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Abstract Background Numerous studies indicate that visceral adipose tissue (VAT) significantly contribute to metabolic syndrome (MetS) development. This study aims to assess the distinguishing value of novel obesity markers, specifically lipid accumulation products (LAP) and cardiometabolic index (CMI), in relation to MetS. Considering the gender disparity in MetS prevalence, it is essential to explore whether LAP and CMI exhibit differential distinguishing capabilities by gender. Method The investigation included a total of 11,687 qualified individuals who participated in the NHANES survey spanning a 14-year period from 2005 to 2018. Biochemical analysis of blood and body measurements were utilized to determine LAP and CMI values for each participant. Inclusion of gender as a variable was a key factor in the examination of all data. Restricted cube plots (RCS) were utilized to analyze the strength of the relationship between LAP, CMI, and MetS. The study delved into potential connections between LAP and CMI with MetS, all-cause and cardiovascular mortality using various statistical models such as multivariate logistic regression and Cox regression. Results The findings revealed a significant nonlinear association between CMI, LAP, and MetS (P-non-linear 0.005) MetS. Impressively, LAP and CMI were identified as the primary predictors of MetS in both genders from AUC (P

Abstract Background The occurrence, development, and outbreak of tea diseases and pests pose a significant challenge to the quality and yield of tea, necessitating prompt identification and control measures. Given the vast array of tea diseases and pests, coupled with the intricacies of the tea planting environment, accurate and rapid diagnosis remains elusive. In addressing this issue, the present study investigates the utilization of transfer learning convolution neural networks for the identification of tea diseases and pests. Our objective is to facilitate the accurate and expeditious detection of diseases and pests affecting the Yunnan Big leaf kind of tea within its complex ecological niche. Results Initially, we gathered 1878 image data encompassing 10 prevalent types of tea diseases and pests from complex environments within tea plantations, compiling a comprehensive dataset. Additionally, we employed data augmentation techniques to enrich the sample diversity. Leveraging the ImageNet pre-trained model, we conducted a comprehensive evaluation and identified the Xception architecture as the most effective model. Notably, the integration of an attention mechanism within the Xeption model did not yield improvements in recognition performance. Subsequently, through transfer learning and the freezing core strategy, we achieved a test accuracy rate of 98.58% and a verification accuracy rate of 98.2310%. Conclusions These outcomes signify a significant stride towards accurate and timely detection, holding promise for enhancing the sustainability and productivity of Yunnan tea. Our findings provide a theoretical foundation and technical guidance for the development of online detection technologies for tea diseases and pests in Yunnan.

Abstract Pleckstrin homology domain-containing family M member 2 (PLEKHM2) is an essential adaptor for lysosomal trafficking and its homozygous truncation have been reported to cause early onset dilated cardiomyopathy (DCM). However, the molecular mechanism of PLEKHM2 deficiency in DCM pathogenesis and progression is poorly understood. Here, we generated an in vitro model of PLEKHM2 knockout (KO) induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) to elucidate the potential pathogenic mechanism of PLEKHM2-deficient cardiomyopathy. PLEKHM2-KO hiPSC-CMs developed disease phenotypes with reduced contractility and impaired calcium handling. Subsequent RNA sequencing (RNA-seq) analysis revealed altered expression of genes involved in mitochondrial function, autophagy and apoptosis in PLEKHM2-KO hiPSC-CMs. Further molecular experiments confirmed PLEKHM2 deficiency impaired autophagy and resulted in accumulation of damaged mitochondria, which triggered increased reactive oxygen species (ROS) levels and decreased mitochondrial membrane potential (Δψm). Importantly, the elevated ROS levels caused oxidative stress-induced damage to nearby healthy mitochondria, resulting in extensive Δψm destabilization, and ultimately leading to impaired mitochondrial function and myocardial contractility. Moreover, ROS inhibition attenuated oxidative stress-induced mitochondrial damage, thereby partially rescued PLEKHM2 deficiency-induced disease phenotypes. Remarkably, PLEKHM2-WT overexpression restored autophagic flux and rescued mitochondrial function and myocardial contractility in PLEKHM2-KO hiPSC-CMs. Taken together, these results suggested that impaired mitochondrial clearance and increased ROS levels play important roles in PLEKHM2-deficient cardiomyopathy, and PLEKHM2-WT overexpression can improve mitochondrial function and rescue PLEKHM2-deficient cardiomyopathy.

Abstract Early and accurate diagnosis of focal liver lesions is crucial for effective treatment and prognosis. We developed and validated a fully automated diagnostic system named Liver Artificial Intelligence Diagnosis System (LiAIDS) based on a diverse sample of 12,610 patients from 18 hospitals, both retrospectively and prospectively. In this study, LiAIDS achieved an F1-score of 0.940 for benign and 0.692 for malignant lesions, outperforming junior radiologists (benign: 0.830-0.890, malignant: 0.230-0.360) and being on par with senior radiologists (benign: 0.920-0.950, malignant: 0.550-0.650). Furthermore, with the assistance of LiAIDS, the diagnostic accuracy of all radiologists improved. For benign and malignant lesions, junior radiologists’ F1-scores improved to 0.936-0.946 and 0.667-0.680 respectively, while seniors improved to 0.950-0.961 and 0.679-0.753. Additionally, in a triage study of 13,192 consecutive patients, LiAIDS automatically classified 76.46% of patients as low risk with a high NPV of 99.0%. The evidence suggests that LiAIDS can serve as a routine diagnostic tool and enhance the diagnostic capabilities of radiologists for liver lesions.

The precise identification of disease traits in the complex sugarcane planting environment not only effectively prevents the spread and outbreak of common diseases but also allows for the real-time monitoring of nutrient deficiency syndrome at the top of sugarcane, facilitating the supplementation of relevant nutrients to ensure sugarcane quality and yield. This paper proposes a human–machine collaborative sugarcane disease detection method in complex environments. Initially, data on five common sugarcane diseases—brown stripe, rust, ring spot, brown spot, and red rot—as well as two nutrient deficiency conditions—sulfur deficiency and phosphorus deficiency—were collected, totaling 11,364 images and 10 high-definition videos captured by a 4K drone. The data sets were augmented threefold using techniques such as flipping and gamma adjustment to construct a disease data set. Building upon the YOLOv8 framework, the EMA attention mechanism and Focal loss function were added to optimize the model, addressing the complex backgrounds and imbalanced positive and negative samples present in the sugarcane data set. Disease detection models EF-yolov8s, EF-yolov8m, EF-yolov8n, EF-yolov7, and EF-yolov5n were constructed and compared. Subsequently, five basic instance segmentation models of YOLOv8 were used for comparative analysis, validated using nutrient deficiency condition videos, and a human–machine integrated detection model for nutrient deficiency symptoms at the top of sugarcane was constructed. The experimental results demonstrate that our improved EF-yolov8s model outperforms other models, achieving mAP_0.5, precision, recall, and F1 scores of 89.70%, 88.70%, 86.00%, and 88.00%, respectively, highlighting the effectiveness of EF-yolov8s for sugarcane disease detection. Additionally, yolov8s-seg achieves an average precision of 80.30% with a smaller number of parameters, outperforming other models by 5.2%, 1.9%, 2.02%, and 0.92% in terms of mAP_0.5, respectively, effectively detecting nutrient deficiency symptoms and addressing the challenges of sugarcane growth monitoring and disease detection in complex environments using computer vision technology.

Background and objective Lung cancer is one of the most common malignant tumors in the world, and the current lung cancer screening and treatment strategies are constantly improving, but its 5-year survival rate is still very low, which seriously endangers human health. Therefore, it is critical to explore new biomarkers to provide personalized treatment and improve the prognosis. Cuproptosis is a newly discovered type of cell death, which is due to the accumulation of excess copper ions in the cell, eventually leading to cell death, which has been suggested by studies to be closely related to the occurrence and development of lung adenocarcinoma (LUAD). Based on The Cancer Genome Atlas (TCGA) database, this study explored the association between cuproptosis-related genes (CRGs) and LUAD prognosis, established a prognostic risk model, and analyzed the interaction between CRGs and LUAD immune cell infiltration. Methods The RNA-seq data of LUAD tissue and paracancerous or normal lung tissue were downloaded from the TCGA database; the RNA-seq data of normal lung tissue was downloaded from the Genotype-tissue Expression (GTEx) database, and the data of 462 lung adenocarcinoma cases were downloaded from the Gene Expression Omnibus repository (GEO) as verification. T the risk score model to assess prognosis was constructed by univariate Cox and Lasso-Cox regression analysis, and the predictive ability of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve. Immune-related and drug susceptibility analysis was further performed on high- and low-risk groups. Results A total of 1656 CRGs and 1356 differentially expressed CRGs were obtained, and 13 CRGs were screened out based on univariate Cox and Lasso-Cox regression analysis to construct a prognostic risk model, and the area under the curves (AUCs) of ROC curves 1-, 3- and 5- year were 0.749, 0.740 and 0.689, respectively. Further study of immune-related functions and immune checkpoint differential analysis between high- and low-risk groups was done. High-risk groups were more sensitive to drugs such as Savolitinib, Palbociclib, and Cytarabine and were more likely to benefit from immunotherapy. Conclusion The risk model constructed based on 13 CRGs has good prognostic value, which can assist LUAD patients in individualized treatment, and provides an important theoretical basis for the treatment and prognosis of LUAD.

BackgroundThe novel International Association for the Study of Lung Cancer (IASLC) grading system suggests that poorly differentiated invasive pulmonary adenocarcinoma (IPA) has a worse prognosis. Therefore, prediction of poorly differentiated IPA before treatment can provide an essential reference for therapeutic modality and personalized follow-up strategy. This study intended to train a nomogram based on CT intratumoral and peritumoral radiomics features combined with clinical semantic features, which predicted poorly differentiated IPA and was tested in independent data cohorts regarding models’ generalization ability.MethodsWe retrospectively recruited 480 patients with IPA appearing as subsolid or solid lesions, confirmed by surgical pathology from two medical centers and collected their CT images and clinical information. Patients from the first center (n =363) were randomly assigned to the development cohort (n = 254) and internal testing cohort (n = 109) in a 7:3 ratio; patients (n = 117) from the second center served as the external testing cohort. Feature selection was performed by univariate analysis, multivariate analysis, Spearman correlation analysis, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the model performance.ResultsThe AUCs of the combined model based on intratumoral and peritumoral radiomics signatures in internal testing cohort and external testing cohort were 0.906 and 0.886, respectively. The AUCs of the nomogram that integrated clinical semantic features and combined radiomics signatures in internal testing cohort and external testing cohort were 0.921 and 0.887, respectively. The Delong test showed that the AUCs of the nomogram were significantly higher than that of the clinical semantic model in both the internal testing cohort(0.921 vs 0.789, p< 0.05) and external testing cohort(0.887 vs 0.829, p< 0.05).ConclusionThe nomogram based on CT intratumoral and peritumoral radiomics signatures with clinical semantic features has the potential to predict poorly differentiated IPA manifesting as subsolid or solid lesions preoperatively.

Pest target identification in agricultural production environments is challenging due to the dense distribution, small size, and high density of pests. Additionally, changeable environmental lighting and complex backgrounds further complicate the detection process. This study focuses on enhancing the recognition performance of tea pests by introducing a lightweight pest image recognition model based on the improved YOLOv8 architecture. First, slicing-aided fine-tuning and slicing-aided hyper inference (SAHI) are proposed to partition input images for enhanced model performance on low-resolution images and small-target detection. Then, based on an ELAN, a generalized efficient layer aggregation network (GELAN) is designed to replace the C2f module in the backbone network, enhance its feature extraction ability, and construct a lightweight model. Additionally, the MS structure is integrated into the neck network of YOLOv8 for feature fusion, enhancing the extraction of fine-grained and coarse-grained semantic information. Furthermore, the BiFormer attention mechanism, based on the Transformer architecture, is introduced to amplify target characteristics of tea pests. Finally, the inner-MPDIoU, based on auxiliary borders, is utilized as a replacement for the original loss function to enhance its learning capacity for complex pest samples. Our experimental results demonstrate that the enhanced YOLOv8 model achieves a precision of 96.32% and a recall of 97.95%, surpassing those of the original YOLOv8 model. Moreover, it attains an mAP@50 score of 98.17%. Compared to Faster R-CNN, SSD, YOLOv5, YOLOv7, and YOLOv8, its average accuracy is 17.04, 11.23, 5.78, 3.75, and 2.71 percentage points higher, respectively. The overall performance of YOLOv8 outperforms that of current mainstream detection models, with a detection speed of 95 FPS. This model effectively balances lightweight design with high accuracy and speed in detecting small targets such as tea pests. It can serve as a valuable reference for the identification and classification of various insect pests in tea gardens within complex production environments, effectively addressing practical application needs and offering guidance for the future monitoring and scientific control of tea insect pests.

The mechanical incompatibilities between ferrite and martensite at the cladding interface of stainless steel (SS)/carbon steel (CS) clad plates can result in stress concentration and interface cracks. In this paper, 304 SS/Q235 CS clad plates were prepared by liquid-solid (L-S) composite casting, and the mechanical incompatibilities between ferrite and martensite reduced by constructing gradient carbides in the interfacial ferrite. The precipitation behavior of the gradient carbides was analyzed, and the strengthening mechanism was revealed. The ultimate strength of the SS/CS clad plates was 370 MPa when stretched perpendicular to the cladding interface, and the SS/CS clad plates fractured in the CS that was far from the cladding interface. The interfacial microstructures from the CS to the SS were ferrite, M7C3 carbides, and lath martensite, and the carbides content gradually decreased toward the CS. During the L-S composite process, a micro-melting region with decreased volume fraction of interdendritic liquid to the CS formed at the cladding interface. The C, Cr, and Ni mixed and diffused in the interdendritic liquid, and the gradient distribution of elements resulted in the precipitation of coherent M7C3 carbides whose volume fraction decreased toward the CS. The coherent strengthening and precipitation strengthening of carbides strengthened the interfacial ferrite and resulted in a gradient strengthening, which reduced the mechanical incompatibilities between ferrite and martensite at the cladding interface. Additionally, the gradient carbides changed the stress state at the cladding interface and improved the interfacial bonding strength.

Using poly(acrylic acid) (abbreviated as PAA) as a shell, bimodal mesoporous silicas (abbreviated as BMMs) as a core, and bipyridine-proline (abbreviated as Z) as an active species, a facile approach for preparation of the P-Z@BMMs nanocomposites with core–shell structure was proposed, which was used as a suitable pH-sensitive catalyst for asymmetric aldol reaction between p-nitrobenzaldehyde and cyclohexanone. Their microstructural features and physicochemical properties were extensively characterized by various methods, such as powder X-ray diffraction patterns, N2 adsorption–desorption isotherms, the scanning (and transmission) electron microscopy images, the dynamic light scattering measurements, the thermogravimetric analysis, the elemental analysis, and the Fourier transform infrared spectroscopy spectra. Particularly, their fractal evolution, the pair distance distribution function, and the Porod plots were demonstrated via the small-angle X-ray scattering patterns. The results elucidated that the PAA was successfully incorporated onto the external amino-modified surfaces of the mesoporous BMMs, and the particles having PAA grafted thereon had a pH-responsive shell in thickness of around 0.97 nm for controlled release of Z species by adjusting pH value of the reaction medium. Besides, the synthesized P-Z@BMMs presented the satisfactory catalytic yields (around 80%) in comparison with the homo- and heterogeneous catalytic system using Z or Z@BMMs as the catalysts.

Interfacial performance of stainless steel/carbon steel (SS/CS) laminated composite is crucial for further manufacturing and application. Here, we reported a new strategy for fabricating the SS/CS laminated composites that composed of heterogeneous lamella structure at the cladding interface zone, by employing liquid–solid bonding and subsequent hot rolling. Different rolling temperatures were applied for comparison of the formation of heterogeneous lamella structure and their influences on the mechanical properties of the cladding interface, and the mechanisms of enhanced interfacial shear strength and ductility by the heterogenous lamella structure were discussed. A metallurgical bonding interface with intensive elements diffusion was obtained by liquid–solid bonding method, and coarse equiaxed grains and a wider decarburized layer formed at the cladding interface zone. Under rolling temperature of 900 °C, the mechanical incompatibilities of cladding interface zone and lower temperature resulted in heterodeformation and inefficient driving force of recrystallization, resulting in a heterogenous lamella structure consisted of hardened austenite region, coarse-grained ferrite region and fine-grained pearlite and ferrite region at the cladding interface zone of SS/CS laminated composite, which obviously improved the interfacial shear strength and ductility of the SS/CS laminated composites due to back stress strengthening and hardening.

Airway mucus dysfunction and impaired immunological defenses are hallmarks of several lung diseases, including asthma, cystic fibrosis, and chronic obstructive pulmonary diseases, and are mostly causative factors in bacterial-biofilm-associated respiratory tract infections. Bacteria residing within the biofilm architecture pose a complex challenge in clinical settings due to their increased tolerance to currently available antibiotics and host immune responses, resulting in chronic infections with high recalcitrance and high rates of morbidity and mortality. To address these unmet clinical needs, potential anti-biofilm therapeutic strategies are being developed to effectively control bacterial biofilm. This review focuses on recent advances in the development and application of nanoparticulate drug delivery systems for the treatment of biofilm-associated respiratory tract infections, especially addressing the respiratory barriers of concern for biofilm accessibility and the various types of nanoparticles used to combat biofilms. Understanding the obstacles facing pulmonary drug delivery to bacterial biofilms and nanoparticle-based approaches to combatting biofilm may encourage researchers to explore promising treatment modalities for bacterial-biofilm-associated chronic lung infections.

BackgroundThis study aimed to establish an effective model for preoperative prediction of tumor deposits (TDs) in patients with rectal cancer (RC). MethodsIn 500 patients, radiomic features were extracted from magnetic resonance imaging (MRI) using modalities such as high-resolution T2-weighted (HRT2) imaging and diffusion-weighted imaging (DWI). Machine learning (ML)-based and deep learning (DL)-based radiomic models were developed and integrated with clinical characteristics for TD prediction. The performance of the models was assessed using the area under the curve (AUC) over five-fold cross-validation.ResultsA total of 564 radiomic features that quantified the intensity, shape, orientation, and texture of the tumor were extracted for each patient. The HRT2-ML, DWI-ML, Merged-ML, HRT2-DL, DWI-DL, and Merged-DL models demonstrated AUCs of 0.62 ± 0.02, 0.64 ± 0.08, 0.69 ± 0.04, 0.57 ± 0.06, 0.68 ± 0.03, and 0.59 ± 0.04, respectively. The clinical-ML, clinical-HRT2-ML, clinical-DWI-ML, clinical-Merged-ML, clinical-DL, clinical-HRT2-DL, clinical-DWI-DL, and clinical-Merged-DL models demonstrated AUCs of 0.81 ± 0.06, 0.79 ± 0.02, 0.81 ± 0.02, 0.83 ± 0.01, 0.81 ± 0.04, 0.83 ± 0.04, 0.90 ± 0.04, and 0.83 ± 0.05, respectively. The clinical-DWI-DL model achieved the best predictive performance (accuracy 0.84 ± 0.05, sensitivity 0.94 ± 0. 13, specificity 0.79 ± 0.04).ConclusionsA comprehensive model combining MRI radiomic features and clinical characteristics achieved promising performance in TD prediction for RC patients. This approach has the potential to assist clinicians in preoperative stage evaluation and personalized treatment of RC patients.

The random lamellae of the synthetic CP were synthesized with a hydrothermal approach using o-Phenylenediamine (OPD) as a modifier. The decreases in the order degree of the CP synthesized in the presence of the OPD resulted from the loss of long-range order in a certain direction. Subsequently, the ultrasonic treatment and washing were conducive to further facilitate the disordered arrangements of its lamellae. The possible promotion mechanism regarding the nucleation and growth behaviors of the sol-gel particles was proposed. The fractal evolutions of the aluminosilicate species with crystallization time implied that the aluminosilicate species became gradually smooth to rough during the crystallization procedures since the amorphous structures transformed into flower-like morphologies. Their gas adsorption and separation performances indicated that the adsorption capacity of CO2 at 273 K reached up to 2.14 mmol·g−1 at 1 bar, and the selective factor (CO2/CH4) up to 3.4, much higher than that of the CPs synthesized without additive OPD. The breakthrough experiments displayed a longer breakthrough time and enhancement of CO2 uptake, showing better performance for CO2/CH4 separation. The cycling test further highlighted their efficiency for CO2/CH4 separation.

Clinoptilolite (CP) was successfully synthesized via a hydrothermal route in the presence of polyethylene glycol (PEG), and it was then delaminated by washing using Zn2+ containing acid. HKUST-1, as one kind of the Cu-based MOFs, showed a high CO2 adsorption capacity owing to its large pore volume and specific surface area. In the present work, we selected one of the most efficient ways for preparing the HKUST-1@CP compounds via coordination between exchanged Cu2+ and ligand (trimesic acid). Their structural and textural properties were characterized by XRD, SAXS, N2 sorption isotherms, SEM, and TG-DSC profiles. Particularly, the effect of the additive PEG (average molecular weight of 600) on the induction (nucleation) periods and growth behaviors were detailed and investigated in the hydrothermal crystallization procedures of synthetic CPs. The corresponding activation energies of induction (En) and growth (Eg) periods during crystallization intervals were calculated. Meanwhile, the pore size of the inter-particles of HKUST-1@CP was 14.16 nm, and the BET specific area and pore volume were 55.2 m2/g and 0.20 cm3/g, respectively. Their CO2 and CH4 adsorption capacities and selectivity were preliminarily explored, showing 0.93 mmol/g for HKUST-1@CP at 298 K with the highest selective factor of 5.87 for CO2/CH4, and the dynamic separation performance was evaluated in column breakthrough experiments. These results suggested an efficient way of preparing zeolites and MOFs composites that is conducive to being a promising adsorbent for applications in gas separation.

As a non-homogeneous porous medium, the structural complexity of coal directly affects pore structure parameters and gas percolation characteristics, which in turn determine the fractal dimension of coal samples. Among them, the specific surface area of coal largely determines the complexity of the pore structure and is closely related to coal and gas protrusion hazards. To investigate the relationship between the fractal dimension of coal and its specific surface area, we analyzed the pore structure of coal samples using low-temperature nitrogen adsorption, the mercury pressure method, and X-ray micro-computed tomography (CT) experiments. By calculating the fractal dimension of coal and reconstructing it in three dimensions, the morphological characteristics and distribution of pores can be described qualitatively and quantitatively. The fractal dimension of coal samples was found to increase exponentially with the specific surface area based on measurements of large pores and mesopores via the mercury pressure method and those of small pores and micropores using the nitrogen adsorption method. X-ray micro-CT experiments revealed that the fractal dimension of large pores (i.e., >2 μm) conformed to this pattern.

Abstract Background Hepatocellular carcinoma (HCC) is a common malignant tumor with poor prognosis. Magnetic resonance imaging (MRI) is one of the most effective imaging methods for the early diagnosis of HCC. However, the current MR contrast agents are still facing challenges in the early diagnosis of HCC due to their relatively low sensitivity and biosafety. Thus, the development of effective MR agents is highly needed for the early diagnosis of HCC. Results Herein, we fabricated an HCC-targeted nanocomplexes containing SPIO-loaded mesoporous polydopamine (MPDA@SPIO), sialic acid (SA)-modified polyethyleneimine (SA-PEI), and alpha-fetoprotein regulated ferritin gene (AFP-Fth) which was developed for the early diagnosis of HCC. It was found that the prepared nanocomplexes (MPDA@SPIO/SA-PEI/AFP-Fth) has an excellent biocompatibility towards the liver cells. In vivo and in vivo studies revealed that the transfection of AFP-Fth gene in hepatic cells significantly upregulated the expression level of ferritin, thereby resulting in an enhanced contrast on T2-weighted images via the formed endogenous MR contrast. Conclusions The results suggested that MPDA@SPIO/SA-PEI/AFP-Fth had a superior ability to enhance the MR contrast of T2-weighted images of tumor region than the other preparations, which was due to its HCC-targeted ability and the combined T2 contrast effect of endogenous ferritin and exogenous SPIO. Our study proved that MPDA@SPIO/SA-PEI/AFP-Fth nanocomplexes could be used as an effective MR contrast agent to detect HCC in the early stage.

Objective To explore independent risk factors for incomplete radiofrequency ablation (iRFA) of colorectal cancer liver metastases (CRLM) and evaluate adverse outcomes following iRFA. Materials and Methods Magnetic resonance imaging data of CRLM patients who received percutaneous RFA were randomized into training (70%) and validation set 1 (30%) data sets. An independent validation set 2 was derived from computed tomography scans. Uni- and multivariate analyses identified independent risk factors for iRFA. Area under the curve (AUC) values were used to evaluate the predictive model performance. Risk points were assigned to independent predictors, and iRFA was predicted according to the total risk score. Kaplan–Meier curves were used to assess new intrahepatic metastases (NIHM), unablated tumor progression, and overall survival (OS). Results Multivariate regression determined as independent iRFA risk factors perivascular tumor location, subcapsular tumor location, tumor size ≥20 mm, and minimal ablative margin ≤5 mm. The AUC values of the model in the training set, validation set 1, and validation set 2 were 0.867, 0.772, and 0.820, respectively. The respective AUC values of the total risk score were 0.864, 0.768, and 0.817. During the 6-year follow-up, the cumulative OS was significantly shorter in the iRFA than in the complete RFA group, and NIHM (hazard ratio [HR] = 2.79; 95% confidence interval [CI]: 1.725, 4.513) and unablated tumor progression (HR = 3.473; 95% CI: 1.506, 8.007) were more severe. Conclusions Perivascular tumor location, subcapsular tumor location, tumor size ≥20 mm, and minimal ablative margin ≤5 mm were independent risk factors for iRFA. iRFA may be a potential predictor of NIHM, unablated tumor progression, and OS.

Although rectal cancer comprises up to one-third of colorectal cancer cases and several prognosis nomograms have been established for colon cancer, statistical tools for predicting long-term survival in rectal cancer are lacking. In addition, previous prognostic studies did not include much imaging findings, qualitatively or quantitatively. Therefore, we include multiparametric MRI information from both radiologists’ readings and quantitative radiomics signatures to construct a prognostic model that allows 5-year overall survival (OS) prediction for advance-staged rectal cancer patients. The result suggested that the model combined with quantitative imaging findings might outperform that of conventional TNM staging or other clinical prognostic factors. It was noteworthy that the identified radiomics signature consisted of three from dynamic contrast-enhanced (DCE)-MRI, four from anatomical MRI, and one from functional diffusion-weighted imaging (DWI). This highlighted the importance of multiparametric MRI to address the issue of long-term survival estimation in rectal cancer. Additionally, the constructed radiomics signature demonstrated value to the conventional prognostic factors in predicting 5-year OS for stage II–III rectal cancer. The presented nomogram also provides a practical example of individualized prognosis estimation and may potentially impact treatment strategies.

Abstract Occurrence of Colorectal cancer (CRC) is relevant with gut microbiota. However, role of IRF3, a key signaling mediator in innate immune sensing, has been barely investigated in CRC. Here, we unexpectedly found that the IRF3 deficient mice are hyper-susceptible to the development of intestinal tumor in AOM/DSS and Apcmin/+ models. Genetic ablation of IRF3 profoundly promotes the proliferation of intestinal epithelial cells via aberrantly activating Wnt signaling. Mechanically, IRF3 in resting state robustly associates with the active β-catenin in the cytoplasm, thus preventing its nuclear translocation and cell proliferation, which can be relieved upon microbe-induced activation of IRF3. In accordance, the survival of CRC is clinically correlated with the expression level of IRF3. Therefore, our study identifies IRF3 as a negative regulator of the Wnt/β-catenin pathway and a potential prognosis marker for Wnt-related tumorigenesis, and describes an intriguing link between gut microbiota and CRC via the IRF3-β-catenin axis.

TiO2-supported clinoptilolites (TiO2/clinoptilolites) were successfully synthesized with controlled crystal phase and particle size via hydrothermal method to enhance photocatalytic performance of TiO2. The effects of various parameters including temperature, acidity and concentration of Ti-containing solutions on the particle size, crystal phase and agglomeration of TiO2 supported on clinoptilolite were investigated thoroughly by characterizations of X-ray diffraction (XRD), Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscope (SEM), transmission electron microscope (TEM), BET isotherm, UV–visible (UV–vis) spectrophotometer and Malvern zetasizer. The results demonstrate that increasing temperature and strengthen acidity are beneficial to enhance the crystallinity and particle size of supported TiO2. Increase in acidity also leads to more uniform distribution of TiO2 on the surface of clinoptilolite. The TiO2 nano-crystals deposited on the surface of clinoptilolite, exhibit rutile or anatase phase, strongly depending on the preparation procedure. The resultant TiO2/clinoptilolites could be used as photo-catalysts for the degradation of crystal violet (CV) dye in aqueous solution, showing a higher photo-catalytic activity with 89% degradation within 100 min. The effect of operational parameters, such as pH values of reaction media, dose of used catalyst, and concentration of CV dye on the CV degradation performance were investigated, in which the kinetics of CV dye degradation was found to follow the pseudo-first order kinetic model. Keywords: TiO2, Clinoptilolite, Hydrothermal method, Crystal phase, Degradation, Crystal violet dye

The dual (pH- and temperature-) responsive core-shell structured mesoporous nanomaterial P@BMMs were prepared using bimodal mesoporous silica as a core and poly(N-isopropylacrylamide-co-acrylic acid) P(NIPAM-co-AA) copolymer as a shell. Ibuprofen (IBU) was used as a model drug, and the effects of copolymer-coated shell thickness on drug loading and controlled release behavior were investigated by means of N2 sorption isotherms, dynamic light scattering measurements, X-ray diffraction patterns, Fourier transform infrared spectra, scanning electron and transmission electron microscopy, thermogravimetric profiles, and elemental analysis techniques. Particularly, their fractal evolutions in the drug delivery durations were explored via small angle X-ray scattering methods, demonstrating that the resultant P@BMMs before IBU-loading and after releasing possess the typical fractal features with spherical morphology. Meanwhile, the estimation for shell thickness of P@BMMs coating in different time intervals indicated that the drug-loaded capacity was improved with the increasing shell thickness, but drug-released rate varies, strongly depending on both shell thickness and release conditions. The drug delivery mechanism was preliminarily explored, following the Korsmeyer-Peppas model. Finally, cytotoxicity in cell and pharmacokinetic of released-IBU from hybrid nanocomposite in mice via intravenously injection were preliminarily explored. Keywords: Fractal, Mesoporous SiO2, Core-shell structures, SAXS, Dual (pH- and temperature-) responsive

Accurate tooth segmentation from CBCT images is a crucial step for specialist to perform quantitative analysis, clinical diagnosis and operation. In this paper, we present a symmetric full convolutional network with residual block and Dense Conditional Random Field (DCRF), which can achieve accurate segmentation automatically for tooth images. The proposed method can not only strengthen feature propagation, but also boost feature reuse, which can be credited to the contracting path and the expanding path that extract and recover pixel cues sufficiently. To this end, we apply special deep bottleneck architectures (DBAs) and summation-based skip connection into our network to ensure accurate segmentation for much deeper neural network. Compared with previous methods which are based on conditional random field for original image intensity, our approach applies DCRF to the posterior probability generated by the proposed network. To avoid the interferences of noises around the tooth, we combine the pixel-level prediction capability of DCRF, which further enhance the segmentation performance. In the experiments, we verify the capabilities of our methods based on four evaluation indicators, which demonstrates the superiority of our method.

The novel mesoporous TiO2/BMMs nanocomposites using bimodal mesoporous silica (BMMs) as support and rutile-anatase mixed phase as active species were successfully synthesized via hydrothermal and subsequent calcination method. Their structural and physiochemical properties were characterized by X-ray diffraction, scanning/transmission electron microscopy, BET-isotherms, inductive coupled plasma optical emission spectroscopy, zeta potential, Fourier transform infrared and UV–visible spectroscopy. The results demonstrated that the photocatalytic degradation activity of the synthesized catalysts were extensively enhanced as compare to bare TiO2, due to the highly uniform dispersion of mixed phases (Anatase and Rutile) TiO2 on the bimodal mesoporous surfaces. Particularly, the catalytic efficiency became increased as increasing the calcination temperature, showing the highest (98%) overall removal of CV dye using TBH5d as catalyst calcinated at 800 °C. Its most interesting finding is that the % adsorption of TBH5d was 46 %, more than that (26%) of TBH5c calcinated at 600 ℃, however, its % degradation was 21 %, lower than that (39 %) of TBH5c for dye concentration of 20 ppm in 50 min. Meanwhile, the kinetic adsorption and degradation performances were followed the pseudo second and first order models, respectively, further proving the high degradation efficiency of TBH5c with high rate constant than that of TBH5d. Thermodynamic parameters (ΔGads, ΔHads, and ΔSads) were calculated, suggesting the spontaneous and exothermic procedure with high entropy, while the adsorption equilibrium data was fitted to Dubinin-Radushkevich model. Both TBH5c and TBH5d showed an excellent stability and reactivity 71.2 and 61 %, respectively, even after 5th cycles. Thus, these results suggested that that TBH5c may be one of the suitable candidates in wastewater treatments.

Fe(III)-modified clinoptilolites (Fe-CPs) were prepared by hydrothermal treatment. The collapse of the heulandite skeletons was avoided by adjusting the pH value using HCl solution, showing the maximum relative crystallinity of the Fe-CPs at an optimal pH of 1.3. The competitive exchange performances between Fe3+ ions and H+ with Na+ (and K+) suggested that the exchange sites were more easily occupied by H+. Various characterizations verified that the hydrothermal treatments had a strong influence on the dispersion and morphology of the isolated and clustered Fe species. The high catalytic activity of the oxygen evolution reaction indicated the insertion of Fe3+ into the skeletons and the occurrences of isomorphic substitution. The fractal evolutions revealed that hydrothermal treatments with the increase of Fe content strongly affected the morphologies of Fe species with rough and disordered surfaces. Meanwhile, the Fe(III)-modified performances of the CPs were systematically investigated, showing that the maximum Fe-exchange capacity was up to 10.6 mg/g. Their thermodynamic parameters and kinetic performances suggested that the Fe(III)-modified procedures belonged to spontaneous, endothermic, and entropy-increasing behaviors. Finally, their adsorption capacities of CO2 at 273 and 298 K were preliminarily evaluated, showing high CO2 adsorption capacity (up to 1.67 mmol/g at 273 K).

Abstract Background Breast cancer is the leading cause of cancer-related death in women worldwide. Metastatic disease remains the primary cause of death in patients with breast cancer. Basal-like breast cancer (BLBC) is associated with aggressive behavior, stem-like phenotype, high histological grade, poor clinical features, and high rates of recurrences and/or metastasis. However, the mechanism of BLBC phenotype shaping remains obscure. Methods Seventeen normal breast/breast cancer cell lines were used for evaluating the breast cancer subtype-markers, WNT targets and constitutive components, and epithelial mesenchymal transition (EMT) markers analysis by western blot. One hundred and twenty formalin-fixed breast cancer tissues were used for immunohistochemistry (IHC) staining. Nine online platforms (cBioPortal, CCLE, GEPIA, etc.) were used for related analyses. Results We identified Wnt5b as a key regulatory factor that governs the phenotype of BLBC by activating canonical and non-canonical WNT signaling. Wnt5b exhibited basal-like specificity in cells and clinical samples both at the mRNA and protein levels and also showed good correlation with basal-like phenotype at the mRNA level. Besides, Wnt5b was also a promising therapeutic target for LGK-974 treatment. In addition, we identified that CK1α was expressed at low levels in BLBC and that the activation of CK1α by pyrvinium was an alternative strategy for BLBC treatment. Conclusions Wnt5b is not only a diagnostic biomarker but also a potential therapeutic target of BLBC. Graphical abstract

Abstract Background Gallbladder cancer is the most common malignant neoplasm of the biliary tract, responsible for 80–95% of cases. Appropriate models are required for investigating the molecular pathogenesis of gallbladder cancer. Methods In this study, we aimed to establish a gallbladder cancer cell line from primary tumour. Single cell RNA sequencing, Light and electron microscopy, DNA content analysis, cytogenetic analysis, short tandem repeat (STR) DNA fingerprint analysis, immunophenotypic characterization, and xeno-transplantation were utilized to characterize the novel ZJU-0430 cell line in vitro and in vivo. Results The cell line showed multiple cell shapes and characteristic epithelial morphologies under the microscope, but no too much heterogeneity by scRNA-Seq, with a population doubling time (PDT) of 19.81 h, which was shorter than that for GBC-SD cells. An immunophenotypic analysis revealed that ZJU-0430 cells were positive for CD24, CD44, CD29 and CD133 expression, and partially positive for CD184, and CD326 expression, and negative for CD34, CD90, CD117, and CD338 expression, similar to the primary cancer cells. A pathological analysis confirmed the origination of cell line from gallbladder tumour. ZJU-0430 cells had higher migration, invasion and proliferation properties than GBC-SD cells in vitro, and showed in vivo tumorigenicity in nude mouse xenograft settings. Conclusions The results confirm the potential utility of ZJU-0430 cell line as a representative model of gallbladder cancer and suggest that it could be used in the in vitro and in vivo studies of gallbladder cancer pathogenesis and to develop new therapeutics.

PurposeTo evaluate the efficacy and safety of percutaneous radiofrequency ablation (RFA) for subcapsular colorectal cancer liver metastases (CLMs).Materials and MethodsWith the approval of the Institutional Review Board, the clinical data of CLM patients who underwent percutaneous RFA for the first time from August 2010 to August 2020 were continuously collected. All CLMs were divided into subcapsular and non-capsular groups. Baseline characteristic data, technical effectiveness, minimal ablative margin, complications, local tumor progression (LTP), and overall survival (OS) between the two groups were analyzed using the t-test or chi-square test. A Cox regression model was used to evaluate the prognostic factors of LTP.ResultsOne hundred and ninety-nine patients (124 males; mean age, 60.2 years) with 402 CLMs (221 subcapsular; mean size, 16.0 mm) were enrolled in the study. Technical effectiveness was achieved in 93.5% (376/402) of CLMs, with a major complication rate of 5.5%. Compared with non-subcapsular tumors, the minimal ablative margin achieved in subcapsular CLM was smaller (χ2 = -8.047, P < 0.001). With a median follow-up time of 23 months (range, 3−96 months), 37.1% of the tumors had LTP. The estimated cumulative OS at 1, 3, and 5 years was 96.1%, 66.0%, and 44.2%, respectively. There were no statistically significant differences between the two groups in terms of technical effectiveness (χ2 = 0.484, P = 0.487), major complications (χ2 = 0.082, P = 0.775), local tumor progression-free survival (LTPFS) (χ2 = 0.881, P = 0.348), and OS (χ2 = 2.874, P = 0.090). Minimal ablative margin, tumor size (≥20 mm), and technical effectiveness were predictors of LTP (all P < 0.05).ConclusionRFA is a safe and effective technique for local tumor control of subcapsular CLMs.

In this study, we synthesized pH-sensitive thiamethoxam-3-(2-aminoethylamino) propyl-bimodal mesoporous silica (P/Thi-NN-BMMs) nanoparticles (NPs). We used this bimodal mesoporous silica (BMMs) mesoporous material as a carrier based on the principle of free radical polymerization. The size of the P/Thi-NN-BMMs NPs was about 891.7 ± 4.9 nm, with a zeta potential of about −25.7 ± 2.5 mV. X-ray powder diffraction analysis, N2-sorption measurements and thermogravimetric analysis indicated that thiamethoxam (Thi) was loaded into the pores of the mesoporous structure and that the mesopore surface was coated with polyacrylic acid (PAA). The loading rate of P/Thi-NN-BMMs was about 25.2%. The controlled-release NPs had excellent anti-photolysis performance and storage stability. The NPs showed significant pH sensitivity, and the Thi release rate in pH 10.0 phosphate buffer was higher than those in pH 7.4 and pH 3.0 phosphate buffers. We described the sustained-release curves according to the Weibull model. The relative toxicity of P/Thi-NN-BMMs against peach aphid was 1.44 times that of commercial Thi. This provides a promising instrument for effective insect control and environment protection.

Supply chain finance (SCF) plays an increasingly important role in global enterprise competition. The credit risk accompanying SCF has attracted the attention of the government, enterprises, and academia. However, with the absence of data and inaccurate information, traditional risk assessment methods are frequently failed to assess the credit risk in SCF, especially for small- and medium-sized enterprises (SMEs). In this study, a grey correlation model is introduced and applied to the SCF risk assessment process for 15 firms in the Chinese home appliance industry with 15 performance indicators that represent profitability, solvency, operational capability, and development capability. The empirical study displays the operability and effectiveness of the grey correlation model, which is superior to traditional methods in the supply chain financial risk assessment.

Various cation–exchanged clinoptilolites (M–CPs, M = Li+, Cs+, Ca2+, Sr2+) were prepared, and their exchanged thermodynamic (and kinetic) properties and adsorption performances for CH4, N2, and CO2 were investigated. The results demonstrated that the relative crystallinity of M–CPS decreased with the increase of exchange times. Their chemisorbed water weight loss gradually increased with the increasing exchange times, except that of Cs–x–CP. The ΔrGmθ values of exchange process of Li+, Cs+, Ca2+, or Sr2 presented the increased trend with the enhanced exchange times, but they decreased as the temperature increased. The negative ΔrGmθ values and the positive ΔrHmθ and ΔrSmθ values suggested that the exchanged procedure belonged to spontaneous, endothermic, and entropy-increasing behaviors; their kinetic performances followed a pseudo–second–order model. However, the calculated Ea values of exchange process showed the increased tendencies with the enhanced exchange times, indicating that the exchange process became more difficult. Finally, the preliminary adsorption results indicated that the maximum adsorption amount at 273 K and 1 bar was 0.51 mmol/g of CH4 and 0.38 mmol/g of N2 by (Na, K)–CP, and 2.32 mmol/g of CO2 by Li–6–CP.

In the current context of the establishment of world-class universities and disciplines in China, this study examined the investment of research funds at universities. First, six variables were selected as evaluation indicators from the perspective of fixed assets, teaching configuration, research instruments, and the number of books in libraries. Seventy-two universities were investigated from 2013 to 2017. Second, an evaluation system was constructed using the BP (backpropagation) neural network method and its applicability was verified. Finally, by adjusting the six indicators, the investment of university research funds could be adjusted and predicted to provide a reference for the construction of “first-class” universities and disciplines.

The gray prediction model, based on the GM(1,1) method, is an important branch of gray theory with the most active research and the most fruitful results, and it is the most widely used because of its small sample size, simple modeling process, and easy to use. Such advantages have been successfully applied in many fields such as transportation, agriculture, energy, medicine, and environment and have been gradually developed into a mainstream predictive modeling method. This study combines the Three-parameter Whitenization Grey Model (TWGM(1,1)), which fits the inhomogeneous exponential law sequence, and the Particle Swarm Algorithm (PSA) to optimize the order and background value coefficients under the condition of the minimum sum of squares of simulation errors, and hence, to solve the problem that the cumulative order is fixed to “1” and the background value coefficient value is fixed to “0.5.” As a result, a parameter-optimized gray system model with flexibility, adaptability, and dynamic adjustment is designed to simulate and predict China’s higher education gross enrollment rate. The application shows that the model has better overall simulation and prediction performance than others. On the one hand, the parametric optimization model significantly improves its own performance, and on the other hand, its intelligent and adjustable adaptivity improves the accuracy and further extends its application.

ABSTRACT: Purpose To evaluate the performance of diffusion-weighted imaging (DWI) and variable flip angle (VFA) T1 mapping as a supplement to image-guided biopsy in follow-up analysis of liver fibrosis.Materials and Methods This prospective study was approved by the institution’s committee on human research, and written informed consent was provided from the enrolled patients. We investigated five MRI parameters of DWI and VFA T1 mapping, collected from 11 patients who underwent serial ultrasound image-guided biopsy with follow-up MRI within 1.5 years after treatment for liver fibrosis/cirrhosis. For each patient, four consecutive MRI examinations were conducted, including baseline MRI before treatment and three follow-up MRI examinations after treatment at each 0.5-year interval. ADC values at four b values and T1 relaxation times were correlated to pathology-confirmed liver fibrosis stages, which were subsequently divided into two groups, stages F2–3 and F4. The receiver operating characteristic (ROC) analysis and repeated measurement analysis of variance were used for statistical analysis.Results Among these ADC parameters, ADC value (b = 500 s/mm2) was the most consistent in differentiating between stage F2–3 and F4 liver fibrosis. Repeated measurement analysis showed that the intra-group and inter-group differences were 0.447 and 0.024, respectively. T1 relaxation time could not consistently differentiate between the F2–3 and F4 groups; however, it was repeatable, and the intra-group and inter-group differences were 0.410 and 0.042, respectively.Conclusion MRI-ADC value at a b value of 500 s/mm2 can be a promising biomarker for differentiating stages F2–3 and F4 liver fibrosis. A combination of this biomarker with repeatable T1 relaxation time may function as a non-invasive tool for follow-up liver fibrosis in patients who reject repeated image-guided biopsy. Keywords: image-guided biopsy, MRI T1 mapping, diffusion-weighted imaging

Abstract Background Basal/human epidermal growth factor receptor (HER)2-positive (HER2+) breast cancer is resistant to monoclonal antibody (herceptin) treatment. There are currently only three basal/HER2+ breast cancer cell lines available, but they are not from Chinese populations. Methods Three immortalized cell lines (ZJU-0327, ZJU-0725, and ZJU-1127) were established from invasive ductal breast carcinoma tissue of two patients treated by surgical resection at our center. The cell lines were characterized in terms of histology, therapeutic response, and biomarker expression. Their tumorigenic potential was evaluated in an athymic nude (BALB/C nu) mouse xenograft model. Cell authentication testing by the techniques of short tandem repeat. Results ZJU-0327, ZJU-0725, and ZJU-1127 cell lines were maintained for more than 110 passages in vitro. The cells grew as monolayers; showed typical epithelial morphology and ultrastructure; were polyploid; had doubling times of 18, 57.5, and 18 h, respectively; had a near-tetraploid (ZJU-0327 and ZJU-1127) or aneuploid (ZJU-0725) karyotype with structural aberrations and tumor protein 53 mutation; insensitive to chemotherapeutic drugs and/or radiation; show high invasiveness and tumorigenicity in mice; and had no mycoplasma contamination. The cell lines were basal/HER2+, expressed cluster of differentiation, and were associated with poor prognosis. Cell authentication testing by the American Type Culture Collection confirmed the human origin of the cell lines, which did not match those in existing databases. Conclusions The three novel basal/HER2+ breast cancer cell lines recapitulating the malignant characteristics of the parent tumor’s, and can be useful for clarifying the molecular pathogenesis of basal/HER2+ breast cancer.

The authors show that NDR1 promotion of STAT1 translation is an important event for IFN-dependent antiviral immune response. These data suggest that NDR1 has an important role in controlling viral infections.

Abstract Casein kinase 1α (CK1α) is a multifunctional protein belonging to the CK1 protein family that is conserved in eukaryotes from yeast to humans. It regulates signaling pathways related to membrane trafficking, cell cycle progression, chromosome segregation, apoptosis, autophagy, cell metabolism, and differentiation in development, circadian rhythm, and the immune response as well as neurodegeneration and cancer. Given its involvement in diverse cellular, physiological, and pathological processes, CK1α is a promising therapeutic target. In this review, we summarize what is known of the biological functions of CK1α, and provide an overview of existing challenges and potential opportunities for advancing theranostics.

Abstract The conventional chemotherapeutics could not be traced in vivo and provide timely feedback on the clinical effectiveness of drugs. In this study, poly(L-γ-glutamyl-glutamine)-paclitaxel (PGG-PTX), as a model polymer, was chemically conjugated with Gd-DTPA (Gd-diethylenetriaminepentaacetic acid), a T1-contrast agent of MRI, to prepare a Gd-DTPA-conjugated PGG-PTX (PGG-PTX-DTPA-Gd) delivery system used for tumor theranostics. PGG-PTX-DTPA-Gd can be self-assembled to NPs in water with a z-average hydrodynamic diameter about 35.9 nm. The 3 T MRI results confirmed that the relaxivity of PGG-PTX-DTPA-Gd NPs (r1 = 18.98 mM−1S−1) was increased nearly 4.9 times compared with that of free Gd-DTPA (r1 = 3.87 mM−1S−1). The in vivo fluorescence imaging results showed that PGG-PTX-DTPA-Gd NPs could be accumulated in the tumor tissue of NCI-H460 lung cancer animal model by EPR effect, which was similar to PGG-PTX NPs. The MRI results showed that compared with free Gd-DTPA, PGG-PTX-DTPA-Gd NPs showed significantly enhanced and prolonged signal intensity in tumor tissue, which should be attributed to the increased relaxivity and tumor accumulation. PGG-PTX-DTPA-Gd NPs also showed effective antitumor effect in vivo. These results indicated that PGG-PTX-DTPA-Gd NPs are an effective delivery system for tumor theranostics, and should have a potential value in personalized treatment of tumor.

In this study, boscalid silica nanosphere nanoparticles (Bos@SNS/t Nps) and boscalid bimodal mesoporous silicas material nanoparticles (Bos@BMMs Nps) were prepared using two different methods. A comparative study on characteristics and properties of two nanospheres were conducted. Both nanoparticles had spherical shapes with average diameters of 719.3 ± 6.3 nm (Bos@BMMs) Nps and 981.3 ± 4.8 nm (Bos@SNS/t) Nps. The structures of nanoparticles were characterized by scanning electron microscopy, X-ray diffraction, dynamic light scattering laser particle-size analysis, and fourier transform infrared spectroscopy, indicating that Nps had a well-defined core–shell construction for efficient loading of Bos. The loading rates of Bos@BMMs and Bos@SNS/t Nps were 25.2 ± 2.3% and 27.3 ± 3.6%, respectively. The nanoparticles had obvious pH sensitivity, and the release of Bos in pH 9.0 was higher than those in pH 7.0 and pH 4.0. No significant difference in the release behavior of nanocomposites was found, and the release models were fitted with the Weibull equation. Finally, the bioactivity of the Bos-loaded nanocomposite was measured against Rhizoctonia solani , which showed that the fungicidal efficacy of Bos@SNS/t was slightly better than that of Bos@BMMs.

Abstract Unresectable hepatocellular carcinoma (HCC) needs locoregional ablation as a curative or downstage therapy. Microsecond Pulsed Electric Fields (μsPEFs) is an option. A xenograft tumor model was set up on 48 nude mice by injecting human hepatocellular carcinoma Hep3B cells subcutaneously. The tumor-bearing mice were randomly divided into 3 groups: μsPEFs treated, sham and control group. μsPEFs group was treated by μsPEFs twice in 5 days. Tumor volume, survival, pathology, mitochondria function and cytokines were followed up. μsPEFs was also conducted on 3 swine to determine impact on organ functions. The tumors treated by μsPEFs were completely eradicated while tumors in control and sham groups grew up to 2 cm3 in 3 weeks. The μsPEFs-treated group indicated mitochondrial damage and tumor necrosis as shown in JC-1 test, flow cytometry, H&E staining and TEM. μsPEFs activates CD56+ and CD68+ cells and inhibits tumor proliferating cell nuclear antigen. μsPEFs inhibits HCC growth in the nude mice by causing mitochondria damage, tumor necrosis and non-specific inflammation. μsPEFs treats porcine livers without damaging vital organs. μsPEFs is a feasible minimally invasive locoregional ablation option.

Because of its good stability, immobilized enzyme biosensor has become one of the main methods to prepare enzyme electrode, which is widely used in biosensors. The sensor cannot be used online due to the high temperature sterilization process. It cannot control the amount of glucose in real time, which affects the quality and yield of fermentation. For this reason, some scholars put forward the idea of using enzyme instead of immobilized enzyme membrane. The glucose biosensor of enzyme injection has reached the standard of practical application. However, there is a slight difference in the detection time, stability and other performance indicators compared with the mature enzyme membrane sensor. In this paper, a new algorithm is designed to calculate the reaction constant and concentration of enzyme injection glucose biosensor based on the kinetic equation of enzyme reaction. The accuracy of the algorithm is verified by experiments. The main content of this study is to detect the glucose solution of 1mg/ml and 2mg/ml by enzyme injection sensor. By recording the voltage versus time curve, the linear slope of the curve is obtained. The Michaelis constant Km of the enzyme involved in the reaction was calculated to be 1.59. The change of voltage gradient of 3mg/ml glucose standard solution can be obtained. In addition, the algorithm is incorporated into the concentration equation. The concentration of the measured object is 3.04mg/ml. The accuracy of the algorithm is 98.67%.

Adsorption characteristics of pure gases N2 and O2 on various silver exchanged low silica X-type (AgxLi96-x-LSX) zeolites were investigated. The equilibrium adsorption isotherms of N2 and O2 were measured at 273 and 298 K. Textual and structural properties of parent and resultant AgxLi96-x-LSX were characterized by XRD, BET surface area, and SEM techniques. Kinetics of their thermal dehydration were studied by exploiting thermogravimetric and differential data (TG-DTG) obtained at three heating rates (5, 10 and 15 K) using two model-free (Kissinger and Flynn-Wall-Ozawa) and one model fitting (Coats-Redfern) methods. Forty one mechanism functions were used to evaluate kinetic triplet (activation energy, frequency factor, and most probable mechanism/model) for different stages of dehydration. Results revealed that the impact of very small content of silver on the adsorption of N2 is pronounced and attributed to weak chemical bonds formed between N2 and Ag+ clusters due to strong adsorption of N2 at low pressure, whereas O2 adsorption is affected to a negligible extent. In addition, the N2/O2 adsorption selectivity shows unexpected low values for Ag87.08Li7.94Na0.98-LSX with higher Ag+ content (91.00 %), which might be due to low crystalline water content as well as Ag+ clusters located at SIII sites. N2 adsorption strongly depends on temperature as higher adsorption occurs at low temperature 273 K as compared to 298 K.

A characteristic feature of atherosclerosis is its diffuse involvement of arteries across the entire human body. Bone marrow cells (BMC) can be simultaneously transferred with therapeutic genes and magnetic resonance (MR) contrast agents prior to their transplantation. Via systemic transplantation, these dual-transferred BMCs can circulate through the entire body and thus function as vehicles to carry genes/contrast agents to multiple atherosclerosis. This study was to evaluate the feasibility of using in vivo MR imaging (MRI) to monitor BMC-mediated interleukin-10 (IL-10) gene therapy of atherosclerosis.For in vitro confirmation, donor mouse BMCs were transduced by IL-10/lentivirus, and then labeled with a T2-MR contrast agent (Feridex). For in vivo validation, atherosclerotic apoE(-/-) mice were intravenously transplanted with IL-10/Feridex-BMCs (Group I, n = 5) and Feridex-BMCs (Group II, n = 5), compared to controls without BMC transplantation (Group III, n = 5). The cell migration to aortic atherosclerotic lesions was monitored in vivo using 3.0T MRI with subsequent histology correlation. To evaluate the therapeutic effect of BMC-mediated IL-10 gene therapy, we statistically compared the normalized wall indexes (NWI) of ascending aortas amongst different mouse groups with various treatments.Of in vitro experiments, simultaneous IL-10 transduction and Feridex labeling of BMCs were successfully achieved, with high cell viability and cell labeling efficiency, as well as IL-10 expression efficiency (≥90%). Of in vivo experiments, MRI of animal groups I and II showed signal voids within the aortic walls due to Feridex-created artifacts from the migrated BMCs in the atherosclerotic plaques, which were confirmed by histology. Histological quantification showed that the mean NWI of group I was significantly lower than those of group II and group III (P

This case report originated from a case of neonatal multisystemic juvenile xanthogranuloma (JXG). The patient presented with blue muffin rush, cervical mass, bone destruction, lung nodule, hepatosplenomegaly, and coagulopathy and was successfully treated with Langerhans cell histiocytosis (LCH) based chemotherapy treatment. Similar cases in literature were reviewed and it seems that JXG, a relatively benign entity, when presented in its systemic form with liver involvement, could have an aggressive course and portend quite poor prognosis. Challenges and special consideration of the diagnosis, treatment, and future case observation are discussed.