Magnetic nanoparticles(NPs) are characterized by a rich variety of properties. Because of their excellent physical and chemical properties, they have come to the fore in biomedicine and other fields. ...The magnetic NPs were extensively studied in magnetic separation of cells, targeted drug delivery, tumor hyperthermia, chemo-photothermal therapy, magnetic resonance imaging (MRI) and other biomedical fields. Magnetic NPs are increasingly used in magnetic resonance imaging (MRI) based on their inherent magnetic targeting, superparamagnetic enzyme-like catalytic properties and nanoscale size. Poly(lactic-co-glycolic acid) (PLGA) is a promising biodegradable material approved by FDA and EU for drug delivery. Currently, PLGA-based magnetic nano-drug delivery systems have attracted the attention of researchers. Herein, we achieved the effective encapsulation of sized-controlled polyethylene glycol-3,4-dihydroxy benzyl-amine-coated superparamagnetic iron oxide nanoparticles (SPIO NPs) and euphorbiasteroid into PLGA nanospheres via a modified multiple emulsion solvent evaporation method (W1/O2/W2). NPs with narrow size distribution and acceptable magnetic properties were developed that are very useful for applications involving cancer therapy and MRI. Furthermore, SPIO-PLGA NPs enhanced the MRI T2 relaxation properties of tumor sites.The prepared SPIO NPs and magnetic PLGA nanospheres can be promising magnetic drug delivery systems for tumor theranostics. This study has successfully constructed a tumor-targeting and magnetic-targeting smart nanocarrier with enhanced permeability and retention, multimodal anti-cancer therapeutics and biodegradability, which could be a hopeful candidate for anti-tumor therapy in the future.
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•For the first time, the lipid-soluble drug EFL1 and the water-soluble magnetic nanomaterials are co-loaded into the PLGA.•Based on the research idea of "theranostics" realize targeted treatment under the dual guidance of magnetism and biology.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The ketogenic diet (KD), which can induce changes in gut microbiota, has shown benefits for epilepsy and several neurodegenerative diseases. However, the effects of a KD on glucose and lipid ...metabolism remain inconclusive. Using two formulas of ketogenic diets (KDR with 89.5% fat and KDH with 91.3% fat), which are commonly used in mouse trials, we found that KDR but not KDH induced insulin resistance and damaged glucose homeostasis, while KDH induced more fat accumulation in mice. Further study showed that KD impacted glucose metabolism, which was related to the sources of fat, while both the sources and proportions of fat affected lipid metabolism. And the KD widely used in human studies still induced insulin resistance and fat accumulation in mice. Moreover, KDs changed the gut microbiota and metabolites in mice, and the sources and proportions of fat in the diets respectively changed the abundance of specific bacteria and metabolites which were correlated with parameters related to glucose intolerance and lipid accumulation. Overall, our study demonstrated that the metabolic disorders induced by KDs are closely related to the source and proportion of fat in the diet, which may be associated with the changes of the gut microbiota and metabolites.
The ketogenic diet with extremely high fat and very low carbohydrate levels is very popular in society today. Although it has beneficial effects on epilepsy and neurodegenerative diseases, how ketogenic diets impact host glucose and lipid metabolism and gut microbiota still needs further investigation. Here, we surveyed the effects of two ketogenic diets which are commonly used in mouse trials on metabolic phenotypes, gut microbiota, and metabolites in mice. We found that both ketogenic diets impaired glucose and lipid metabolism in mice, and this may be due to the sources and proportions of fat in the diets. This work highlights the potential risk of glucose and lipid metabolism disorders and the importance of evaluating the sources and proportions of fat in the diets, when using ketogenic diets for weight loss and the treatment of diseases.
Vibrio parahaemolyticus is the predominant etiological agent of seafood-associated foodborne illnesses on a global scale. It is essential to elucidate the mechanisms by which this pathogen ...disseminates. Given the existing research predominantly concentrates on localized outbreaks, there is a pressing necessity for a comprehensive investigation to capture strains of V. parahaemolyticus cross borders.
This study examined the frequency and genetic attributes of imported V. parahaemolyticus strains among travelers entering Shanghai Port, China, between 2017 and 2019.Through the collection of 21 strains from diverse countries and regions, Southeast Asia was pinpointed as a significant source for the emergence of V. parahaemolyticus. Phylogenetic analysis revealed clear delineation between strains originating from human and environmental sources, emphasizing that underlying genome data of foodborne pathogens is essential for environmental monitoring, food safety and early diagnosis of diseases. Furthermore, our study identified the presence of virulence genes (tdh and tlh) and approximately 120 antibiotic resistance-related genes in the majority of isolates, highlighting their crucial involvement in the pathogenesis of V. parahaemolyticus.
This research enhanced our comprehension of the worldwide transmission of V. parahaemolyticus and its antimicrobial resistance patterns. The findings have important implications for public health interventions and antimicrobial stewardship strategies, underscoring the necessity for epidemiological surveillance of pathogen at international travel hubs.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Enterprises are facing both new opportunities and severe challenges in a complex market environment. Improving forecast accuracy is key to improving your bottom line. This paper takes the practice ...process of Lenovo Group as a case study to explore the construction mechanism of enterprise forecasting ability. This paper finds the establishment of database management, the adoption of general forecasting methods, and the application of multi-level demand collaborative forecasting technology. All of them are conducive to reducing the forecast error rate. This paper analyzes Lenovo Group's efforts to improve the problems of data islands and data breakpoints in the past. It innovates some ways and methods. Not only provides a reference for other enterprises to improve but also reduces the bullwhip effect. They are making the resource utilization of the supply chain more sufficient, and being more conducive to the sustainable development of the supply chain. The research conclusions of this paper have certain references and enlightenments for enterprises to improve the accuracy of forecasting.
Quantifying free-form surfaces using differential confocal microscopy can be challenging, as it requires balancing accuracy and efficiency. When the axial scanning mechanism involves sloshing and the ...measured surface has a finite slope, traditional linear fitting can introduce significant errors. This study introduces a compensation strategy based on Pearson's correlation coefficient to effectively reduce measurement errors. Additionally, a fast-matching algorithm based on peak clustering was proposed to meet real-time requirements for non-contact probes. To validate the effectiveness of the compensation strategy and matching algorithm, detailed simulations and physical experiments were conducted. The results showed that for a numerical aperture of 0.4 and a depth of slope < 12°, the measurement error was <10 nm, improving the speed of the traditional algorithm system by 83.37%. Furthermore, repeatability and anti-disturbance experiments demonstrated that the proposed compensation strategy is simple, efficient, and robust. Overall, the proposed method has significant potential for application in the realization of high-speed measurements of free-form surfaces.
Background The majority of lung cancer(LC) patients are diagnosed at advanced stage with a poor prognosis. However, there is still no ideal diagnostic and prognostic prediction model for lung cancer. ...Methods Data of CEA, CYFRA21-1 and NSE test of patients with LC and benign lung diseases (BLDs) or healthy people from Physical Examination Center was collected. Samples were divided into three data sets as needed. Reassign three kinds of tumor markers (TMs) according to their distribution characteristics in different populations. Diagnostic and prognostic models were thus established, and independent validation was conducted with other data sets. Results The diagnostic prediction model showed good discrimination ability: the area under the receiver operating characteristic curve (AUC) differentiated LC from healthy people and BLDs (diagnosed within 2 months), being 0.88 and 0.84 respectively. Meanwhile, the prognostic prediction model did great in prediction: AUC in training data set and test data set were 0.85 and 0.8 respectively. Conclusion Reassigned CEA, CYFRA21-1 and NSE can effectively predict the diagnosis and prognosis of LC. Compared with the same TMs that were considered individually, this diagnostic prediction model can identify high-risk population for LC screening more accurately. The prognostic prediction model could be helpful in making more scientific treatment and follow-up plans for patients. Keywords: Lung cancer, CEA, CYFRA21-1, NSE, Screening, Prognosis
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Advances in machine learning technology have made efficient image denoising possible. In this paper, we propose a new ridgelet support vector machine (RSVM) for image noise reduction. Multiscale ...ridgelet support vector filter (MRSVF) is first deduced from RSVM, to produce a multiscale, multidirection, undecimated, dyadic, aliasing, and shift-invariant geometric multiscale ridgelet support vector transform (GMRSVT). Then, multiscale dictionaries are learned from examples to reduce noises existed in GMRSVT coefficients. Compared with the available approaches, the proposed method has the following characteristics. The proposed MRSVF can extract the salient features associated with the linear singularities of images. Consequently, GMRSVT can well approximate edges, contours and textures in images, and avoid ringing effects suffered from sampling in the multiscale decomposition of images. Sparse coding is explored for noise reduction via the learned multiscale and overcomplete dictionaries. Some experiments are taken on natural images, and the results show the efficiency of the proposed method.
Highlights • Pharmacist-driven antimicrobial stewardship was a protect factor for mortality. • The strategy had a lower rate of the emergence of multidrug-resistant organisms. • The strategy ...optimised antimicrobial use in ICUs in China. • The strategy need a large-scale implementation in ICUs in China.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Gene therapy has become an essential treatment for optic nerve injury (ONI) in recent years, and great strides have been made using animal models. ONI, which is characterized by the loss of retinal ...ganglion cells (RGCs) and axons, can induce abnormalities in the pupil light reflex, visual field defects, and even vision loss. The eye is a natural organ to target with gene therapy because of its high accessibility and certain immune privilege. As such, numerous gene therapy trials are underway for treating eye diseases such as glaucoma. The aim of this review was to cover research progress made in gene therapy for ONI. Specifically, we focus on the potential of gene therapy to prevent the progression of neurodegenerative diseases and protect both RGCs and axons. We cover the basic information of gene therapy, including the classification of gene therapy, especially focusing on genome editing therapy, and then we introduce common editing tools and vector tools such as Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) -Cas9 and adeno-associated virus (AAV). We also summarize the progress made on understanding the roles of brain derived neurotrophic factor (BDNF), ciliary neurotrophic factor (CNTF), phosphatase-tensin homolog (PTEN), suppressor of cytokine signal transduction 3 (SOCS3), histone acetyltransferases (HATs), and other important molecules in optic nerve protection. However, gene therapy still has many challenges, such as misalignment and mutations, immunogenicity of AAV, time it takes and economic cost involved, which means that these issues need to be addressed before clinical trials can be considered.
The Air-conditioning System (ACS), used in office buildings in the hot summer and cold winter zone of China, are always operate intermittently. The dynamic thermal behaviors of building walls with ...real climate conditions may be different from those with only the representative day’s climate conditions, due to the time varying nature of the climate, which will lead to the variation of the ACS loads. A numerical calculation was performed to analyze the effects of insulation form on heat behavior of external walls and ACS loads. The results indicate that cooling transmission load with inside insulation reaches its maximum value when the solar-air temperature in daytime is the highest, while that with outside insulation occurs at the time when the air temperature at night is the highest during summer. Heating transmission load for the wall with external and internal insulation both peaks in the day with lowest mean outdoor temperature during the last non-working period. Inside insulation can be considered a better way to reduce the peak load, peak-valley load difference and energy consumption.
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