Fresnel incoherent compressive holography toward 3D videography via dual-channel simultaneous phase-shifting interferometry.

Fresnel incoherent correlation holography (FINCH) enables high-resolution 3D imaging of objects from several 2D holograms under incoherent light and has many attractive applications in motionless 3D fluorescence imaging. However, FINCH has difficulty implementing 3D imaging of dynamic scenes since multiple phase-shifting holograms need to be recorded for removing the bias term and twin image in the reconstructed scene, which requires the object to remain static during this progress. Here, we propose a dual-channel Fresnel noncoherent compressive holography method. First, a pair of holograms with π phase shifts obtained in a single shot are used for removing the bias term noise. Then, a physic-driven compressive sensing (CS) algorithm is used to achieve twin-image-free reconstruction. In addition, we analyze the reconstruction effect and suitability of the CS algorithm and two-step phase-shift filtering algorithm for objects with different complexities. The experimental results show that the proposed method can record hologram videos of 3D dynamic objects and scenes without sacrificing the imaging field of view or resolution. Moreover, the system refocuses images at arbitrary depth positions via computation, hence providing a new method for fast high-throughput incoherent 3D imaging.

Accelerating quad Airy beams-based point response for interferenceless coded aperture correlation holography.

Interferenceless-coded aperture correlation holography (I-COACH) is a promising single-shot 3D imaging method in which a coded phase mask (CPM) is used to encode 3D information about an object into an intensity distribution. However, conventional CPM encoding methods usually lead to intensity dilution, especially in the recording of point spread holograms (PSHs), resulting in low-resolution reconstruction of I-COACH. Here, we propose accelerating quad Airy beams with four mainlobes as a point response to enable weak diffraction propagation and a sharp maximum intensity in the transverse direction. Moreover, the four mainlobes exhibit lateral acceleration in 3D space, so the PSHs in different axial positions show a unique and concentrated intensity distribution on the image sensor, thereby realizing a high-resolution reconstruction of I-COACH. Compared with conventional CPM encoding methods, the proposed accelerating quad Airy-beam-encoding method has superior performance in improving the resolution of I-COACH reconstruction even in the presence of external interference.

Series Arc Fault Detection under Vibration Condition Based on N-M-M-B.

Under the conditions of a mechanical fault in a motor, mechanical vibration of a specific frequency can be generated. The electrical contact points directly connected to the motor can vibrate at the same frequency. The electrical contact points with poor contact can easily produce a series arc fault under vibration conditions, which affects the reliability of the power supply. In order to detect the series arc fault under different vibration conditions, the arc fault generator is connected between the back end of the frequency converter and the motor. An arc fault experiment under different vibration conditions was carried out and the fault phase current and arc voltage signals were collected. In this paper, the noise-assisted multivariate empirical mode decomposition and the correlation coefficient between each intrinsic mode function are used to select the fault feature signals. Then, the reconstructed signal is input into the series arc fault model combining a multi-scale convolutional neural network and a bidirectional long short-term memory network for training. The research results show that the series arc fault detection method proposed in this paper can effectively detect the series arc fault and can preliminarily identify the type of motor fault causing the mechanical vibration of the motor; the model has good noise immunity and generalization.

Real-time phase imaging with physics-enhanced network and equivariance.

Learning-based phase imaging balances high fidelity and speed. However, supervised training requires unmistakable and large-scale datasets, which are often hard or impossible to obtain. Here, we propose an architecture for real-time phase imaging based on physics-enhanced network and equivariance (PEPI). The measurement consistency and equivariant consistency of physical diffraction images are used to optimize the network parameters and invert the process from a single diffraction pattern. In addition, we propose a regularization method based total variation kernel (TV-K) function constraint to output more texture details and high-frequency information. The results show that PEPI can produce the object phase quickly and accurately, and the proposed learning strategy performs closely to the fully supervised method in the evaluation function. Moreover, the PEPI solution can handle high-frequency details better than the fully supervised method. The reconstruction results validate the robustness and generalization ability of the proposed method. Specially, our results show that PEPI leads to considerable performance improvement on the imaging inverse problem, thereby paving the way for high-precision unsupervised phase imaging.

Broadband Raman scattering enhancement with reduced heat generation in a dielectric-metal hybrid nanocavity.

The strongly localized electric field achieved in metallic nanoparticles (NPs) and nanostructures are commonly employed to realize surface-enhanced Raman scattering. However, the heat originating from the Ohmic loss of metals may lead to the damage of the analyzed molecules, which severely limits the practical applications of pure-metallic nanostructures. Here, we propose a dielectric-metallic hybrid nanocavity placing silicon (Si) NPs onto a gold (Au) film to realize broadband Raman scattering enhancement with significantly reduced heat generation. Our results reveal that the heat generation is dramatically reduced in the hybrid nanocavity as compared with its pure-metallic counterpart while a significantly enhanced electric field is maintained. We demonstrate numerically and experimentally that the optical resonances, which arise from the coherent coupling of the electric and magnetic dipoles excited inside the Si NP with their mirror images arisen from the Au film, can be employed to enhance the excitation and radiation of Raman signals, respectively. We find that the enhancement in the radiation of Raman signals plays a crucial role in enhancing the total Raman scattering. We also show that the hybrid nanocavity acts as a nano-antenna which effectively radiates Raman signals into the far-field. These findings indicate the advantages of such hybrid nanocavities in temperature-sensitive Raman scattering characterization and supply new strategies for designing nanoscale photonic devices of other functionalities with hybrid nanocavities.

Optical nanoantenna with muitiple surface plasmon resonances for enhancements in near-field intensity and far-field radiation.

Plasmonic nanostructures with dual surface plasmon resonances capable of simultaneously realizing strong light confinement and efficient light radiation are attractive for light-matter interaction and nanoscale optical detection. Here, we propose an optical nanoantenna by adding gold nanoring to the conventional Fano-type resonance antenna. With the help of gold nanoring, the following improvements are simultaneously realized: (1). The near-field intensity of the Fano-type antenna is further enhanced by the Fabry Perot-like resonance formed by the combination of the gold nanoring and the substrate waveguide layer. (2). Directional radiation is realized by the collaboration of the gold nanoring and the Fano-type antenna, thus improving the collection efficiency of the far-field signal. (3). The multi-wavelength tunable performance of the Fano resonance antenna is significantly improved by replacing the superradiation mode in the Fano resonance with the dipole resonance induced by the gold nanoring. The optical properties of the nanoantennas are demonstrated by numerical simulations and practical devices. Therefore, the proposed optical nanoantenna provides a new idea for further improving the performance of conventional Fano-type nanoantennas and opens new horizons for designing plasmonic devices with enhancements in both near- and far-field functionalities, which can be applied in a wide range of applications such as surface-enhanced spectroscopy, photoluminescence, nonlinear nanomaterials/emitters and biomedicine sensing.

Periprocedural risk factors for incomplete radiofrequency ablation of liver metastases from colorectal cancer: a single-center retrospective analysis.

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.

Lipopolysaccharide induces neuroinflammation in microglia by activating the MTOR pathway and downregulating Vps34 to inhibit autophagosome formation.

BACKGROUND: Microglial activation is a prominent feature of neuroinflammation, which is present in almost all neurodegenerative diseases. While an initial inflammatory response mediated by microglia is considered to be protective, excessive pro-inflammatory response of microglia contributes to the pathogenesis of neurodegeneration. Although autophagy is involved in the suppression of inflammation, its role and mechanism in microglia are unclear. METHODS: In the present study, we studied the mechanism by which lipopolysaccharide (LPS) affects microglial autophagy and the effects of autophagy on the production of pro-inflammatory factors in microglial cells by western blotting, immunocytochemistry, transfection, transmission electron microscopy (TEM), and real-time PCR. In a mouse model of neuroinflammation, generated by intraventricular injection of LPS (5 µg/animal), we induced autophagy by rapamycin injection and investigated the effects of enhanced autophagy on microglial activation by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry. RESULTS: We found that autophagic flux was suppressed in LPS-stimulated N9 microglial cells, as evidenced by decreased expression of the autophagy marker LC3-II (lipidated form of MAP1LC3), as well as increased levels of the autophagy adaptor protein SQSTM1. LPS significantly decreased Vps34 expression in N9 microglial cells by activating the PI3KI/AKT/MTOR pathway without affecting the levels of lysosome-associated proteins and enzymes. More importantly, overexpression of Vps34 significantly enhanced the autophagic flux and decreased the accumulation of SQSTM1 in LPS-stimulated N9 microglial cells. Moreover, our results revealed that an LPS-induced reduction in the level of Vps34 prevented the maturation of omegasomes to phagophores. Furthermore, LPS-induced neuroinflammation was significantly ameliorated by treatment with the autophagy inducer rapamycin both in vitro and in vivo. CONCLUSIONS: These data reveal that LPS-induced neuroinflammation in N9 microglial cells is associated with the inhibition of autophagic flux through the activation of the PI3KI/AKT/MTOR pathway, while enhanced microglial autophagy downregulates LPS-induced neuroinflammation. Thus, this study suggests that promoting the early stages of autophagy might be a potential therapeutic approach for neuroinflammation-associated diseases.

Diffusion kurtosis imaging in liver: a preliminary reproducibility study in healthy volunteers.

OBJECTIVES: To systematically test the reproducibility of DKI technique in normal liver and report a complete set of DKI measurement data. MATERIALS AND METHODS: Thirty-two healthy volunteers were examined with liver DKI twice on the GE 3.0 T MRI scanner and reviewed by three professional experts. DKI-derived parameters fractional anisotropy of kurtosis (FAk), mean diffusivity (Md), axial diffusivity (Da), radial diffusivity (Dr), mean kurtosis (Mk), axial kurtosis (Ka), and radial kurtosis (Kr) in eight segments divided by Couinaud octagonal method were collected. Inter-class correlation coefficient (ICC) was used to assess the agreement between three experts. For each expert, the reproducibility of twice scans was evaluated by Bland-Altman method. Multivariate analysis of variance was to explore the regional distribution characteristics of DKI-derived parameters, and showed with box-plot graph. RESULTS: Using ICC analysis, except for FAk (ICC 0.312, 0.307), other DKI metric values showed high reproducibility (0.716 < ICC < 0.907) between three experts for each of two DKI measurements. With Bland-Altman method, liver segment 5 (S5) showed the best reproducibility between two DKI measurement, and the reproducibility of segment 4 (S4) was the worst. The reproducibility of the right lobe was significantly higher than the left lobe. The values of diffusion metrics (Md, Da, and Dr) and kurtosis metrics (Mk, Ka, and Kr) existed significantly difference between the right and left hepatic lobes. CONCLUSION: DKI has shown excellent reproducibility in liver imaging. The range of values for multiple DKI parameters, derived from the normal liver, was reported, and may provide data reference for further clinical DKI applications. Additionally, DKI technique is a non-invasive method to reflect the perfusion or structural differences between the left and right hepatic lobes from the molecular level.

Clinical diagnostic value of contrast-enhanced ultrasound combined with microflow imaging in benign and malignant renal tumors: A retrospective cohort study.

This study aims to evaluate the clinical diagnostic value of contrast-enhanced ultrasound combined with microflow imaging (CEUS-MFI) in the differential diagnosis of benign and malignant renal tumors. All patients underwent CEUS, MFI, color doppler flow imaging (CDFI), and CEUS-MFI. The efficacies of these different diagnostic modalities in diagnosing benign and malignant renal tumors were evaluated by Kappa consistency test and the receiver operating characteristic (ROC) curve, with pathological findings serving as the gold standard. CDFI, MFI and CEUS-MFI all demonstrated higher blood flow in malignant tumors compared with benign tumors. Compared with benign tumors, CDFI detected a higher rate of punctate and linear Adler grade 2 and 3 blood flows in malignant tumors, as well as peripheral semicircular or annular blood flow. MFI identified a high rate of peripheral circumferential blood flow and irregular vascular morphology in malignant tumors, with most exhibiting Adler grade 3 blood flow. In addition, CEUS-MFI showed more dendritic or irregular Adler grade 2 or 3 blood flows in malignant renal tumors than MFI alone. Further analysis showed that CEUS-MFI had the highest consistency with pathological diagnosis (Kappa = 0.808). The ROC curve showed that the area under the curve (AUC) for CEUS-MFI in differentiating between benign and malignant lesions was 0.898, significantly outperforming other single diagnostic methods. With its capability to display microvascular information and assess overall pathological characteristics, MFI can accurately predict the nature of renal tumors and assist in surgical planning.

Pseudoginsenoside-F11 reduces cognitive impairment and white matter injury in vascular dementia by alleviating autophagy-lysosomal pathway deficiency.

BACKGROUND: Vascular dementia (VaD) resulting from chronic cerebral hypoperfusion (CCH) induces cognitive impairment and white matter injury (WMI). We previously found that CCH induces dysfunction of the autophagy-lysosomal pathway (ALP) in white matter (WM) of rats. Enhancing oligodendrocyte autophagy to counteract ALP deficiency is beneficial for cognitive recovery. Pseudogenoside-F11 (PF11), a saponin extracted from Panax quinquefolium l., provides neuroprotective benefits in many animal models of cerebral ischemia and dementia. PURPOSE: To investigate how PF11 affects cognitive deterioration in rats with VaD induced by two vessel occlusion (2VO), and to determine if PF11 regulates ALP dysfunction in WM. METHODS: CCH-related VaD was induced in rats using the 2VO method. PF11 (6, 12, 24 mg/kg, intragastric administration) was given continuously for 4 weeks postoperatively. Behavioral tests related to cognitive function were performed on the 28th day following 2VO. Transmission electron microscopy, immunofluorescence, western blotting and Luxol fast blue staining were used to assess the WMI and the mechanism of action of PF11 in 2VO-induced VaD. RESULTS: PF11 (12 mg/kg) ameliorated 2VO-induced cognitive impairment. PF11 also alleviated WMI on the 28th day following 2VO, as characterized by reduction of neuronal axonal demyelination and axonal loss. Furthermore, PF11 prevented mature oligodendrocytes death by attenuating ALP deficiency in WM on the 14th day following 2VO, as manifested by enhancement of mechanistic target of rapamycin-mediated autophagy and lysosomal function, thereby reducing the aberrant accumulation of autophagy substrates and increasing the level of autophagosomes in WM. In addition, PF11 also prevented microglia and astrocytes from activating in WM on the 28th day following 2VO. CONCLUSION: PF11 significantly ameliorates cognitive impairment and WMI, and the mechanism is at least partly related to lessening ALP dysfunction in WM by enhancing autophagy and reducing lysosomal defects in oligodendrocytes.

Aluminum oxyhydroxide-Poly(I:C) combination adjuvant with balanced immunostimulatory potentials for prophylactic vaccines.

The development of high-purity antigens promotes the urgent need of novel adjuvant with the capability to trigger high levels of immune response. Polyinosinic-polycytidylic (Poly(I:C)) is a synthetic double-stranded RNA (dsRNA) that can engage Toll-like receptor 3 (TLR3) to initiate immune responses. However, the Poly(I:C)-induced toxicity and inefficient delivery prevent its applications. In our study, combination adjuvants are formulated by aluminum oxyhydroxide nanorods (AlOOH NRs) and Poly(I:C), named Al-Poly(I:C), and the covalent interaction between the two components is further demonstrated. Al-Poly(I:C) mediates enhanced humoral and cellular immune responses in three antigen models, i.e., HBsAg virus-like particles (VLPs), human papilloma virus (HPV) VLPs and varicella-zoster virus (VZV) glycoprotein E (gE). Further mechanistic studies demonstrate that the dose and molecular weight (MW) of Poly(I:C) determine the physicochemical properties and adjuvanticity of the Al-Poly(I:C) combination adjuvants. Al-Poly(I:C) with higher Poly(I:C) dose promotes antigen-bearing dendritic cells (DCs) recruitment and B cells proliferation in lymph nodes. Al-Poly(I:C) formulated with higher MW Poly(I:C) induces higher activation of helper T cells, B cells, and CTLs. This study demonstrates that Al-Poly(I:C) potentiates the humoral and cellular responses in vaccine formulations. It offers insights for adjuvant design to meet the formulation requirements in both prophylactic and therapeutic vaccines.

Silicon or Calcium Doping Coordinates the Immunostimulatory Effects of Aluminum Oxyhydroxide Nanoadjuvants in Prophylactic Vaccines.

Aluminum salts still remain as the most popular adjuvants in marketed human prophylactic vaccines due to their capability to trigger humoral immune responses with a good safety record. However, insufficient induction of cellular immune responses limits their further applications. In this study, we prepare a library of silicon (Si)- or calcium (Ca)-doped aluminum oxyhydroxide (AlOOH) nanoadjuvants. They exhibit well-controlled physicochemical properties, and the dopants are homogeneously distributed in nanoadjuvants. By using Hepatitis B surface antigen (HBsAg) as the model antigen, doped AlOOH nanoadjuvants mediate higher antigen uptake and promote lysosome escape of HBsAg through lysosomal rupture induced by the dissolution of the dopant in the lysosomes in bone marrow-derived dendritic cells (BMDCs). Additionally, doped nanoadjuvants trigger higher antigen accumulation and immune cell activation in draining lymph nodes. In HBsAg and varicella-zoster virus glycoprotein E (gE) vaccination models, doped nanoadjuvants induce high IgG titer, activations of CD4+ and CD8+ T cells, cytotoxic T lymphocytes, and generations of effector memory T cells. Doping of aluminum salt-based adjuvants with biological safety profiles and immunostimulating capability is a potential strategy to mediate robust humoral and cellular immunity. It potentiates the applications of engineered adjuvants in the development of vaccines with coordinated immune responses.

The orientation of CpG conjugation on aluminum oxyhydroxide nanoparticles determines the immunostimulatory effects of combination adjuvants.

In subunit vaccines, aluminum salts (Alum) are commonly used as adjuvants, but with limited cellular immune responses. To overcome this limitation, CpG oligodeoxynucleotides (ODNs) have been used in combination with Alum. However, current combined usage of Alum and CpG is limited to linear mixtures, and the underlying interaction mechanism between CpG and Alum is not well understood. Thus, we propose to chemically conjugate Alum nanoparticles and CpG (with 5' or 3' end exposed) to design combination adjuvants. Our study demonstrates that compared to the 3'-end exposure, the 5'-end exposure of CpG in combination adjuvants (Al-CpG-5') enhances the activation of bone-marrow derived dendritic cells (BMDCs) and promotes Th1 and Th2 cytokine secretion. We used the SARS-CoV-2 receptor binding domain (RBD) and hepatitis B surface antigen (HBsAg) as model antigens to demonstrate that Al-CpG-5' enhanced antigen-specific antibody production and upregulated cytotoxic T lymphocyte markers. Additionally, Al-CpG-5' allows for coordinated adaptive immune responses even at lower doses of both CpG ODNs and HBsAg antigens, and enhances lymph node transport of antigens and activation of dendritic cells, promoting Tfh cell differentiation and B cell activation. Our novel Alum-CPG strategy points the way towards broadening the use of nanoadjuvants for both prophylactic and therapeutic vaccines.

Motor Imagery EEG Classification Based on a Weighted Multi-Branch Structure Suitable for Multisubject Data.

OBJECTIVE: Electroencephalogram (EEG) signal recognition based on deep learning technology requires the support of sufficient data. However, training data scarcity usually occurs in subject-specific motor imagery tasks unless multisubject data can be used to enlarge training data. Unfortunately, because of the large discrepancies between data distributions from different subjects, model performance could only be improved marginally or even worsened by simply training on multisubject data. METHOD: This article proposes a novel weighted multi-branch (WMB) structure for handling multisubject data to solve the problem, in which each branch is responsible for fitting a pair of source-target subject data and adaptive weights are used to integrate all branches or select branches with the largest weights to make the final decision. The proposed WMB structure was applied to six well-known deep learning models (EEGNet, Shallow ConvNet, Deep ConvNet, ResNet, MSFBCNN, and EEG_TCNet) and comprehensive experiments were conducted on EEG datasets BCICIV-2a, BCICIV-2b, high gamma dataset (HGD) and two supplementary datasets. RESULT: Superior results against the state-of-the-art models have demonstrated the efficacy of the proposed method in subject-specific motor imagery EEG classification. For example, the proposed WMB_EEGNet achieved classification accuracies of 84.14%, 90.23%, and 97.81% on BCICIV-2a, BCICIV-2b and HGD, respectively. CONCLUSION: It is clear that the proposed WMB structure is capable to make good use of multisubject data with large distribution discrepancies for subject-specific EEG classification.

Ultrasound-targeted semaglutide-loaded PEG-nanoliposomes microbubble destruction protects diabetic cardiomyopathy by activating PI3K/Akt/Nrf2 signaling pathway.

Objective: To investigate the ameliorative effect of Semaglutide-loaded PEG-nanoliposomes (Sem-PEG-lips) combined with ultrasound-targeted microbubble destruction (UTMD) on streptozotocin (STZ)-induced diabetic cardiomyopathy (DCM) in rodents and its potential mechanisms. Methods: Sem-PEG-lips were prepared by the reverse phase evaporation method. Fifty STZ-induced diabetic rats were randomly divided into DCM model group, Sem or Sem-PEG-lips alone treatment group, UTMD + Sem group and UTMD + Sem-PEG-lips group (n = 10), respectively, and used the healthy rats as normal control. During the 12-week intervention, the weight and blood glucose levels of all rats were recorded. Myocardial injury and fibrosis were observed by using H&E and Masson staining. The activity of antioxidant enzymes and the expression levels of oxidative stress-related signaling pathway markers in myocardial tissues were measured by ELISA and western blotting method, respectively. Results: Compared with DCM rats, the body weight and blood glucose levels of those in the UTMD + Sem-PEG-lips group were significantly increased and decreased, respectively (both p < 0.05). The results of H&E and Masson staining showed that myocardial fibrosis and apoptosis were both significantly improved in combination group (both p < 0.001). Further results of ELISA and Western blot analysis showed that the activity of antioxidant enzymes in ones received combination therapy were significantly higher than that in DCM model group (all p < 0.001), and the expression of PI3K/Akt/Nrf2 signaling pathway related proteins were significantly up-regulated (all p < 0.001), and all these changes were reversed by the treatment of PI3K inhibitor. results. Conclusion: UTMD combined Sem-PEG-lips can reduce the oxidative stress of myocardial tissue in DCM rats by activating PI3K/Akt/Nrf2 signaling pathway, thereby improving diabetic myocardial injury.

Combination therapy of irreversible electroporation and cytokine-induced killer cells for treating mice bearing panc02 pancreatic-cancer xenografts.

The current study aimed to investigate the antitumor effects and potent mechanism of cytokine-induced killer (CIK) cells combined with irreversible electroporation (IRE) via Panc02 cell-bearing mouse model in vivo. CIK cells were isolated from the spleens of Panc02 pancreatic-cancer (PC) subcutaneous-xenograft model and the proportion of different lymphocytes was also determined. The antitumor effect of the combination of IRE and CIK cells in a PC subcutaneous-xenograft model was also investigated. The proportion of cells that were positive for CD3+CD8+ and the proportion of CD3+CD56+ cells were both significantly increased after 21 days of in vitro culture. Combined treatment of IRE and CIK cell significantly inhibited tumor growth and increased the survival rate of Panc02 cell-bearing mice. Furthermore, infiltration of lymphocytes into tumor tissue was significantly increased by this combination therapy compared with the untreated group or monotherapy group. In addition, IRE significantly enhanced the expression of chemokine receptors elicited by CIK cells. In conclusion, IRE combined with CIK cells showed superior antitumor efficacy in a PC xenograft model, which we attributed to the promotion of lymphocytic infiltration, as well as to upregulation of chemokine receptor expression and the regulators of CIK cell proliferation.

Influence of SPIO labelling on the function of BMSCs in chemokine receptors expression and chemotaxis.

Bone marrow-derived mesenchymal stem cells (BMSCs) are increasingly being used in bone marrow transplantation (BMT) to enable homing of the allogeneic hematopoietic stem cells and suppress acute graft versus host disease (aGVHD). The aim of this study was to optimize the labelling of BMSCs with superparamagnetic iron oxide particles (SPIOs), and evaluate the impact of the SPIOs on the biological characteristics, gene expression profile and chemotaxis function of the BMSCs. The viability and proliferation rates of the SPIO-labeled BMSCs were analyzed by trypan blue staining and CCK-8 assay respectively, and the chemotaxis function was evaluated by the transwell assay. The expression levels of chemokine receptors were measured by RT-PCR and flow cytometry. The SPIOs had no effect on the viability of the BMSCs regardless of the labelling concentration and culture duration. The labelling rate of the cells was higher when cultured for 48 h with the SPIOs. Furthermore, cells labeled with 25 µg/ml SPIOs for 48 h had the highest proliferation rates, along with increased expression of chemokine receptor genes and proteins. However, there was no significant difference between the chemotaxis function of the labeled and unlabeled BMSCs. To summarize, labelling BMSCs with 25 µg/ml SPIOs for 48h did not affect their biological characteristics and chemotaxis function, which can be of significance for in vivo applications.

Enhancement of oligodendrocyte autophagy alleviates white matter injury and cognitive impairment induced by chronic cerebral hypoperfusion in rats.

Cognitive impairment caused by chronic cerebral hypoperfusion (CCH) is associated with white matter injury (WMI), possibly through the alteration of autophagy. Here, the autophagy-lysosomal pathway (ALP) dysfunction in white matter (WM) and its relationship with cognitive impairment were investigated in rats subjected to two vessel occlusion (2VO). The results showed that cognitive impairment occurred by the 28th day after 2VO. Injury and autophagy activation of mature oligodendrocytes and neuronal axons sequentially occurred in WM by the 3rd day. By the 14th day, abnormal accumulation of autophagy substrate, lysosomal dysfunction, and the activation of mechanistic target of rapamycin (MTOR) pathway were observed in WM, paralleled with mature oligodendrocyte death. This indicates autophagy activation was followed by ALP dysfunction caused by autophagy inhibition or lysosomal dysfunction. To target the ALP dysfunction, enhanced autophagy by systemic rapamycin treatment or overexpression of Beclin1 (BECN1) in oligodendrocytes reduced mature oligodendrocyte death, and subsequently alleviated the WMI and cognitive impairment after CCH. These results reveal that early autophagy activation was followed by ALP dysfunction in WM after 2VO, which was associated with the aggravation of WMI and cognitive impairment. This study highlights that alleviating ALP dysfunction by enhancing oligodendrocyte autophagy has benefits for cognitive recovery after CCH.

Artificial-intelligence-based computed tomography histogram analysis predicting tumor invasiveness of lung adenocarcinomas manifesting as radiological part-solid nodules.

Background: Tumor invasiveness plays a key role in determining surgical strategy and patient prognosis in clinical practice. The study aimed to explore artificial-intelligence-based computed tomography (CT) histogram indicators significantly related to the invasion status of lung adenocarcinoma appearing as part-solid nodules (PSNs), and to construct radiomics models for prediction of tumor invasiveness. Methods: We identified surgically resected lung adenocarcinomas manifesting as PSNs in Peking University People's Hospital from January 2014 to October 2019. Tumors were categorized as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) by comprehensive pathological assessment. The whole cohort was randomly assigned into a training (70%, n=832) and a validation cohort (30%, n=356) to establish and validate the prediction model. An artificial-intelligence-based algorithm (InferRead CT Lung) was applied to extract CT histogram parameters for each pulmonary nodule. For feature selection, multivariate regression models were built to identify factors associated with tumor invasiveness. Logistic regression classifier was used for radiomics model building. The predictive performance of the model was then evaluated by ROC and calibration curves. Results: In total, 299 AIS/MIAs and 889 IACs were included. In the training cohort, multivariate logistic regression analysis demonstrated that age [odds ratio (OR), 1.020; 95% CI, 1.004-1.037; p=0.017], smoking history (OR, 1.846; 95% CI, 1.058-3.221; p=0.031), solid mean density (OR, 1.014; 95% CI, 1.004-1.024; p=0.008], solid volume (OR, 5.858; 95% CI, 1.259-27.247; p = 0.037), pleural retraction sign (OR, 3.179; 95% CI, 1.057-9.559; p = 0.039), variance (OR, 0.570; 95% CI, 0.399-0.813; p=0.002), and entropy (OR, 4.606; 95% CI, 2.750-7.717; p<0.001) were independent predictors for IAC. The areas under the curve (AUCs) in the training and validation cohorts indicated a better discriminative ability of the histogram model (AUC=0.892) compared with the clinical model (AUC=0.852) and integrated model (AUC=0.886). Conclusion: We developed an AI-based histogram model, which could reliably predict tumor invasiveness in lung adenocarcinoma manifesting as PSNs. This finding would provide promising value in guiding the precision management of PSNs in the daily practice.