green at 15 minutes, an indicator for the performance of a subsegmentectomy. The newly proposed mALBI grade provides a more subtle assessment of liver function to guide clinical decision-making and predicts the prognosis of HCC patients more accurately than the original ALBI grade.

Hierarchical reinforcement learning for automatic disease diagnosis.

MOTIVATION: Disease diagnosis-oriented dialog system models the interactive consultation procedure as the Markov decision process, and reinforcement learning algorithms are used to solve the problem. Existing approaches usually employ a flat policy structure that treat all symptoms and diseases equally for action making. This strategy works well in a simple scenario when the action space is small; however, its efficiency will be challenged in the real environment. Inspired by the offline consultation process, we propose to integrate a hierarchical policy structure of two levels into the dialog system for policy learning. The high-level policy consists of a master model that is responsible for triggering a low-level model, the low-level policy consists of several symptom checkers and a disease classifier. The proposed policy structure is capable to deal with diagnosis problem including large number of diseases and symptoms. RESULTS: Experimental results on three real-world datasets and a synthetic dataset demonstrate that our hierarchical framework achieves higher accuracy and symptom recall in disease diagnosis compared with existing systems. We construct a benchmark including datasets and implementation of existing algorithms to encourage follow-up researches. AVAILABILITY AND IMPLEMENTATION: The code and data are available from https://github.com/FudanDISC/DISCOpen-MedBox-DialoDiagnosis. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Dysfunction of the Hippocampal-Lateral Septal Circuit Impairs Risk Assessment in Epileptic Mice.

Temporal lobe epilepsy, a chronic disease of the brain characterized by degeneration of the hippocampus, has impaired risk assessment. Risk assessment is vital for survival in complex environments with potential threats. However, the underlying mechanisms remain largely unknown. The intricate balance of gene regulation and expression across different brain regions is related to the structure and function of specific neuron subtypes. In particular, excitation/inhibition imbalance caused by hyperexcitability of glutamatergic neurons and/or dysfunction of GABAergic neurons, have been implicated in epilepsy. First, we estimated the risk assessment (RA) by evaluating the behavior of mice in the center of the elevated plus maze, and found that the kainic acid-induced temporal lobe epilepsy mice were specifically impaired their RA. This experiment evaluated approach-RA, with a forthcoming approach to the open arm, and avoid-RA, with forthcoming avoidance of the open arm. Next, results from free-moving electrophysiological recordings showed that in the hippocampus, ∼7% of putative glutamatergic neurons and ∼15% of putative GABAergic neurons were preferentially responsive to either approach-risk assessment or avoid-risk assessment, respectively. In addition, ∼12% and ∼8% of dorsal lateral septum GABAergic neurons were preferentially responsive to approach-risk assessment and avoid-risk assessment, respectively. Notably, during the impaired approach-risk assessment, the favorably activated dorsal dentate gyrus and CA3 glutamatergic neurons increased (∼9%) and dorsal dentate gyrus and CA3 GABAergic neurons decreased (∼7%) in the temporal lobe epilepsy mice. Then, we used RNA sequencing and immunohistochemical staining to investigate which subtype of GABAergic neuron loss may contribute to excitation/inhibition imbalance. The results show that temporal lobe epilepsy mice exhibit significant neuronal loss and reorganization of neural networks. In particular, the dorsal dentate gyrus and CA3 somatostatin-positive neurons and dorsal lateral septum cholecystokinin-positive neurons are selectively vulnerable to damage after temporal lobe epilepsy. Optogenetic activation of the hippocampal glutamatergic neurons or chemogenetic inhibition of the hippocampal somatostatin neurons directly disrupts RA, suggesting that an excitation/inhibition imbalance in the dHPC dorsal lateral septum circuit results in the impairment of RA behavior. Taken together, this study provides insight into epilepsy and its comorbidity at different levels, including molecular, cell, neural circuit, and behavior, which are expected to decrease injury and premature mortality in patients with epilepsy.

Low-cost and easy-fabrication lightweight drivable electrode array for multiple-regions electrophysiological recording in free-moving mice.

Objective.Extracellular electrophysiology has been widely applied to neural circuit dissections. However, long-term multiregional recording in free-moving mice remains a challenge. Low-cost and easy-fabrication of elaborate drivable electrodes is required for their prevalence.Approach.A three-layer nested construct (outside diameter, OD ∼ 1.80 mm, length ∼10 mm, <0.1 g) was recruited as a drivable component, which consisted of an ethylene-vinyl acetate copolymer heat-shrinkable tube, non-closed loop ceramic bushing, and stainless ferrule with a bulge twining silver wire. The supporting and working components were equipped with drivable components to be assembled into a drivable microwire electrode array with a nested structure (drivable MEANS). Two drivable microwire electrode arrays were independently implanted for chronic recording in different brain areas at respective angles. An optic fiber was easily loaded into the drivable MEANS to achieve optogenetic modulation and electrophysiological recording simultaneously.Main results.The drivable MEANS had lightweight (∼0.37 g), small (∼15 mm × 15 mm × 4 mm), and low cost (⩽$64.62). Two drivable MEANS were simultaneously implanted in mice, and high-quality electrophysiological recordings could be applied ⩾5 months after implantation in freely behaving animals. Electrophysiological recordings and analysis of the lateral septum (LS) and lateral hypothalamus in food-seeking behavior demonstrated that our drivable MEANS can be used to dissect the function of neural circuits. An optical fiber-integrated drivable MEANS (∼0.47 g) was used to stimulate and record LS neurons, which suggested that changes in working components can achieve more functions than electrophysiological recordings, such as optical stimulation, drug release, and calcium imaging.Significance.Drivable MEANS is an easily fabricated, lightweight drivable microwire electrode array for multiple-region electrophysiological recording in free-moving mice. Our design is likely to be a valuable platform for both current and prospective users, as well as for developers of multifunctional electrodes for free-moving mice.

Valuable Clues for DCNN-Based Landslide Detection from a Comparative Assessment in the Wenchuan Earthquake Area.

Landslide inventories could provide fundamental data for analyzing the causative factors and deformation mechanisms of landslide events. Considering that it is still hard to detect landslides automatically from remote sensing images, endeavors have been carried out to explore the potential of DCNNs on landslide detection, and obtained better performance than shallow machine learning methods. However, there is often confusion as to which structure, layer number, and sample size are better for a project. To fill this gap, this study conducted a comparative test on typical models for landside detection in the Wenchuan earthquake area, where about 200,000 secondary landslides were available. Multiple structures and layer numbers, including VGG16, VGG19, ResNet50, ResNet101, DenseNet120, DenseNet201, UNet-, UNet+, and ResUNet were investigated with different sample numbers (100, 1000, and 10,000). Results indicate that VGG models have the highest precision (about 0.9) but the lowest recall (below 0.76); ResNet models display the lowest precision (below 0.86) and a high recall (about 0.85); DenseNet models obtain moderate precision (below 0.88) and recall (about 0.8); while UNet+ also achieves moderate precision (0.8) and recall (0.84). Generally, a larger sample set can lead to better performance for VGG, ResNet, and DenseNet, and deeper layers could improve the detection results for ResNet and DenseNet. This study provides valuable clues for designing models' type, layers, and sample set, based on tests with a large number of samples.

Diagnostic assessment of deep learning for melanocytic lesions using whole-slide pathological images.

BACKGROUND: Deep learning has the potential to improve diagnostic accuracy and efficiency in medical image recognition. In the current study, we developed a deep learning algorithm and assessed its performance in discriminating melanoma from nevus using whole-slide pathological images (WSIs). METHODS: The deep learning algorithm was trained and validated using a set of 781 WSIs (86 melanomas, 695 nevi) from PLA General Hospital. The diagnostic performance of the algorithm was tested on an independent test set of 104 WSIs (29 melanomas, 75 nevi) from Tianjin Chang Zheng Hospital. The same test set was also diagnostically classified by 7 expert dermatopathologists. RESULTS: The deep learning algorithm receiver operating characteristic (ROC) curve achieved a sensitivity 100% at the specificity of 94.7% in the classification of melanoma and nevus on the test set. The area under ROC curve was 0.99. Dermatopathologists achieved a mean sensitivity and specificity of 95.1% (95% confidence interval [CI]: 92.0%-98.2%) and 96.0% (95% CI: 94.2%-97.8%), respectively. At the operating point of sensitivity of 95.1%, the algorithm revealed a comparable specificity with 7 dermatopathologists (97.3% vs. 96.0%, P = 0.11). At the operating point of specificity of 96.0%, the algorithm also achieved a comparable sensitivity with 7 dermatopathologists (96.5% vs. 95.1%, P = 0.30). A more transparent and interpretable diagnosis could be generated by highlighting the regions of interest recognized by the algorithm in WSIs. CONCLUSION: The performance of the deep learning algorithm was on par with that of 7 expert dermatopathologists in interpreting WSIs with melanocytic lesions. By pre-screening the suspicious melanoma regions, it might serve as a supplemental diagnostic tool to improve working efficiency of pathologists.

[Water Quality Analysis and Health Risk Assessment for Groundwater at Xiangshui, Chongzuo].

To investigate the environmental quality and human health risks of different types of groundwater at Xiangshui, Chongzuo, several regular water quality indexes and concentrations of metals in 60 groundwater samples were measured and analyzed. The environmental quality of groundwater was analyzed by means of the Nemerow index. The health risks were assessed by using a human health risk assessment model. The regular water quality indexes and concentrations of metals of the well water, spring water, and underground river water exceeded the standards to different degrees. The environmental quality of groundwater was at a poor grade. The comprehensive evaluation score of underground river water (F=4.26) was the lowest. The well water had the same score as spring water (F=7.10). The high hardness and salinity were conducive to enrichment of Cr, and the reducing environment was of great advantage for the enrichment of As. The environmental geochemistry of Zn, Pb, Cd, and Cu was similar. The sources of Fe, Al, and Mn were similar. The results of the health risk assessment indicated that the health risks of well water, spring water, and underground river water were relatively high. The health risks decreased in the order of well water > underground river water > spring water. The health risks mainly came from the carcinogenic metallic element Cr. Carcinogenic risks were 4-6 orders of magnitude higher than non-carcinogenic risks. Carcinogenic risks were higher than the maximum allowance levels (5.0×10-5 a-1). Non-carcinogenic risks were lower than the allowance levels (10-6 a-1). Children had greater health risks than adults. The health risks of metals through the drinking pathway were 2-3 orders of magnitude higher than the values caused by the dermal contact pathway. For the sake of drinking water safety, the well water, underground river water, and spring water should be properly treated and the concentration of Cr in groundwater should be controlled before drinking.

A progressive compression model of thoracic spinal cord injury in mice: function assessment and pathological changes in spinal cord.

Non-traumatic injury accounts for approximately half of clinical spinal cord injury, including chronic spinal cord compression. However, previous rodent spinal cord compression models are mainly designed for rats, few are available for mice. Our aim is to develop a thoracic progressive compression mice model of spinal cord injury. In this study, adult wild-type C57BL/6 mice were divided into two groups: in the surgery group, a screw was inserted at T9 lamina to compress the spinal cord, and the compression was increased by turning it further into the canal (0.2 mm) post-surgery every 2 weeks up to 8 weeks. In the control group, a hole was drilled into the lamina without inserting a screw. The results showed that Basso Mouse Scale scores were lower and gait worsened. In addition, the degree of hindlimb dysfunction in mice was consistent with the degree of spinal cord compression. The number of motor neurons in the anterior horn of the spinal cord was reduced in all groups of mice, whereas astrocytes and microglia were gradually activated and proliferated. In conclusion, this progressive compression of thoracic spinal cord injury in mice is a preferable model for chronic progressive spinal cord compression injury.

Surfactant-activated lipase hybrid nanoflowers with enhanced enzymatic performance.

Increasing numbers of materials have been extensively used as platforms for enzyme immobilization to improve catalytic performance. However, activity of the most of the enzymes was declined after immobilization. Here, we develop a surfactant-activated lipase-inorganic flowerlike hybrid nanomaterials with rational design based on interfacial activation and self-assembly. The resulting surfactant-activated lipase-inorganic hybird nanoflower (activated hNF-lipase) exhibited 460% and 200% higher activity than native lipase and conventional lipase-inorganic hybird nanoflower (hNF-lipase). Furthermore, the activated hNF-lipase displayed good reusability due to its monodispersity and mechanical properties, and had excellent long-time stability. The superior catalytic performances were attributed to both the conformational modulation of surfactants and hierarchical structure of nanoflowers, which not only anchored lipases in an active form, but also decreased the enzyme-support negative interaction and mass-transfer limitations. This new biocatalytic system is promising to find widespread use in applications related to biomedicine, biosensor, and biodiesel.

Full-Endoscopic Procedures Versus Traditional Discectomy Surgery for Discectomy: A Systematic Review and Meta-analysis of Current Global Clinical Trials.

BACKGROUND: Traditional discectomy surgery (TDS) provides good or excellent results in clinical surgical discectomy but may induce neural adhesion, spinal structural damage, instability, and other complications. The potential advantages of full-endoscopic (FE) procedures over standard TDS include less blood loss, less postoperative pain, shorter hospitalization, and an earlier return to work. However, more evidence is needed to support this new technology in clinical applications. OBJECTIVE: The aim of this systematic review and meta-analysis was to compare the safety and efficacy of FE and TDS. STUDY DESIGN: Comprehensive systematic review and meta-analysis of the literature. METHODS: Electronic databases, including PubMed, EMBASE, SinoMed, and Cochrane Library, were searched to identify clinical therapeutic trials comparing FE to TDS for discectomy. RESULTS: Six trials comprising 730 patients were included, and the overall quality of the literature was moderate, including 4 Grade I levels of evidence (4 randomized controlled trials, [RCTs]) and 2 Grade II levels (2 non-RCTs). The pooled data revealed no difference in reoperation rates between FE and TDS (P = 0.94), but the complication rate was significantly lower in the FE group (3.86%) than in the TDS group (11.4%). Perioperative parameters (operation time, blood loss, hospitalization time, and return to work days) were significantly lower in the FE group (P < 0.05 for all groups using either score). Postoperative pain and neurology score assessments were conducted at 4 different time points at 3 months, 6 months, 12 months, and 24 months. Significant differences were detected in the following: lumbar North American Spine Society (NASS) pain at 6 months (P = 0.008); cervical NASS neurology at 6 months (P = 0.03); visual analog scale (VAS) score in leg at 3 months (P < 0.001); VAS score in arm at 24 months (P = 0.002); VAS score in neck at 3 months, 6 months, and 12 months after therapy (P = 0.003, P = 0.004, P = 0.01); and VAS score in neck at 3 months and 6 months (P = 0.01, P = 0.004). Moreover, the pooled data revealed no statistically significant differences in improvements in the Oswestry disability index (ODI), instability (X-ray), and Hilibrand criteria (P > 0.05 for all groups). LIMITATIONS: Only 6 studies were included, 4 of which had the same authors. Between-study heterogeneity due to differences in socioeconomic factors, nutrition, and matching criteria is difficult to avoid. CONCLUSIONS: Based on this meta-analysis of 24 months of clinical results, we conclude that the FE procedure is as effective as TDS but has the additional benefits of lower complication rates and superior perioperative parameters. In addition, patients may experience less pain with FE techniques due to a smaller incision and less operative injury. However, large-volume, well-designed RCTs with extensive follow-up are needed to confirm and update the findings of this analysis.