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Abstract Purpose Currently, deep learning methods for the classification of benign and malignant lung nodules encounter challenges encompassing intricate and unstable algorithmic models, limited data adaptability, and an abundance of model parameters.To tackle these concerns, this investigation introduces a novel approach: the 3D Global Coordinated Attention Wide Inverted ResNet Network (GC-WIR). This network aims to achieve precise classification of benign and malignant pulmonary nodules, leveraging its merits of heightened efficiency, parsimonious parameterization, and robust stability. Methods Within this framework, a 3D Global Coordinate Attention Mechanism (3D GCA) is designed to compute the features of the input images by converting 3D channel information and multi-dimensional positional cues. By encompassing both global channel details and spatial positional cues, this approach maintains a judicious balance between flexibility and computational efficiency. Furthermore, the GC-WIR architecture incorporates a 3D Wide Inverted Residual Network (3D WIRN), which augments feature computation by expanding input channels. This augmentation mitigates information loss during feature extraction, expedites model convergence, and concurrently enhances performance. The utilization of the inverted residual structure imbues the model with heightened stability. Results Empirical validation of the GC-WIR method is performed on the LUNA 16 dataset, yielding predictions that surpass those generated by previous models. This novel approach achieves an impressive accuracy rate of 94.32%, coupled with a specificity of 93.69%. Notably, the model’s parameter count remains modest at 5.76M, affording optimal classification accuracy. Conclusion Furthermore, experimental results unequivocally demonstrate that, even under stringent computational constraints, GC-WIR outperforms alternative deep learning methodologies, establishing a new benchmark in performance.

BackgroundThe systemic immuno-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are widely used and have been shown to be predictive indicators of various diseases. Diabetic nephropathy (DN), retinopathy (DR), and peripheral neuropathy (DPN) are the most prominent and common microvascular complications, which have seriously negative impacts on patients, families, and society. Exploring the associations with these three indicators and diabetic microvascular complications are the main purpose.MethodsThere were 1058 individuals with type 2 diabetes mellitus (T2DM) in this retrospective cross-sectional study. SII, NLR, and PLR were calculated. The diseases were diagnosed by endocrinologists. Logistic regression and subgroup analysis were applied to evaluate the association between SII, NLP, and PLR and diabetic microvascular complications.ResultsSII, NLR, and PLR were significantly associated with the risk of DN [odds ratios (ORs): 1.52, 1.71, and 1.60, respectively] and DR [ORs: 1.57, 1.79, and 1.55, respectively] by multivariate logistic regression. When NLR ≥2.66, the OR was significantly higher for the risk of DPN (OR: 1.985, 95% confidence interval: 1.29–3.05). Subgroup analysis showed no significant positive associations across different demographics and comorbidities, including sex, age, hypertension, HbA1c (glycated hemoglobin), and dyslipidemia.ConclusionThis study found a positive relationship between NLR and DN, DR, and DPN. In contrast, SII and PLR were found to be only associated with DN and DR. Therefore, for the diagnosis of diabetic microvascular complications, SII, NLR and PLR are highly valuable.

Abstract Objective To explore the surgical techniques, advantages, and disadvantages of neuroendoscopic telovelar approach in the treatment of brainstem and fourth ventricle lesions. Methods The clinical data of 5 patients treated by neuroendoscopic telovelar approach from March 2020 to March 2022 were analyzed retrospectively. Results Among the 5 patients, there were 3 cavernous hemangiomas in pontine arm and 2 tumors in brainstem and fourth ventricle. All patients could successfully complete the operation, and 4 patients recovered well, other 1 patient discharged automatically for serious complications of other systems after the operation. Conclusion The telovelar approach has gained popularity as a safe and effective strategy for lesions in fourth ventricular and brainstem. However, without removing the posterior arch of the atlas, it is difficult to enter the upper part of the fourth ventricle under a microscope. Transcranial neuroendoscopy can effectively compensate for the shortcomings of microscopy, whether used as an auxiliary measure for microsurgery or alone with proficient endoscopic techniques, it will provide greater application in minimally invasive surgery for fourth ventricle and brainstem lesions. By utilizing the excellent degree of freedom of transcranial neuroendoscopy, there is no need to open the posterior arch of the atlas, making the surgery more minimally invasive. However, the sample size of this study is small, and it was completed under the very mature neuroendoscopic technology of our team. Its general safety and practicality still require extensive clinical research validation.

Due to the inadequacy in utilizing complementary information from different modalities and the biased estimation of degraded parameters, the unsupervised hyperspectral super-resolution algorithm suffers from low precision and limited applicability. To address this issue, this paper proposes an approach for hyperspectral image super-resolution, namely, the Unsupervised Multimodal Multilevel Feature Fusion network (UMMFF). The proposed approach employs a gated cross-retention module to learn shared patterns among different modalities. This module effectively eliminates the intermodal differences while preserving spatial–spectral correlations, thereby facilitating information interaction. A multilevel spatial–channel attention and parallel fusion decoder are constructed to extract features at three levels (low, medium, and high), enriching the information of the multimodal images. Additionally, an independent prior-based implicit neural representation blind estimation network is designed to accurately estimate the degraded parameters. The utilization of UMMFF on the “Washington DC”, Salinas, and Botswana datasets exhibited a superior performance compared to existing state-of-the-art methods in terms of primary performance metrics such as PSNR and ERGAS, and the PSNR values improved by 18.03%, 8.55%, and 5.70%, respectively, while the ERGAS values decreased by 50.00%, 75.39%, and 53.27%, respectively. The experimental results indicate that UMMFF demonstrates excellent algorithm adaptability, resulting in high-precision reconstruction outcomes.

Efficient hydrogen storage and transportation are crucial for the sustainable development of human society. Ammonia, with a hydrogen storage density of up to 17.6 wt%, is considered an ideal energy carrier for large-scale hydrogen storage and has great potential for development and application in the “hydrogen economy”. However, achieving ammonia decomposition to hydrogen under mild conditions is challenging, and therefore, the development of suitable catalysts is essential. Metal oxide-based catalysts are commonly used in the industry. This paper presents a comprehensive review of single and composite metal oxide catalysts for ammonia decomposition catalysis. The focus is on analyzing the conformational relationships and interactions between metal oxide carriers and active metal sites. The aim is to develop new and efficient metal oxide-based catalysts for large-scale green ammonia decomposition.

Abstract Background Bladder cancer is one of the most common malignant tumors of the urinary system and is associated with a poor prognosis once invasion and distant metastases occur. Epithelial-mesenchymal transition (EMT) drives metastasis and invasion in bladder cancer. Transforming growth factor β1 (TGF-β1) and stromal fibroblasts, especially cancer-associated fibroblasts (CAFs), are positive regulators of EMT in bladder cancer. However, it remains unclear how TGF-β1 mediates crosstalk between bladder cancer cells and CAFs and how it induces stromal fibroblast-mediated EMT in bladder cancer. We aimed to investigate the mechanism of TGF-β1 regulation of stromal fibroblast-mediated EMT in bladder cancer cells. Methods Primary CAFs with high expression of fibroblast activation protein (FAP) were isolated from bladder cancer tissue samples. Subsequently, different conditioned media were used to stimulate the bladder cancer cell line T24 in a co-culture system. Gene set enrichment analysis, a human cytokine antibody array, and cytological assays were performed to investigate the mechanism of TGF-β1 regulation of stromal fibroblast-mediated EMT in bladder cancer cells. Results Among the TGF-β family, TGF-β1 was the most highly expressed factor in bladder cancer tissue and primary stromal fibroblast supernatant. In the tumor microenvironment, TGF-β1 was mainly derived from stromal fibroblasts, especially CAFs. In stimulated bladder cells, stromal fibroblast-derived TGF-β1 promoted bladder cancer cell migration, invasion, and EMT. Furthermore, TGF-β1 promoted the activation of stromal fibroblasts, inducing CAF-like features, by upregulating FAP in primary normal fibroblasts and a normal fibroblast cell line. Stromal fibroblast-mediated EMT was induced in bladder cancer cells by TGF-β1/FAP. Versican (VCAN), a downstream molecule of FAP, plays an essential role in TGF-β1/FAP axis-induced EMT in bladder cancer cells. VCAN may also function through the PI3K/AKT1 signaling pathway. Conclusions TGF-β1 is a critical mediator of crosstalk between stromal fibroblasts and bladder cancer cells. We revealed a new mechanism whereby TGF-β1 dominated stromal fibroblast-mediated EMT of bladder cancer cells via the FAP/VCAN axis and identified potential biomarkers (FAP, VCAN, N-cadherin, and Vimentin) of bladder cancer. These results enhance our understanding of bladder cancer invasion and metastasis and provide potential strategies for diagnosis, treatment, and prognosis.

In order to solve the serious problems of F−、Fe2+ and Mn2+ in underground water of mining area, the serpentine loaded hydroxy-apatite (Srp/HAP) composite adsorbent was prepared by wet chemical coprecipitation method, and the simultaneous removal of fluorine, iron and manganese in underground water was studied. Through batch experiment and CCD response optimization experiment, the effects of dosage, reaction time and pH on the removal efficiency of F−、Fe2+ and Mn2+ were investigated, and a quadratic regression model with the removal rates of F−、Fe2+ and Mn2+ as response values was established. Srp/HAP adsorption and regeneration experiments were carried out to explore its reusability. The results show that the optimal reaction conditions of Srp/HAP treatment of complex water samples with mass concentrations of F−、Fe2+ and Mn2+ of 5 mg/L, 20 mg/L and 5 mg/L respectively are as follows: When 3.64 g/L water sample was added, the reaction time was 120.47 min and the pH value was 6.3, the corresponding removal rates of F−、Fe2+ and Mn2+ were 98.23%, 99.9% and 99.7% respectively. The effluent shall meet the requirements of the 《Standards for drinking water quality》(GB5749—2006).The adsorption process of F−、Fe2+ and Mn2+ by Srp/HAP was well fitted by the CCD optimized experimental model. The absolute error between the predicted value and the experimental value is less than 5%, which proves that the experimental model is reliable. After five times of regeneration, the removal rates of F−、Fe2+ and Mn2+ by Srp/HAP composite particles decreased by 16.13%, 10.5% and 15.4%, respectively, less than 20%. Srp/HAP composite particles can be used as an excellent adsorbent for the treatment of groundwater containing fluoride, iron and manganese ions.

Abstract Existing molecular property prediction methods based on deep learning ignore the generalization ability of the nonlinear representation of molecular features and the reasonable assignment of weights of molecular features, making it difficult to further improve the accuracy of molecular property prediction. To solve the above problems, an end-to-end double-head transformer neural network (DHTNN) is proposed in this paper for high-precision molecular property prediction. For the data distribution characteristics of the molecular dataset, DHTNN specially designs a new activation function, beaf, which can greatly improve the generalization ability of the nonlinear representation of molecular features. A residual network is introduced in the molecular encoding part to solve the gradient explosion problem and ensure that the model can converge quickly. The transformer based on double-head attention is used to extract molecular intrinsic detail features, and the weights are reasonably assigned for predicting molecular properties with high accuracy. Our model, which was tested on the MoleculeNet [1] benchmark dataset, showed significant performance improvements over other state-of-the-art methods.

Abstract To explore the clinical advantages of 3D-Slicer + 3D printing guide combined with transcranial neuroendoscopic in minimally invasive neurosurgery. By collecting the datum of patients who underwent craniotomy under 3D-Slicer + 3D printing guide plate positioning combined with transcranial neuroendoscopic in our hospital from October 2021 to February 2022, this paper introduces the accurate planning and positioning lesions of patients before operation and the minimally invasive operation of intraoperative neuroendoscopic and analyses clinical data such as lesion size and surgical bone window size. We collected the case datum of 16 patients who underwent craniocerebral surgery with 3D-Slicer + 3D printing guide combined with transcranial neuroendoscopic, including 5 males and 11 females, aged 46–76 years, including 6 brain tumors (3 meningiomas, 1 glioblastoma, 2 lung cancer brain metastases), 2 cavernous hemangioma, 7 hydrocephalus and 1 chronic subdural hematoma. The lesions of the 16 patients were located accurately before operation and the target areas were reached quickly during operation. Postoperative imaging datum confirmed that the lesions was removed fully, and the ventricular end of shunt tube was in good position. The technology of 3D-Slicer + 3D printing guide plate combined with transcranial neuroendoscopic is not difficult, which has many advantages such as inexpensive equipment, simple operation, easy learning, accurate positioning, and minimally invasive surgery. It is considered to be a practical technology that is feasible, reliable, convenient for diagnosis, preoperative planning and minimally invasive surgery. It is suitable for promotion in neurosurgery and other surgical departments of all medical institutions.

Abstract To explore the clinical advantages of 3D Slicer combined with Sina/MosoCam multimodal system in preoperative planning of brain lesions surgery. By collecting the data of brain lesions patients undergoing craniotomy under the preoperative positioning of 3D Slicer combined Sina/MosoCam multimodal system in the people's Hospital of Wuhan University from January 2021 to October 2021, the preoperative planning of patients was introduced, and the size of surgical bone window, operation time, preoperative and postoperative neurological dysfunction were counted. We collected the case data of 35 patients who were reconstructed by 3D Slicer and located by Sina/MosoCam projection. There were 14 cases of malignant tumors (7 cases of glioma, 2 cases of diffuse large B-cell lymphoma, 5 cases of metastatic cancer) and 21 cases of benign tumors (17 cases of meningioma, 1 case of central neurocytoma, 2 cases of cavernous hemangioma and 1 case of arachnoid cyst). All 35 patients were located accurately before operation, the lesions were found quickly during operation, and the postoperative imaging data confirmed that the lesions were removed completely, of which 28 cases (80%) had significantly improved neurological symptoms one month after operation. 3D Slicer combined with Sina/MosoCam multimodal system has many advantages, such as simple and easy to learn, convenient operation, accurate positioning and free. It is considered to be a new technology that is practical, reliable, convenient for diagnosis and preoperative planning. It is suitable for popularization and use in neurosurgery and other operating rooms of all medical institutions.

Abstract Background Inappropriate use of antibiotics in children is common in many countries. The purpose of the study was to explore patterns of antibiotic prescribing in children’s outpatient clinics in primary care institutions in a province of southwest China. Methods We obtained electronic prescription data from 75 primary care institutions in Guizhou province in 2020. The classification of incorrect spectrum of antibiotics, unnecessary use and combined use of antibiotics was based on the Guiding Principle of Clinical Use of Antibiotics (2015, China) and guidelines from the USA Centers for Disease Control and Prevention. Potential risk factors for inappropriate use of antibiotics were identified using bivariate analyses. The generalized estimation equation was used to identify independent predictors of inappropriate use of antibiotics. Results A total of 158,267 antibiotic prescriptions were retrieved. Acute upper respiratory tract infections were the most common diseases, accounting for 74.9% of all prescriptions. The main antibiotic group used was penicillins (63.7%), followed by cephalosporins (18.8%). Of 137,284 visits, 18.3% of antibiotic prescriptions were appropriate and the percentage of unnecessary use, incorrect spectrum of antibiotics and combined use of antibiotics was 76.9, 2.4 and 2.4%, respectively. Physicians with lower professional titles and more than 40 years of work duration were relatively more likely to prescribe inappropriate antibiotics. Conclusion The inappropriate use of antibiotics in children is still prominent in primary care institutions of southwest China. The education and training of physicians and caregivers in these institutions should be strengthened.

Introduction: Pure ventricular hemorrhage is often secondary to Moyamoya disease, rarely caused by rupture of ventricular aneurysm. The surgical treatment of the latter is very challenging. 3D Slicer reconstruction technology can accurately locate small intracranial lesions and combined with minimally invasive surgery with transcranial neuroendoscope is a new attempt to treat the above diseases. Case presentation: We report a case of pure intraventricular hemorrhage secondary to rupture of a distal segment aneurysm of the anterior choroidal artery. Brain computed tomography (CT) before admission showed pure ventricular hemorrhage, and brain CT angiography (CTA) before operation showed a distal segment aneurysm of the anterior choroidal artery. We used 3D Slicer reconstruction and precise location of the focus before the operation and used the minimally invasive surgery technique with transcranial neuroendoscope to completely remove the hematoma in the ventricle, and found the responsible aneurysm located in the ventricle. Conclusion: Pure intraventricular hemorrhage requires vigilance against the distal segment aneurysm of the anterior choroidal artery. At present, conventional microscopic craniotomy and intravascular interventional therapy have limitations, and 3D Slicer reconstruction and precise positioning technology combined with transcranial neuroendoscope minimally invasive surgery may be a good choice.

Abstract. Background:. The dermoscopic features of rosacea have already been reported. However, the current findings are incomplete, and little is known about phymatous rosacea. Hence, this study aimed to summarize and compare the dermoscopic features and patterns of three rosacea subtypes (erythematotelangiectatic [ETR], papulopustular [PPR], and phymatous [PHR]) in the Chinese Han population and to evaluate whether these features differ with patients’ genders, ages, and durations. Methods:. Dermoscopic images of 87 rosacea patients were collected in non-polarized and polarized dermoscopy contact modes at 20-fold magnification. Dermoscopic features, including vessels, scales, follicular findings, and other structures, were summarized and evaluated. Results:. The reticular linear vessels and red diffuse structureless areas of ETR were distinctive. For PPR, red diffuse structureless areas, reticular linear vessels, yellow scales, follicular plugs, and follicular pustules were typical dermoscopic criteria. The common dermoscopic features of PHR were: orange diffuse structureless areas, linear vessels with branches, perifollicular white color, orange focal structureless areas, and white lines. The following features statistically differed among the three rosacea subtypes: reticular linear vessels (P

BackgroundExpansion and activation of cytotoxic T lymphocytes (CTLs) in vitro represents a promising immunotherapeutic strategy, and CTLs can be primed by dendritic cells (DCs) loaded with tumor-associated antigens (TAAs) transformed by recombinant adeno-associated virus (rAAV). This study aimed to explore the impact of rAAV-DC-induced CTLs on prognosis of CRC and to explore factors associated with prognosis.MethodsThis prospective observational study included patients operated for CRC at Yan’an Hospital Affiliated to Kunming Medical University between 2016 and 2019. The primary outcome was progression-free survival (PFS), secondary outcomes were overall survival (OS) and adverse events. Totally 49 cases were included, with 29 and 20 administered rAAV-DC-induced CTL and chemotherapy, respectively.ResultsAfter 37-69 months of follow-up (median, 54 months), OS (P=0.0596) and PFS (P=0.0788) were comparable between two groups. Mild fever occurred in 2 (6.9%) patients administered CTL infusion. All the chemotherapy group experienced mild-to-moderate adverse effects, including vasculitis (n=20, 100%), vomiting (n=5, 25%), nausea (n=17, 85%) and fatigue (n=17, 85%).ConclusionsLymphatic metastasis (hazard ratio [HR]=4.498, 95% confidence interval [CI]: 1.290-15.676; P=0.018) and lower HLA-I expression (HR=0.294, 95%CI: 0.089-0.965; P=0.044) were associated with poor OS in the CTL group. CTLs induced by rAAV-DCs might achieve comparable effectiveness in CRC patients compare to chemotherapy, cases with high tumor-associated HLA-I expression and no lymphatic metastasis were more likely to benefit from CTLs.

The high-quality development of society needs the support of resource and environmental carrying capacity, and the improvement of resource and environmental carrying capacity is driven by the process of high-quality development. Therefore, how to realize the dynamic coordination of the two is an urgent problem to be solved. Different from previous studies which mainly focused on economic development and the environment, this paper considers all aspects of society and analyzes the interactive relationship between high-quality development and resource and environmental carrying capacity for the first time. Based on the panel data of 30 provinces in China from 2005 to 2020, a comprehensive evaluation index system is constructed, and the information entropy method, coupling coordination degree, and kernel density estimation model are applied to explore the coupling coordination relationship and spatial-temporal characteristics between resource and environmental carrying capacity and high-quality development. The results show that there are four nonlinear relationships between the resource and environmental carrying capacity and high-quality development, including simultaneous increase, first increase and then decrease, first decrease and then increase, and alternating fluctuation; Water resources per capita and the green coverage rate of the built-up area contributed the most to the resource and environmental carrying capacity subsystem, and GDP per capita and urbanization rate contributed the most to the high-quality development subsystem. From the time series, the coupling relationship between the two shows an upward trend over time. From the spatial series, the coupling relationship between the two is in a state of spatial aggregation. This paper discusses the results and puts forward policy recommendations, hoping to provide a reference for the coordinated development of the region. Moreover, this study provides a new perspective for the scientific construction of the relationship between resource and environmental carrying capacity and high-quality development on a global level.

IntroductionExisting multi-view-based 3D model classification methods have the problems of insufficient view refinement feature extraction and poor generalization ability of the network model, which makes it difficult to further improve the classification accuracy. To this end, this paper proposes a multi-view SoftPool attention convolutional network for 3D model classification tasks.MethodsThis method extracts multi-view features through ResNest and adaptive pooling modules, and the extracted features can better represent 3D models. Then, the results of the multi-view feature extraction processed using SoftPool are used as the Query for the self-attentive calculation, which enables the subsequent refinement extraction. We then input the attention scores calculated by Query and Key in the self-attention calculation into the mobile inverted bottleneck convolution, which effectively improves the generalization of the network model. Based on our proposed method, a compact 3D global descriptor is finally generated, achieving a high-accuracy 3D model classification performance.ResultsExperimental results showed that our method achieves 96.96% OA and 95.68% AA on ModelNet40 and 98.57% OA and 98.42% AA on ModelNet10.DiscussionCompared with a multitude of popular methods, our algorithm model achieves the state-of-the-art classification accuracy.

In order to clarify the temporal and spatial changes in the internal photothermal environment in an open-field agrivoltaic system (OAVS), this paper took the OAVS in eastern China as the research object and divided the internal area into the southern area, middle area and northern area, according to the spatial structure. Further, a photothermal environment test was conducted in the above three areas in the summer and winter. The results showed that the summer average daylight rate (Rm-avg) in the middle area was 66.6%, while the Rm-avg in the other two areas was about 20%, with no significant difference. In the winter, the light environment in the southern area was slightly better, and the Rm-avg in the above three areas was 26.4%, 24.7% and 19.7%, respectively. On the whole, the relationship between the thermal environmental factors and the solar radiation intensity was consistent. Further, a 3D model of an OAVS was established using Autodesk Ecotect Analysis 2011, and the internal light environment was simulated. Compared with the measured values, the relative error was less than 10%, which verified the reliability of the OAVS model. Then, the model was used to reveal the temporal and spatial changes in the light environment of the OAVS. The simulation results showed that the daylighting rate in the summer from the ground to the height of the fig canopy inside the system was 20.7% to 61.5%. In the winter, the daylighting rate from the ground to the height of the fig canopy inside the system was 17.7% to 36.4%. The effectiveness of the OAVS in reducing the level of solar radiation intensity depended on the time of day and the angle of the sun. At the spatial scale, due to the strong consumption of light by photovoltaic panels, there was a strong horizontal and vertical light environment gradient inside the system. In conclusion, the photothermal environment research of an OAVS based on Autodesk Ecotect Analysis 2011 can not only provide a basis for agricultural production and structural design such as span, height and the laying density of PV panels, but also expand its application to regions with different latitudes and longitudes and specific climates.

ABSTRACT The composition and function of the human gut microbiome are often associated with health and disease status. Sugar substitute sweeteners are widely used food additives, although many studies using animal models have linked sweetener consumption to gut microbial changes and health issues. Whether sugar substitute sweeteners directly change the human gut microbiome functionality remains largely unknown. In this study, we systematically investigated the responses of five human gut microbiomes to 21 common sugar substitute sweeteners, using an approach combining high-throughput in vitro microbiome culturing and metaproteomic analyses to quantify functional changes in different taxa. Hierarchical clustering based on metaproteomic responses of individual microbiomes resulted in two clusters. The noncaloric artificial sweetener (NAS) cluster was composed of NASs and two sugar alcohols with shorter carbon backbones (4 or 5 carbon atoms), and the carbohydrate (CHO) cluster was composed of the remaining sugar alcohols. The metaproteomic functional responses of the CHO cluster were clustered with those of the prebiotics fructooligosaccharides and kestose. The sugar substitute sweeteners in the CHO cluster showed the ability to modulate the metabolism of Clostridia. This study provides a comprehensive evaluation of the direct effects of commonly used sugar substitute sweeteners on the functions of the human gut microbiome using a functional metaproteomic approach, improving our understanding of the roles of sugar substitute sweeteners on microbiome-associated human health and disease issues. IMPORTANCE The human gut microbiome is closely related to human health. Sugar substitute sweeteners as commonly used food additives are increasingly consumed and have potential impacts on microbiome functionality. Although many studies have evaluated the effects of a few sweeteners on gut microbiomes using animal models, the direct effect of sugar substitute sweeteners on the human gut microbiome remains largely unknown. Our results revealed that the sweetener-induced metaproteomic responses of individual microbiomes had two major patterns, which were associated with the chemical properties of the sweeteners. This study provided a comprehensive evaluation of the effects of commonly used sugar substitute sweeteners on the human gut microbiome.

Abstract Hemorrhagic stroke (HS) is usually treated under microscopy, but recently, an increasing number of cases have been treated under neuroendoscopy. The objective of this study was to explore the feasibility and efficacy of a transcranial neuroendoscopic approach for HS. Based on etiology and clinical features, 203 HS patients were classified into two groups, with 100 patients in the primary HS (PHS) group and 103 patients in the secondary HS (SHS) group. All patients were treated either by full neuroendoscopy (FNE) or by neuroendoscopy combined with microsurgery (ECM). Outcomes were assessed according to the Glasgow Coma Scale (GCS) at discharge, and the rate of good plus excellent results was recorded as the GE rate to assess the treatment effect. All 203 patients underwent surgery successfully, with 165 patients who underwent FNE and 38 patients who underwent ECM. No patients died within 3 days after surgery, and the surgery-related mortality rate was 0%, but a total of 4 patients died by discharge, and the overall mortality rate was 1.97%. A total of 133 patients showed an excellent result and 16 showed a good result, for a total GE rate of 73%. Neuroendoscopy can provide excellent illumination, clear visualization, and multiangle views in HS. The transcranial neuroendoscopic approach is feasible and safe for both PHS and SHS and is very effective for hematoma evacuation. However, some aneurysms and most arteriovenous malformations and arteriovenous fistulas require ECM.

This paper proposes an end-to-end Learnable Edge-Attention Map (LEAM) method to assist image inpainting. To achieve a better-recovered effect, we design an edge attention module, which extracts the feature information of the edge map and re-normalizes the image feature information when automatically updating the edge map. And the information of known regions is adopted to assist the decoder generates semantically consistent results. A dual-discriminator structure consisting of the local discriminator and global discriminator is proposed to generate realistic texture details and improve the consistency of the overall structure. Experiments show that our method can obtain higher image inpainting quality than the existing state-of-the-art approaches, which improves PSNR by 3.58%, SSIM by 2.27%, and reduce MAE by 9.21% on average.

Solar-driven steam generation as a potential green technology has attracted extensive attention to solve the freshwater scarcity crisis. Photothermal materials as the key section of solar steam generation have been widely reported. However, there is still a challenge in developing easily prepared, environmental-friendly, and low-cost materials. Herein, the simple, scalable, and porous carbonized cotton was prepared as an evaporator to enhance solar-based evaporation, which has excellent light absorption ability in the range of the full spectrum (300–2,500 nm). Benefiting from 95% solar absorption and the pores between the cellulose tubes, the carbonized cotton heated by plate carbonization reaches a steam generation rate of 0.8 kg m−2 h−1, which is about 5 times that of untreated cotton. Compared with tube furnace carbonization, flat plate heating carbonization of cotton requires lower equipment requirements and does not need nitrogen protection and cleaning tar, and the photothermal conversion efficiencies of both are similar. In addition, carbonized cotton as an evaporator was heated up rapidly under 1 sun irradiation and reached a stable temperature in 20 s, greatly improving the photothermal conversion rate. Therefore, plate heating carbonized cotton provides a good idea for preparing solar photothermal conversion materials and a novel strategy for simplifying the production of biomass thermal evaporators.

The therapeutic effects and mechanism of umbilical cord mesenchymal stem cells (UC-MSC) on kidney injury in MRL/Ipr mice were studied. UC-MSC, methylprednisolone (MP), and their combination were used to treat MRL/Ipr mice. The therapeutic effects were evaluated by renal function assessment, and HE, PAS, and Masson staining were carried out on renal tissues and visualized by electron microscopy. Subsequently, podocyte injury was detected by the presence of podocin in renal tissues by immunofluorescence. To further explore the mechanism, serum TGF-β1 was measured, and TGF-β1, p-Smad3, and TRAF6 in the renal tissue were detected by Western blotting. In vitro, TGF-β1 was used to stimulate podocytes, and the podocyte activity and changes in synaptopodin were observed after UC-MSC treatment. Significant improvements in renal function and pathological injury were observed in the UC-MSC group compared to the lupus nephritis (LN) model group. UC-MSC and MP treatment improved podocyte injury in MRL/Ipr mice. Western blot examination showed a significant increase in TGF-β1, p-Smad3, and TRAF6 expression in renal tissues of the LN model group, while significant downregulation of those proteins was observed in the UC-MSC group. After TGF-β1 stimulation in vitro, podocyte activity decreased, and UC-MSC treatment improved podocyte activity and restored synaptopodin expression. UC-MSC therapy could improve the deterioration of renal function and the pathological changes of the renal tissues in MRL/Ipr mice. Our study suggested that UC-MSC may improve kidney injury and podocyte injury in LN mice by inhibiting the TGF-β1 pathway.

Based on the characteristics of information and communication technology (ICT) in China,an empirical study was made on the diffusion effect of ICT innovation using Bass extension model.The results show that the curve fitting estimation effect of genetic algorithm was remarkable.In addition,non-cumulative adopter model was used to empirically analyze the diffusion effect of ICT innovation from the aspects of technology evolution,business,region and provinces.It was concluded that innovation diffusion was significantly driven by innovation effect along with the evolution of ICT,especially 3G/4G,broadband Internet,digital TV and their convergent business.Finally,the non-cumulative Bass model using genetic algorithm were used to predict the user size of fixed-line,mobile,broad-band,radio and television in the next five years.

Background: Gallbladder cancer (GBC) is a highly lethal malignancy that carries an extremely poor prognosis due to its chemoresistant nature. Cisplatin (CDDP) is a first-line chemotherapeutic for GBC; however, patients experienced no benefit when treated with CDDP alone. The underlying mechanisms of CDDP resistance in GBC remain largely unknown. Methods: Agilent mRNA microarray analysis was performed between paired GBC and paracarcinoma to explore differentially expressed genes that might underlie drug resistance. Gene Set Enrichment Analysis (GSEA) was employed to identify key genes mediating CDDP resistance in GBC, and immunohistochemistry was performed to validate protein expression and test correlations with clinicopathological features. In vitro and in vivo functional assays were performed to investigate the proteins’ roles in CDDP resistance. Results: Olfactomedin 4 (OLFM4) was differentially expressed between GBC and paracarcinoma and had the highest rank metric score in the GSEA. OLFM4 expression was increasingly upregulated from chronic cholecystitis to GBC in clinical tissue samples, and OLFM4 depletion decreased GBC cell proliferation and invasion. Interestingly, downregulation of OLFM4 reduced ARL6IP1 (antiapoptotic factor) expression and sensitized GBC cells to CDDP both in vitro and in vivo. The evidence indicated that CDDP could significantly increase Bax and Bad expression and activate caspase-3 cascade in OLFM4-depleted GBC cells through ARL6IP1. Clinically, lower OLFM4 expression was associated with good prognosis of GBC patients. Conclusions: Our results suggest that OLFM4 is an essential gene that contributes to GBC chemoresistance and could serve as a prognostic biomarker for GBC. Importantly, OLFM4 could be a potential chemotherapeutic target.

Abstract Objectives Even though postoperative chemotherapy can eliminate residual tumor cells in patients with colorectal cancer (CRC), severe adversity, weakened immunity and drug resistance are still problems. Adjuvant cytokine‐induced killer (CIK) cell therapy is an alternative to CRC patients after surgery. The present study investigated the efficacy of adjuvant CIK cell therapy combined with chemotherapy in postoperative CRC patients. Methods This retrospective analysis included 137 postoperative CRC patients, including 71 who received adjuvant chemotherapy alone (control group) and 66 who received adjuvant immunotherapy based on CIK cells combined with chemotherapy (CIT group). Results Long‐term follow‐up study indicated that overall survival (OS) and progression‐free survival (PFS) were significantly longer in the CIT group than in the control group. Subgroup analyses showed that CIT treatment significantly improved OS and PFS of CRC patients classified as stage II and N0 stage and in patients with primary tumors in the rectum. Increasing the number of CIK infusions resulted in better prognosis. CRC patients aged

To understand the pollution characteristics of volatile organic compounds (VOCs) in the glass deep-processing industry, samples were collected using polyvinyl fluoride bags and quickly transferred to summa tanks for GC/MS/FID analysis. The emission characteristics of VOCs, the ozone formation potential and the secondary aerosol formation potential were studied. The results showed that the VOCs emitted by the six enterprises were mainly aromatics and OVOCs, accounting for 35% to 97% of the emissions, with high emission loads of alkanes and halocarbons from individual enterprises. The stack emissions from Enterprise 2 were as high as 38 mg/m3, while the emissions from the remaining five enterprises were all in the range of 1.7~4.1 mg/m3, probably because the terminal treatment facilities were not updated in a timely manner, resulting in excessive stack emissions from Enterprise 2. The characteristic pollutants, including OVOCs, aromatics and alkanes, which are mainly derived from spray painting and gluing, were screened in the six enterprises. Aromatics and OVOCs contributed the most to the ozone formation potential in the six enterprises, with some enterprises having a high contribution from alkanes and alkenes. On the basis of the secondary aerosol formation potential, toluene, benzene, ethylbenzene, o-xylene and m/p-xylene account for 98% of the six enterprises’ emissions. Glass enterprises should prioritise the control of benzene and OVOCs emissions. The glass processing industry mainly emits aromatics, OVOCs and alkanes. Through a preliminary study on the emission characteristics of VOCs in the glass deep-processing industry, we provided basic data for the reduction and control of VOCs in the glass deep-processing industry in China.

The formation energy of an oxygen vacancy and the diffusion barrier of an oxygen ion have a significant impact on the operating voltage and other parameters of resistive random access memory. In this research, n-type dopants and p-type dopants were, respectively, used to make comparative research on the formation energy of the oxygen vacancy and the diffusion barrier of the oxygen ion in orthorhombic λ-Ta2O5 taking first-principles methods. The band unfolding calculation results show that the donor level and acceptor level are, respectively, formed in the bandgap after the doping of W and Al. After the doping of Al, the formation energy of the oxygen vacancy decreases as the doping concentration increases. Instead, after the doping of W, the formation energy of the oxygen vacancy only undergoes an increase of 0.2 eV, and the diffusion barrier increases first and then decreases with the increase in the concentration of the doped W. After the doping of Al and W, the diffusion barriers of oxygen ions change within the ranges of 0.3–1.6 and 0.12–1.23 eV, respectively.

Excessive carbon emissions will cause irreversible damage to the human living environment. Therefore, carbon neutrality has become an inevitable choice for sustainable development. Marine fishery is an essential pathway for biological carbon sequestration. However, it is also a source of carbon emissions. From this perspective, an in-depth assessment of the performance of carbon emissions and sinks from marine fisheries is required to achieve the goal of carbon neutrality. This paper measured the carbon emissions, carbon sinks, and net carbon emissions of marine fisheries in nine coastal provinces of China from 2005 to 2020 for the first time. Based on the calculation results, the log-mean decomposition index method was used to analyze the driving factors of net carbon emissions. The results suggested that, from 2005 to 2020, both the carbon emissions and carbon sinks of China’s marine fisheries increased, and the net carbon emissions showed a downward trend. There were variations in the performance of carbon emissions, carbon sinks, and net carbon emissions in different provinces, and only Shandong could consistently achieve carbon neutrality. Fujian and Liaoning achieved carbon neutrality in 2020. In terms of the contribution of each factor, the industrial structure was the main positive driver, and carbon intensity was the main negative driver. Based on the empirical results, this paper suggested increasing the implementation of the carbon tax policy, establishing a farming compensation mechanism and promoting carbon emissions trading and international blue carbon trading. The results could give a reference for the energy conservation and emission reduction of marine fisheries while enhancing the ecological benefits of their carbon sinks and helping to achieve the carbon neutrality target.

In this report, we concluded there are four dermoscopic features of APD including a yellow-brown homogeneous structureless area in the center of the lesion, dotted and linear vessels distribution radially and a dam shape uplift at the periphery, as well as a white irregular ring surrounding the lesion. There are three features, including the yellow-brown homogeneous structureless area in the center of the lesion, the dotted and linear vessels distribution radially and the white irregular ring surrounding the lesion were correspond to the report of Emma Ormerod et al.These features are also similar to those previously discribed in three separated reports of seven cases with APD. In our report, we found a new dermoscopic features: the dam shape uplift at the periphery. These finding may be contributed to improve the rate of clinical diagnosis of APD.

Three-dimensional (3D) point cloud classification methods based on deep learning have good classification performance; however, they adapt poorly to diverse datasets and their classification accuracy must be improved. Therefore, FSDCNet, a neural network model based on the fusion of static and dynamic convolution, is proposed and applied for multiview 3D point cloud classification in this paper. FSDCNet devises a view selection method with fixed and random viewpoints, which effectively avoids the overfitting caused by the traditional fixed viewpoint. A local feature extraction operator of dynamic and static convolution adaptive weight fusion was designed to improve the model’s adaptability to different types of datasets. To address the problems of large parameters and high computational complexity associated with the current methods of dynamic convolution, a lightweight and adaptive dynamic convolution operator was developed. In addition, FSDCNet builds a global attention pooling, integrating the most crucial information on different view features to the greatest extent. Due to these characteristics, FSDCNet is more adaptable, can extract more fine-grained detailed information, and can improve the classification accuracy of point cloud data. The proposed method was applied to the ModelNet40 and Sydney Urban Objects datasets. In these experiments, FSDCNet outperformed its counterparts, achieving state-of-the-art point cloud classification accuracy. For the ModelNet40 dataset, the overall accuracy (OA) and average accuracy (AA) of FSDCNet in a single view reached 93.8% and 91.2%, respectively, which were superior to those values for many other methods using 6 and 12 views. FSDCNet obtained the best results for 6 and 12 views, achieving 94.6%, 93.3%, 95.3%, and 93.6% in OA and AA metrics, respectively. For the Sydney Urban Objects dataset, FSDCNet achieved an OA and F1 score of 81.2% and 80.1% in a single view, respectively, which were higher than most of the compared methods. In 6 and 12 views, FSDCNet reached an OA of 85.3% and 83.6% and an F1 score of 85.5% and 83.7%, respectively.

Diesel engine has attracted much attention because of its good power performance, fuel economy, reliability and durability, but the exhaust gas containing soot has significant impact on environment and human health. Catalyzed diesel particulate filter (CDPF) that reduces the activation energy of soot oxidation by catalysts are used to eliminate soot. In this work, MFe _2 O _4 spinel (M = Cu, Ni and Co) was synthesized by sol-gel method to catalyze the oxidation of soot. The characterization results of MFe _2 O _4 showed that CuFe _2 O _4 possessed the smallest average grain size (65.6 nm) and the best redox performance. The activity tests of the catalysts showed that the activity order of the catalyst is CuFe _2 O _4 (330 °C > CoFe _2 O _4 (411 °C > NiFe _2 O _4 (464 °C. DFT results showed that soot is more easily adsorbed on the O-terminal surface of CuFe _2 O _4 and reacts with oxygen vacancies, resulting in the promotion of soot oxidation by the diffusion of oxygen from the inside to the surface. It also proves that CuFe _2 O _4 has the best catalytic effect on soot.

The dispersion-corrected density functional theory (DFT-D) has been used to study the interactions of SO _2 on the pristine and defective single-walled MgO nanotubes (MgONTs). A geometric optimization was performed for MgONTs and adsorbents/MgONTs. The adsorption energies of SO _2 molecules at different layers of MgONTs were considered. The adsorption property of SO _2 was analyzed in terms of the adsorption energy, the electron donation (basicity), and the atomic charges on the adsorbed materials. The densities of states (DOS) have been calculated and used for examining the adsorption properties. In addition, the presence of vacancy defects increases the adsorption energies of the SO _2 molecules. The band gaps of the defective MgONTs are sensitive to SO _2 molecules.

Current research on the reconstruction of hyperspectral images from RGB images using deep learning mainly focuses on learning complex mappings through deeper and wider convolutional neural networks (CNNs). However, the reconstruction accuracy of the hyperspectral image is not high and among other issues the model for generating these images takes up too much storage space. In this study, we propose the double ghost convolution attention mechanism network (DGCAMN) framework for the reconstruction of a single RGB image to improve the accuracy of spectral reconstruction and reduce the storage occupied by the model. The proposed DGCAMN consists of a double ghost residual attention block (DGRAB) module and optimal nonlocal block (ONB). DGRAB module uses GhostNet and PRELU activation functions to reduce the calculation parameters of the data and reduce the storage size of the generative model. At the same time, the proposed double output feature Convolutional Block Attention Module (DOFCBAM) is used to capture the texture details on the feature map to maximize the content of the reconstructed hyperspectral image. In the proposed ONB, the Argmax activation function is used to obtain the region with the most abundant feature information and maximize the most useful feature parameters. This helps to improve the accuracy of spectral reconstruction. These contributions enable the DGCAMN framework to achieve the highest spectral accuracy with minimal storage consumption. The proposed method has been applied to the NTIRE 2020 dataset. Experimental results show that the proposed DGCAMN method outperforms the spectral accuracy reconstructed by advanced deep learning methods and greatly reduces storage consumption.

Solar-driven steam generation using photothermal materials is a green and promising approach to address clean water scarcity. In this work, the graphene oxide(GO) was synthesized by an improved Hummers method, and then GO was reduced by hydrothermal method and modified with nitrogen, called as NRGO. Then, we performed UV-VIS-NIR, XRD, Raman, FTIR and SEM characterization. In order to reduce the heat loss of bulk working liquid and improve the solar-to-heat conversion efficiency, the isolation system with 2D water path was used. The efficiency test of steam generation was performed under the solar intensity of 1000 Wm ^−2 for 1 h, and the photothermal conversion efficiency of reduced graphene oxide (RGO) and nitrogen-doped graphene (NRGO) was 73% and 87%, respectively. It was found that NRGO owned better solar absorption efficiency, lower thermal conductivity and porosity. NRGO was combined with insulated isolated system which can reduce the heat loss of bulk water, to improve photothermal conversion efficiency.

The connection structure in the convolutional layers of most deep learning-based algorithms used for the classification of hyperspectral images (HSIs) has typically been in the forward direction. In this study, an end-to-end alternately updated spectral−spatial convolutional network (AUSSC) with a recurrent feedback structure is used to learn refined spectral and spatial features for HSI classification. The proposed AUSSC includes alternating updated blocks in which each layer serves as both an input and an output for the other layers. The AUSSC can refine spectral and spatial features many times under fixed parameters. A center loss function is introduced as an auxiliary objective function to improve the discrimination of features acquired by the model. Additionally, the AUSSC utilizes smaller convolutional kernels than other convolutional neural network (CNN)-based methods to reduce the number of parameters and alleviate overfitting. The proposed method was implemented on four HSI data sets, as follows: Indian Pines, Kennedy Space Center, Salinas Scene, and Houston. Experimental results demonstrated that the proposed AUSSC outperformed the HSI classification accuracy obtained by state-of-the-art deep learning-based methods with a small number of training samples.

In this paper, an AlGaN/GaN Schottky barrier diode (SBD) with the T-anode located deep into the bottom buffer layer in combination with field plates (TAI-BBF FPs SBD) is proposed. The electrical characteristics of the proposed structure and the conventional AlGaN/GaN SBD with gated edge termination (GET SBD) were simulated and compared using a Technology Computer Aided Design (TCAD) tool. The results proved that the breakdown voltage (VBK) in the proposed structure was tremendously improved when compared to the GET SBD. This enhancement is attributed to the suppression of the anode tunneling current by the T-anode and the redistribution of the electric field in the anode⁻cathode region induced by the field plates (FPs). Moreover, the T-anode had a negligible effect on the two-dimensional electron gas (2DEG) in the channel layer, so there is no deterioration in the forward characteristics. After being optimized, the proposed structure exhibited a low turn-on voltage (VT) of 0.53 V and a specific on-resistance (RON,sp) of 0.32 mΩ·cm2, which was similar to the GET SBD. Meanwhile, the TAI-BBF FP SBD with an anode-cathode spacing of 5 μm achieved a VBK of 1252 V, which was enhanced almost six times compared to the GET SBD with a VBK of 213 V.

In this paper, an edge termination structure, referred to as step-double-zone junction termination extension (Step-DZ-JTE), is proposed. Step-DZ-JTE further improves the distribution of the electric field (EF) by its own step shape. Step-DZ-JTE and other termination structures are investigated for comparison using numerical simulations. Step-DZ-JTE greatly reduces the sensitivity of breakdown voltage (BV) and surface charges (SC). For a 30-μm thick epi-layer, the optimized Step-DZ-JTE shows 90% of the theoretical BV with a wide tolerance of 12.2 × 1012 cm−2 to the JTE dose and 85% of the theoretical BV with an improved tolerance of 3.7 × 1012 cm−2 to the positive SC are obtained. Furthermore, when combined with the field plate technique, the performance of the Step-DZ-JTE is further improved.

Recent research shows that deep-learning-derived methods based on a deep convolutional neural network have high accuracy when applied to hyperspectral image (HSI) classification, but long training times. To reduce the training time and improve accuracy, in this paper we propose an end-to-end fast dense spectral–spatial convolution (FDSSC) framework for HSI classification. The FDSSC framework uses different convolutional kernel sizes to extract spectral and spatial features separately, and the “valid” convolution method to reduce the high dimensions. Densely-connected structures—the input of each convolution consisting of the output of all previous convolution layers—was used for deep learning of features, leading to extremely accurate classification. To increase speed and prevent overfitting, the FDSSC framework uses a dynamic learning rate, parametric rectified linear units, batch normalization, and dropout layers. These attributes enable the FDSSC framework to achieve accuracy within as few as 80 epochs. The experimental results show that with the Indian Pines, Kennedy Space Center, and University of Pavia datasets, the proposed FDSSC framework achieved state-of-the-art performance compared with existing deep-learning-based methods while significantly reducing the training time.

Runt-related transcription factor 3 (RUNX3) is a member of the runt-domain family of transcription factors. Emerging evidence indicates that RUNX3 is a tumor suppressor gene in several types of human cancers including esophageal cancer. However, the association between RUNX3 promoter methylation and esophageal cancer remains unclear. Here we conducted a systematic review and meta-analysis to quantitatively evaluate the effects of RUNX3 promoter methylation on the incidence of esophageal cancer.A detailed literature search was made on Medline, Pubmed and Web of Science for related research publications written in English and/or Chinese. Methodological quality of the studies was also evaluated. The data were extracted and assessed by two reviewers independently. Analysis of pooled data were performed, the odds ratios (OR) were calculated and summarized respectively.Final analysis of 558 patients from 9 eligible studies was performed. The result showed that RUNX3 methylation was significantly higher in esophageal cancer than in normal squamous mucosa from the proximal resection margin or esophageal benign lesions (OR = 2.85, CI = 2.01-4.05, P

Keloid is benign fibroproliferative dermal tumors with unknown etiology. Recently, a genome-wide association study (GWAS) in Japanese population has identified 3 susceptibility loci (rs873549 at 1q41, rs940187 and rs1511412 at 3q22.3, rs8032158 at 15p21.3) for keloid. In order to examine whether these susceptibility loci are associated with keloid in the Chinese Han population, twelve previously reported SNPs were selected for replication in 714 cases and 2,944 controls by using Sequenom MassArray system. We found three SNPs in two regions showed significant association with keloid in the Chinese Han population: 1q41 (rs873549, P = 3.03×10(-33), OR = 2.05, 95% CI: 1.82-2.31 and rs1442440, P = 9.85×10(-18), OR = 0.56, 95% CI: 0.49-0.64, respectively) and 15q21.3 (rs2271289 located in NEDD4, P = 1.02×10(-11), OR = 0.66, 95% CI: 0.58-0.74). We also detected one risk haplotype AG (P = 1.36×10(-31), OR = 2.02) and two protective haplotypes of GA and AA (GA, P = 1.94×10(-19), OR = 0.53, AA, P = 0.00043, OR = 0.78, respectively) from the two SNPs (rs873549 and rs1442440). Our study confirmed two previously reported loci 1q41 and 15q21.3 for keloid in the Chinese Han population, which suggested the common genetic factor predisposing to the development of keloid shared by the Chinese Han and Japanese populations.

hUC-MSCs hold great promise in vitro neuronal differentiation and therapy for neurodegenerative disorders including Parkinson's disease. Recent studies provided that Lmx1α play an important role in the midbrain dopamine cells differentiation. Neurturin is desired candidate gene for providing a neuroprotective to DA neurons. In this study, we investigated a novel neuronal differentiation strategy in vitro with Lmx1α and NTN. We transferred these two genes to hUC-MSCs by recombinant adenovirus combined with Lmx1α regulatory factor and other inductor to improve the efficiency of inducing. Then those induced cells were implanted into the striatum and substantia nigra of MPTP lesioned hemi-parkinsonian rhesus monkeys. Monkeys were monitored by using behavioral test for six months after implantation. The result showed that cells isolated from the umbilical cord were negative for CD45, CD34 and HLA-DR, but were positive for CD44, CD49d, CD29. After those cells were infected with recombinant adenovirus, RT-PCR result shows that both Lmx1α and NTN genes were transcribed in hUC-MSCs. We also observed that the exogenous were highly expressed in hUC-MSCs from immunofluorescence and western blot. Experiments in vitro have proved that secretion NTN could maintain the survival of rat fetal midbrain dopaminergic neurons. After hUC-MSCs were induced with endogenous and exogenous factors, the mature neurons specific gene TH, Pitx3 was transcripted and the neurons specific protein TH, β-tubulinIII, NSE, Nestin, MAP-2 was expressed in those differentiated cells. In addition, the PD monkeys, transplanted with the induced cells demonstrated the animals' symptoms amelioration by the behavioral measures. Further more, pathological and immunohistochemistry data showed that there were neuronal-like cells survived in the right brain of those PD monkeys, which may play a role as dopaminergic neurons. The findings from this study may help us to better understand the inside mechanisms of PD pathogenesis and may also help developing effective therapy for Parkinson's disease.

The title compound, [MoF2O2(C12H8N2)], has non-crystallographic mirror symmetry. The MoVI atom shows a distorted octahedral environment, with the phenanthroline N atoms and the two oxide groups forming the equatorial plane and the F atoms occupying the apical positions. Weak C—H...O and C—H...F hydrogen-bonding contacts and π–π interactions [centroid–centroid distance = 3.662 (1) Å] connect the complex molecules into a three-dimensional supramolecular framework.