PGC-1α in the hippocampus mediates depressive-like and stress-coping behaviours and regulates excitatory synapses in the dentate gyrus in mice.

Decreased hippocampal synaptic plasticity is an important pathological change in stress-related mood disorders, including major depressive disorder. However, the underlying mechanism is unclear. PGC-1α, a transcriptional coactivator, is a key factor in synaptic plasticity. We investigated the relationships between changes in hippocampal PGC-1α expression and depressive-like and stress-coping behaviours, and whether they are related to hippocampal synapses. Adeno-associated virus was used to alter hippocampal PGC-1α expression in male C57BL/6 mice. The sucrose preference test and forced swimming test were used to assess their depressive-like and stress-coping behaviours, respectively. Immunohistochemistry and stereology were used to calculate the total number of excitatory synapses in each hippocampal subregion (the cornu ammonis (CA) 1, CA3, and dentate gyrus). Immunofluorescence was used to visualize the changes in dendritic structure. Western blotting was used to detect the expression of hippocampal PGC-1α and mitochondrial-associated proteins, such as UCP2, NRF1 and mtTFAs. Our results showed that mice with downregulated PGC-1α expression in the hippocampus exhibited depressive-like and passive stress-coping behaviours, while mice with upregulated PGC-1α in the hippocampus exhibited increased stress-coping behaviours. Moreover, the downregulation of hippocampal PGC-1α expression resulted in a decrease in the number of excitatory synapses in the DG and in the protein expression of UCP2 in the hippocampus. Alternatively, upregulation of hippocampal PGC-1α yielded the opposite results. This suggests that hippocampal PGC-1α is involved in regulating depressive-like and stress-coping behaviours and modulating the number of excitatory synapses in the DG. This provides new insight for the development of antidepressants.

Running exercise improves astrocyte loss, morphological complexity and astrocyte-contacted synapses in the hippocampus of CUS-induced depression model mice.

Although the antidepressant effects of running exercise have been widely reported, further research is still needed to determine the structural bases for these effects. Astrocyte processes physically contact many synapses and directly regulate the numbers of synapses, but it remains unclear whether running exercise can modulate astrocyte morphological complexity and astrocyte-contacted synapses in the hippocampus of the mice with depressive-like behavior. Male C57BL/6 J mice underwent four weeks of running exercise after four weeks of chronic unpredictable stress (CUS). The sucrose preference test (SPT), tail suspension test (TST) and forced swim test (FST) were used to assess anhedonia in mice. Western blotting was used to measure the expression of astrocyte- and synapse-related proteins. Immunofluorescence and 3D reconstruction were used to quantify the density and morphology of astrocytes, and astrocyte-contacted synapses in each hippocampal subregion. Four weeks of running exercise alleviated depressive-like symptoms in mice. The expression of astrocyte- and synapse-related proteins in the hippocampus; astrocyte process lengths, process numbers, and dendritic arborization; and the number of astrocyte-contacted PSD95 positive synapses in the CA2-3 and DG regions were significantly decreased in the mice with depressive-like behavior, and running exercise successfully reserved these changes. Running exercise improved the decreases in astrocyte morphological complexity and astrocyte-contacted PSD95 positive synapses in the CA2-3 and DG regions of the mice with depressive-like behavior, suggesting that the physical interactions between astrocytes and synapses can be increased by running exercise, which might be an important structural basis for the antidepressant effects of running exercise.

VSG-GAN: A high-fidelity image synthesis method with semantic manipulation in retinal fundus image.

In recent years, advancements in retinal image analysis, driven by machine learning and deep learning techniques, have enhanced disease detection and diagnosis through automated feature extraction. However, challenges persist, including limited data set diversity due to privacy concerns and imbalanced sample pairs, hindering effective model training. To address these issues, we introduce the vessel and style guided generative adversarial network (VSG-GAN), an innovative algorithm building upon the foundational concept of GAN. In VSG-GAN, a generator and discriminator engage in an adversarial process to produce realistic retinal images. Our approach decouples retinal image generation into distinct modules: the vascular skeleton and background style. Leveraging style transformation and GAN inversion, our proposed hierarchical variational autoencoder module generates retinal images with diverse morphological traits. In addition, the spatially adaptive denormalization module ensures consistency between input and generated images. We evaluate our model on MESSIDOR and RITE data sets using various metrics, including structural similarity index measure, inception score, Fréchet inception distance, and kernel inception distance. Our results demonstrate the superiority of VSG-GAN, outperforming existing methods across all evaluation assessments. This underscores its effectiveness in addressing data set limitations and imbalances. Our algorithm provides a novel solution to challenges in retinal image analysis by offering diverse and realistic retinal image generation. Implementing the VSG-GAN augmentation approach on downstream diabetic retinopathy classification tasks has shown enhanced disease diagnosis accuracy, further advancing the utility of machine learning in this domain.

Running exercise alleviates hippocampal neuroinflammation and shifts the balance of microglial M1/M2 polarization through adiponectin/AdipoR1 pathway activation in mice exposed to chronic unpredictable stress.

Running exercise has been shown to alleviate depressive symptoms. However, the mechanism underlying the antidepressant effects of running exercise is not fully understood. The imbalance of M1/M2 microglia phenotype/polarization and concomitant dysregulation of neuroinflammation play crucial roles in the pathogenesis of depression. Running exercise increases circulating levels of adiponectin which is known to cross the blood‒brain barrier and suppress inflammatory responses. AdipoR1 is an adiponectin receptor that is involved in regulating microglial phenotypes and activation states. However, whether running exercise regulates hippocampal microglial phenotypes and neuroinflammation through adiponectin/AdipoR1 to exert its antidepressant effects remains unclear. In the current study, 4 weeks of running exercise significantly alleviated the depressive-like behaviors of chronic unpredictable stress (CUS)-exposed mice. Moreover, running exercise decreased the microglial numbers and altered microglial morphology in three subregions of the hippocampus to restore the M1/M2 balance; these effects were accompanied by regulation of pro-/anti-inflammatory cytokine production and secretion in CUS-exposed mice. These effects may involve elevation of peripheral tissue (adipose tissue and muscle) and plasma adiponectin levels, and hippocampal AdipoR1 levels as well as activation of the AMPK-NF-κB/STAT3 signaling pathway by running exercise. When an adeno-associated virus was used to knock down hippocampal AdipoR1, mice showed depressive-like behaviors and alterations in microglia and inflammatory factor expression in the hippocampus that were similar to those observed in CUS-exposed mice. Together, these results suggest that running exercise maintains the M1/M2 balance and inhibits neuroinflammation in the hippocampus of CUS-exposed mice. These effects might occur via adiponectin/AdipoR1-mediated activation of the AMPK-NF-κB/STAT3 signaling pathway.

Preoperative evaluation of microvascular invasion in hepatocellular carcinoma with a radiological feature-based nomogram: a bi-centre study.

PURPOSE: To develop a nomogram for preoperative assessment of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) based on the radiological features of enhanced CT and to verify two imaging techniques (CT and MRI) in an external centre. METHOD: A total of 346 patients were retrospectively included (training, n = 185, CT images; external testing 1, n = 90, CT images; external testing 2, n = 71, MRI images), including 229 MVI-negative patients and 117 MVI-positive patients. The radiological features and clinical information of enhanced CT images were analysed, and the independent variables associated with MVI in HCC were determined by logistic regression analysis. Then, a nomogram prediction model was constructed. External validation was performed on CT (n = 90) and MRI (n = 71) images from another centre. RESULTS: Among the 23 radiological and clinical features, size, arterial peritumoral enhancement (APE), tumour margin and alpha-fetoprotein (AFP) were independent influencing factors for MVI in HCC. The nomogram integrating these risk factors had a good predictive effect, with AUC, specificity and sensitivity values of 0.834 (95% CI: 0.774-0.895), 75.0% and 83.5%, respectively. The AUC values of external verification based on CT and MRI image data were 0.794 (95% CI: 0.700-0.888) and 0.883 (95% CI: 0.807-0.959), respectively. No statistical difference in AUC values among training set and testing sets was found. CONCLUSION: The proposed nomogram prediction model for MVI in HCC has high accuracy, can be used with different imaging techniques, and has good clinical applicability.

Diagnostic accuracy of MRI for assessing lymphovascular space invasion in endometrial carcinoma: a meta-analysis.

BACKGROUND: The lymphovascular space invasion (LVSI) status of endometrial cancer (EC) has guiding significance in lymph node dissection. However, LVSI can only be obtained after surgery. Researchers have tried to extract the information of LVSI using magnetic resonance imaging (MRI). PURPOSE: To evaluate the ability of preoperative MRI to predict the LVSI status of EC. MATERIAL AND METHODS: A search was conducted by using the PubMed/MEDLINE, EMBASE, Web of Science, and the Cochrane Library databases. Articles were included according to the criteria. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2. A bivariate random effects model was used to obtain pooled summary estimates, heterogeneity, and the area under the summary receiver operating characteristic curve (AUC). A subgroup analysis was performed to identify sources of heterogeneity. RESULTS: A total of nine articles (814 patients) were included. The risk of bias was low or unclear for most studies, and the applicability concerns were low or unclear for all studies. The summary AUC values as well as pooled sensitivity and specificity of LVSI status in EC were 0.82, 73%, and 77%, respectively. According to the subgroup analysis, radiomics/non-radiomics features, country/region, sample size, age, MR manufacturer, magnetic field, scores of risk bias, and scores of applicability concern may have caused heterogeneity. CONCLUSION: Our meta-analysis showed that MRI has moderate diagnostic efficacy for LVSI status in EC. Large-sample, uniformly designed studies are needed to verify the true value of MRI in assessing LVSI.

Antagonizing LINGO-1 reduces activated microglia and alleviates dendritic spine loss in the hippocampus of APP/PS1 transgenic mice.

In Alzheimer's disease (AD), microglia are involved in synaptic pruning and mediate synapse loss. LINGO-1 is a negative regulator of nerve growth, and whether antagonizing LINGO-1 can attenuate synaptic pruning by microglia and rescue dendritic spines in the hippocampus in AD is still unclear. On this basis, the anti-LINGO-1 antibody, which binds to LINGO-1 protein and antagonizes the effects of LINGO-1, was administered to 10-month-old APP/PS1 transgenic mice for 2 months. The Morris water maze test, immunohistochemical and stereological methods, immunofluorescence and 3D reconstruction were used. Compared to wild-type mice, APP/PS1 transgenic mice had worse performance on behavioral tests, fewer dendritic spines but more microglia in the hippocampus. Meanwhile, the microglia in APP/PS1 transgenic mice had more branches of medium length (4-6 µm) and a cell body area with greater variability. Moreover, APP/PS1 transgenic mice had more postsynaptic termini colocalized with microglia in the hippocampus than wild-type mice. The anti-LINGO-1 antibody significantly reversed these changes in AD, indicating that the anti-LINGO-1 antibody can improve hippocampus-dependent learning and memory abilities and effectively rescue dendritic spines in the hippocampus of AD mice and that microglia might participate in this progression in AD. These results provide a scientific basis for further studying the mechanism of the anti-LINGO-1 antibody in AD and help to elucidate the role of LINGO-1 in the treatment of AD.

Identification of DNA Damage Repair Gene Signature as a Novel Prognostic Marker in Glioblastoma Multiforme.

BACKGROUND: The efficacy of treatment of glioblastoma multiforme (GBM) is limited. The effect of DNA damage repair is an important factor. METHODS: Expression data were downloaded from The Cancer Genome Atlas (training dataset) and the Gene Expression Omnibus (validation dataset) databases. Univariate Cox regression analysis and the least absolute shrinkage and selection operator were used to construct a DNA damage response (DDR) gene signature. Receiver operating characteristic curve analysis and Kaplan-Meier curve analysis were used to estimate the prognostic value of the risk signature. Moreover, consensus clustering analysis was used to investigate the potential subtypes of GBM according to DDR expression. RESULTS: We constructed a 3-DDR-related gene signature through the survival analysis. The Kaplan-Meier curve analysis suggested that patients in the low-risk group have significantly better survival outcomes compared with the high-risk group in the training and external validation datasets. The results from the receiver operating characteristic curve analysis indicated that the risk model has high prognostic value in the training and external validation datasets. Moreover, 3 stable molecular subtypes were identified and validated in the Gene Expression Omnibus and The Cancer Genome Atlas databases according to the expression of the DNA repair gene. The microenvironment and immunity of GBM were further investigated and showed that cluster 2 had higher immunity and a higher immune score compared with clusters 1 and 3. CONCLUSIONS: The DNA damage repair-related gene signature was an independent and powerful prognostic biomarker in GBM. Knowledge of the GBM subtypes could have important implications in the subclassification of GBM.

Qualitative and quantitative wall enhancement associated with unstable intracranial aneurysms: a meta-analysis.

BACKGROUND: Unstable intracranial aneurysms (UIAs) are more likely to rupture and cause serious consequences. Evaluating the stability of unruptured aneurysms facilitates clinical management stratification. PURPOSE: To compare and evaluate the predictive performance of qualitative and quantitative wall enhancement (aneurysmal wall enhancement [AWE], circumferential aneurysmal wall enhancement [CAWE], wall enhancement ratio [WER]) on high-resolution magnetic resonance imaging (MRI) of the vessel wall to predict the presence of UIA. MATERIAL AND METHODS: Original articles describing the depiction of aneurysmal wall enhancement on 3.0-T or 1.5-T high-resolution vessel wall imaging were retrieved from the Web of Science, Medline/PubMed, the Cochrane Library, and EMBASE databases up to 15 February 2022. The combined sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUC) were calculated, and meta-regression analysis was performed. RESULTS: In total, 12 original articles involving 1619 intracranial aneurysms (IAs) were included. The combined sensitivity and specificity of AWE, CAWE, and WER were 91% and 67%, 59% and 83%, and 86% and 75%, respectively, in the diagnosis of UIA. The summary AUC values of these items were, in order from high to low, 0.88 (WER), 0.84 (AWE), and 0.77 (CAWE), and the differences among them were significant (z = 2.976, P = 0.003 and z = 2.950, P = 0.003). The meta-regression analysis identified average size and 2D/3D magnetic imaging technology as possible sources of heterogeneity. CONCLUSION: Qualitative and quantitative wall enhancement showed moderate accuracy in predicting UIA, and WER had the highest accuracy among them in this meta-analysis. Two covariates were found to explain the heterogeneity.

Analysis of clinical predictors of kidney diseases in type 2 diabetes patients based on machine learning.

BACKGROUND: The heterogeneity of Type 2 Diabetes Mellitus (T2DM) complicated with renal diseases has not been fully understood in clinical practice. The purpose of the study was to propose potential predictive factors to identify diabetic kidney disease (DKD), nondiabetic kidney disease (NDKD), and DKD superimposed on NDKD (DKD + NDKD) in T2DM patients noninvasively and accurately. METHODS: Two hundred forty-one eligible patients confirmed by renal biopsy were enrolled in this retrospective, analytical study. The features composed of clinical and biochemical data prior to renal biopsy were extracted from patients' electronic medical records. Machine learning algorithms were used to distinguish among different kidney diseases pairwise. Feature variables selected in the developed model were evaluated. RESULTS: Logistic regression model achieved an accuracy of 0.8306 ± 0.0057 for DKD and NDKD classification. Hematocrit, diabetic retinopathy (DR), hematuria, platelet distribution width and history of hypertension were identified as important risk factors. Then SVM model allowed us to differentiate NDKD from DKD + NDKD with accuracy 0.8686 ± 0.052 where hematuria, diabetes duration, international normalized ratio (INR), D-Dimer, high-density lipoprotein cholesterol were the top risk factors. Finally, the logistic regression model indicated that DD-dimer, hematuria, INR, systolic pressure, DR were likely to be predictive factors to identify DKD with DKD + NDKD. CONCLUSION: Predictive factors were successfully identified among different renal diseases in type 2 diabetes patients via machine learning methods. More attention should be paid on the coagulation factors in the DKD + NDKD patients, which might indicate a hypercoagulable state and an increased risk of thrombosis.

Can a proposed double branch multimodality-contribution-aware TripNet improve the prediction performance of the microvascular invasion of hepatocellular carcinoma based on small samples?

Objectives: To evaluate the potential improvement of prediction performance of a proposed double branch multimodality-contribution-aware TripNet (MCAT) in microvascular invasion (MVI) of hepatocellular carcinoma (HCC) based on a small sample. Methods: In this retrospective study, 121 HCCs from 103 consecutive patients were included, with 44 MVI positive and 77 MVI negative, respectively. A MCAT model aiming to improve the accuracy of deep neural network and alleviate the negative effect of small sample size was proposed and the improvement of MCAT model was verified among comparisons between MCAT and other used deep neural networks including 2DCNN (two-dimentional convolutional neural network), ResNet (residual neural network) and SENet (squeeze-and-excitation network), respectively. Results: Through validation, the AUC value of MCAT is significantly higher than 2DCNN based on CT, MRI, and both imaging (P < 0.001 for all). The AUC value of model with single branch pretraining based on small samples is significantly higher than model with end-to-end training in CT branch and double branch (0.62 vs 0.69, p=0.016, 0.65 vs 0.83, p=0.010, respectively). The AUC value of the double branch MCAT based on both CT and MRI imaging (0.83) was significantly higher than that of the CT branch MCAT (0.69) and MRI branch MCAT (0.73) (P < 0.001, P = 0.03, respectively), which was also significantly higher than common-used ReNet (0.67) and SENet (0.70) model (P < 0.001, P = 0.005, respectively). Conclusion: A proposed Double branch MCAT model based on a small sample can improve the effectiveness in comparison to other deep neural networks or single branch MCAT model, providing a potential solution for scenarios such as small-sample deep learning and fusion of multiple imaging modalities.

Diagnostic Accuracy of the Apparent Diffusion Coefficient for Microvascular Invasion in Hepatocellular Carcinoma: A Meta-analysis.

Background and Aims: Microvascular invasion (MVI) is a major risk factor for the early recurrence of hepatocellular carcinoma (HCC) and it seriously worsens the prognosis. Accurate preoperative evaluation of the presence of MVI could greatly benefit the treatment management and prognosis prediction of HCC patients. The study aim was to evaluate the diagnostic performance of the apparent diffusion coefficient (ADC), a quantitative parameter for the preoperative diagnosis MVI in HCC patients. Methods: Original articles about diffusion-weighted imaging (DWI) and/or intravoxel incoherent motion (IVIM) conducted on a 3.0 or 1.5 Tesla magnetic resonance imaging (MRI) system indexed through January 17, 2021were collected from MEDLINE/PubMed, Web of Science, EMBASE, and the Cochrane Library. Methodological quality was evaluated using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The pooled sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUROC) were calculated, and meta-regression analysis was performed using a bivariate random effects model through a meta-analysis. Results: Nine original articles with a total of 988 HCCs were included. Most studies had low bias risk and minimal applicability concerns. The pooled sensitivity, specificity and AUROC of the ADC value were 73%, 70%, and 0.78, respectively. The time interval between the index test and the reference standard was identified as a possible source of heterogeneity by subgroup meta-regression analysis. Conclusions: Meta-analysis showed that the ADC value had moderate accuracy for predicting MVI in HCC. The time interval accounted for the heterogeneity.

Activation of liver X receptors protects oligodendrocytes in CA3 of stress-induced mice.

Depression is a complex disorder that is associated with various structural abnormalities. Oligodendrocyte (OL) dysfunction is associated with the pathogenesis of depression and the promotion of hippocampal oligodendrocyte maturation and myelination could be a novel therapeutic strategy for ameliorating depressive behaviors. Recent studies have shown that activation of liver X receptors (LXRs) by GW3965 improves depressive phenotypes, but the effects of GW3965 on OL function and myelination in the hippocampus of depression remain relatively unclear. To address this issue, we investigated the effects of GW3965 on mature OL in the hippocampus and on the myelin sheaths of mice subjected to chronic unpredictable stress (CUS). Behavioral tests were performed to assess depressive behaviors. Then, the number of mature OLs (CC1+) in each hippocampal subregion was precisely quantified with immunohistochemical and stereological methods, and the density of newborn mature OLs (BrdU+/Olig2+/CC1+ cells) in each hippocampal subregion was quantified with immunofluorescence. In addition, myelin basic protein (MBP) staining intensity in the cornu ammonis 3 (CA3) region was assessed by using immunofluorescence. We found that both the number of CC1+ OLs and the density of BrdU+/Olig2+/CC1+ cells were obviously decreased in each hippocampal subregion of mice subjected to CUS, and 4 weeks of GW3965 treatment reversed these effects only in the CA3 region. Furthermore, the decreased MBP expression in the CA3 region of mice subjected to CUS was ameliorated by GW3965 treatment. Collectively, these results suggested that improvement of OL maturation and enhancement of myelination may be structural mechanisms underlying the antidepressant effects of LXR agonists.

Positive effects of running exercise on astrocytes in the medial prefrontal cortex in an animal model of depression.

Depression is one of the most common mental illnesses and seriously affects all aspects of life. Running exercise has been suggested to prevent or alleviate the occurrence and development of depression; however, the underlying mechanisms of these effects remain unclear. Independent studies have indicated that astrocytes play essential roles and that the medial prefrontal cortex (mPFC) is an important brain region involved in the pathology underlying depression. However, it is unknown whether running exercise achieves antidepressant effects by affecting the number of astrocytes and glutamate transport function in the mPFC. Here, animal models of depression were established using chronic unpredictable stress (CUS), and depression-like behavior was assessed by the sucrose preference test. After successfully establishing the depression model, experimental animals performed running exercise. Glial fibrillary acidic protein-positive (GFAP+ ) cell number in the mPFC was precisely quantified using immunohistochemical and stereological methods, and the densities of bromodeoxyuridine-positive (BrdU+ ) and BrdU+ /GFAP+ cells in the mPFC were measured using a semiquantitative immunofluorescence assay. Changes in glutamate transporter gene expression in mPFC astrocytes were detected by mRNA sequencing and qRT-PCR. We found that running exercise reversed CUS-induced decreases in sucrose preference, increased astrocyte number and the density of newborn astrocytes, and reversed decreases in gene expression levels of GFAP, S100b, and the glutamate transporters GLT-1 and GLAST in the mPFC of CUS animals. These results suggested that changes in astrocyte number and glutamate transporter function may be potential meditators of the effects of running exercise in the treatment of depression.

Intraosseous Hemangioma of the Ethmoid Sinus: A Case Report.

Intraosseous hemangiomas usually occur in the vertebrae and skull bones, whereas those arising within the nasal cavity are exceedingly rare. Here, we describe the case of a 40-year-old woman with nasal congestion who presented to our hospital with a tumor located in the left nasal cavity. Unenhanced paranasal computed tomography revealed an approximately 3 cm large mass originating from the anterior wall of the ethmoid sinus. Pre-operative imaging failed to reveal the etiology of the mass. The tumor was successfully resected using a trans-nasal endoscopic approach without pre-operative embolization. No complications occurred during the post-operative period, and there was no evidence of recurrence at the 3-month and 6-month follow-up. Histological examination of the resected specimen showed endothelium-lined blood-filled vascular spaces within the bony trabecule, suggesting a pattern typical of intraosseous cavernous hemangioma. Thus, although intraosseous hemangiomas of the nasal cavity are extremely rare, they must be considered when a bony mass is detected in the nasal cavity.

Synergistic effect of Si concentration and distribution on ferroelectric properties optimization of Si:HfO2ferroelectric thin films.

In this paper, a phase-field model of Si-doped hafnium oxide-based ferroelectric thin films is established. And then, the synergistic effect of Si concentration and distribution on ferroelectric properties optimization of Si:HfO2ferroelectric thin films is studied with the proposed model. It is found that no matter how Si dopant is distributed in the film, the volume fraction of the ferroelectric phase in the film increases first and then decreases with the increase of Si concentration. However, compared with the uniform distribution, the layered distribution is more likely to great improve ferrelectric properties. When Si dopant is uniformly distributed in the film, the highest remanent polarization value that the film can obtain via Si concentration modulation is 38.7µC cm-2, and the corresponding Si concentration is 3.8 cat%, which is consistent with the experimental results. When Si dopant is layered in the film, and the concentration difference between the Si-rich and Si-poor layers is 7.6%, in the Si concentration range of 3.6 cat%-3.8 cat%, the residual polarization of the film reaches 46.4-46.8µC cm-2, which is 20% higher than that when Si dopant are evenly distributed in the film. The above results show that selecting the Si layered distribution mode and controlling the concentration difference between Si-rich and Si-poor layers in an appropriate range can greatly improve the films' ferroelectric properties and broaden the Si concentration optimization range of the ferroelectric properties of the films. The result provides further theoretical guidance on using Si doping to adjust the ferroelectric properties of hafnium oxide-based films.

The liver X receptors agonist GW3965 attenuates depressive-like behaviors and suppresses microglial activation and neuroinflammation in hippocampal subregions in a mouse depression model.

Liver X receptors (LXRs) have recently been reported to be novel and potential targets for the reversal of depressive-like behaviors, but the mechanism remains unclear. Hippocampal neuroinflammation and impairment of the normal structure and function of microglia are closely associated with depression. To investigate the effects of LXRs agonist (GW3965) on neuroinflammation and microglia in the hippocampal formation of mice with chronic unpredictable stress (CUS)-induced depression, depressive-like behaviors were evaluated by behavioral tests, hippocampal LXRs gene expression were evaluated by qRT-PCR, the protein expression levels of interleukin-1ß, tumor necrosis factor-α, inducible nitric oxide synthase, nuclear factor kappa B, and cluster of differentiation 206 were estimated by western blotting, modern stereological methods were used to precisely quantify the total number of microglia in each hippocampal subregion, and immunofluorescence was used to detect the density of activated microglia and the morphology of microglia. We found that GW3965 alleviated the depressive-like behavior induced by CUS, reversed the decrease in hippocampal LXRα and LXRß induced by CUS, increased the protein expression of pro-inflammatory factors, and decreased the protein expression of antiinflammatory factors induced by CUS. Moreover, CUS intervention significantly increased the number of microglia in the CA1 region, CA2/3 region, and dentate gyrus and the density of activated microglia in the CA2/3 region and dentate gyrus and significantly decreased the endpoints of microglial branches and process length of microglia in the dentate gyrus, while 4 weeks of injections with GW3965 reversed these changes. These findings suggest that regulating the number, activated state, and morphology of microglia in hippocampal subregions might be an important basis for the antidepressant effects of LXRs.

Diagnostic performance of imaging features in the HBP of gadoxetate disodium-enhanced MRI for microvascular invasion in hepatocellular carcinoma: a meta-analysis.

BACKGROUND: Microvascular invasion (MVI) is a major risk factor for early recurrence in patients with hepatocellular carcinoma (HCC). Preoperative accurate evaluation of the presence of MVI could enormously benefit its treatment and prognosis. PURPOSE: To evaluate and compare the diagnostic performance of two imaging features (non-smooth tumor margin and peritumor hypointensity) in the hepatobiliary phase (HBP) to preoperatively diagnose the presence of MVI in HCC. MATERIAL AND METHODS: Original articles were collected from Medline/PubMed, Web of Science, EMBASE, and the Cochrane Library up to 17 January 2021 linked to gadoxetate disodium-enhanced magnetic resonance imaging (MRI) on 1.5 or 3.0 T. The pooled sensitivity, specificity, and summary area under the receiver operating characteristic curve (AUC) were calculated and meta-regression analyses were performed. RESULTS: A total of 14 original articles involving 2193 HCCs were included. The pooled sensitivity and specificity of non-smooth tumor margin and peritumor hypointensity were 73% and 61%, and 43% and 90%, respectively, for the diagnosis of MVI in HCC. The summary AUC of non-smooth tumor margin (0.74) was comparable to that of peritumor hypointensity (0.76) (z = 0.693, P = 0.488). The meta-regression analysis identified four covariates as possible sources of heterogeneity: average size; time interval between index test and reference test; blindness to index test during reference test; and risk of bias score. CONCLUSION: This meta-analysis showed moderate and comparable accuracy for predicting MVI in HCC using either non-smooth tumor margin or peritumor hypointensity in HBP. Four discovered covariates accounted for the heterogeneity.

Study on the phase transition dynamics of HfO2-based ferroelectric films under ultrafast electric pulse.

Wake-up effect and fatigue in HfO2-based ferroelectric films are closely related to the phase transition dynamics of the film subjected to ultrafast electric pulses. Here, we establish a multiphase coexistence phase field dynamics model for HfO2-based ferroelectric films in the ultrafast time scale and study the effects of the amplitude, width and frequency of the electric pulse on the phase transition dynamics. Based on the simulation results, we obtain the analytical equation of the volume fraction of switchedc-domains under low fields as a function of pulse duration. And we found that monoclinic phase can transform into ferroelectricc-domains under high amplitude electric field (E⩾ 2.8 MV cm-1). The electric pulse duration affects the film's retention properties. When the duration of the electric pulse is less than 1.2 ns or longer than 1.8 ns, the ferroelectricc-domains will respectively invert into other phases or increase cumulatively after removing the electric field. The frequency of cyclic pulse is related to the degree of wake up effect. The lower the pulse frequency is, the more obvious the 'wake up' effect is.

Anti-LINGO-1 antibody ameliorates cognitive impairment, promotes adult hippocampal neurogenesis, and increases the abundance of CB1R-rich CCK-GABAergic interneurons in AD mice.

In view of the negative regulatory effect of leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor-interacting protein 1 (LINGO-1) on neurons, an antibody against LINGO-1 (anti-LINGO-1 antibody) was herein administered to 10-month-old APP/PS1 transgenic Alzheimer's disease (AD) mice for 2 months as an experimental intervention. Behavioral, stereology, immunohistochemistry and immunofluorescence analyses revealed that the anti-LINGO-1 antibody significantly improved the cognitive abilities, promoted adult hippocampal neurogenesis (AHN), decreased the amyloid beta (Aß) deposition, enlarged the hippocampal volume, and increased the numbers of total neurons and GABAergic interneurons, including GABAergic and CCK-GABAergic interneurons rich in cannabinoid type 1 receptor (CB1R), in the hippocampus of AD mice. In contrast, this intervention significantly reduced the number of GABAergic interneurons expressing LINGO-1 and CB1R in the hippocampus of AD mice. More importantly, we also found a negative correlation between LINGO-1 and CB1R on GABAergic interneurons in the hippocampus of AD mice, while the anti-LINGO-1 antibody reversed this relationship. These results indicated that LINGO-1 plays an important role in the process of hippocampal neuron loss in AD mice and that antagonizing LINGO-1 can effectively prevent hippocampal neuron loss and promote AHN. The improvement in cognitive abilities may be attributed to the improvement in AHN, and in the numbers of GABAergic interneurons and CCK-GABAergic interneurons rich in CB1Rs in the hippocampus of AD mice induced by the anti-LINGO-1 antibody. Collectively, the double target effect (LINGO-1 and CB1R) initiated by the anti-LINGO-1 antibody may provide an important basis for the study of drugs for the prevention and treatment of AD in the future.