Targeting tumor suppressor p53 for organ fibrosis therapy.

Fibrosis is a reparative and progressive process characterized by abnormal extracellular matrix deposition, contributing to organ dysfunction in chronic diseases. The tumor suppressor p53 (p53), known for its regulatory roles in cell proliferation, apoptosis, aging, and metabolism across diverse tissues, appears to play a pivotal role in aggravating biological processes such as epithelial-mesenchymal transition (EMT), cell apoptosis, and cell senescence. These processes are closely intertwined with the pathogenesis of fibrotic disease. In this review, we briefly introduce the background and specific mechanism of p53, investigate the pathogenesis of fibrosis, and further discuss p53's relationship and role in fibrosis affecting the kidney, liver, lung, and heart. In summary, targeting p53 represents a promising and innovative therapeutic approach for the prevention and treatment of organ fibrosis.

Cross-waveband optical computing imaging.

A novel, to the best of our knowledge, cross-spectral optical computing imaging experiment has been achieved through a single exposure of a charge-coupled device. The experimental setup integrates single-pixel imaging (SPI) with ghost imaging (GI) through a photoelectric conversion circuit and a synchronous modulation system. The experimental process involves modulation in one wavelength band (in SPI) and demodulation using the GI algorithm in another. Significantly, our approach utilizes optical computing demodulation, a departure from the conventional electronic demodulation in GI (SPI), which involves the convolution between the bucket optical signals and the modulated patterns on the digital micromirror device. A proof-of-concept cross-band imaging experiment from near-infrared to visible light has been carried out. The results highlight the system's ability to capture images at up to 20 frames per second using near-infrared illumination, which are then reconstructed in the visible light spectrum. This success not only validates the feasibility of our approach but also expands the potential applications in the SPI or GI fields, particularly in scenarios where two-dimensional detector arrays are either unavailable or prohibitively expensive in certain electromagnetic spectra such as x-ray and terahertz.

Optical Encryption Using Attention-Inserted Physics-Driven Single-Pixel Imaging.

Optical encryption based on single-pixel imaging (SPI) has made great advances with the introduction of deep learning. However, the use of deep neural networks usually requires a long training time, and the networks need to be retrained once the target scene changes. With this in mind, we propose an SPI encryption scheme based on an attention-inserted physics-driven neural network. Here, an attention module is used to encrypt the single-pixel measurement value sequences of two images, together with a sequence of cryptographic keys, into a one-dimensional ciphertext signal to complete image encryption. Then, the encrypted signal is fed into a physics-driven neural network for high-fidelity decoding (i.e., decryption). This scheme eliminates the need for pre-training the network and gives more freedom to spatial modulation. Both simulation and experimental results have demonstrated the feasibility and eavesdropping resistance of this scheme. Thus, it will lead SPI-based optical encryption closer to intelligent deep encryption.

Shared Genetic Architecture between Parkinson's Disease and Brain Structural Phenotypes.

BACKGROUND: Patients with Parkinson's disease (PD) have consistently demonstrated brain structure abnormalities, indicating the presence of shared etiological and pathological processes between PD and brain structures; however, the genetic relationship remains poorly understood. OBJECTIVE: The aim of this study was to investigate the extent of shared genetic architecture between PD and brain structural phenotypes (BSPs) and to identify shared genomic loci. METHODS: We used the summary statistics from genome-wide association studies to conduct MiXeR and conditional/conjunctional false discovery rate analyses to investigate the shared genetic signatures between PD and BSPs. Subsequent expression quantitative trait loci mapping in the human brain and enrichment analyses were also performed. RESULTS: MiXeR analysis identified genetic overlap between PD and various BSPs, including total cortical surface area, average cortical thickness, and specific brain volumetric structures. Further analysis using conditional false discovery rate (FDR) identified 21 novel PD risk loci on associations with BSPs at conditional FDR < 0.01, and the conjunctional FDR analysis demonstrated that PD shared several genomic loci with certain BSPs at conjunctional FDR < 0.05. Among the shared loci, 16 credible mapped genes showed high expression in the brain tissues and were primarily associated with immune function-related biological processes. CONCLUSIONS: We confirmed the polygenic overlap with mixed directions of allelic effects between PD and BSPs and identified multiple shared genomic loci and risk genes, which are likely related to immune-related biological processes. These findings provide insight into the complex genetic architecture associated with PD. © 2023 International Parkinson and Movement Disorder Society.

Causal Effects of Blood Metabolites and Obstructive Sleep Apnea: A Mendelian Randomization Study.

BACKGROUND: Obstructive sleep apnea (OSA) is one of the most common forms of sleep-disordered breathing. Studies have shown that certain changes in metabolism play an important role in the pathophysiology of OSA. However, the causal relationship between these metabolites and OSA remains unclear. AIMS: We use a mendelian randomization (MR) approach to investigate the causal associations between the genetic liability to metabolites and OSA. METHODS: We performed a 2-sample inverse-variance weighted mendelian randomization analysis to evaluate the causal effects of genetically determined 486 metabolites on OSA. Multiple sensitivity analyses were performed to assess pleiotropy. We used multivariate mendelian randomization analyses to assess confounding factors and mendelian randomization Bayesian model averaging to rank the significant biomarkers by their genetic evidence. We also conducted a metabolic pathway analysis to identify potential metabolic pathways. RESULTS: We identified 14 known serum metabolites (8 risk factors and 6 protective factors) and 12 unknown serum metabolites associated with OSA. These 14 known metabolites included 8 lipids( 1-arachidonoylglycerophosphoethanolamine, Tetradecanedioate, Epiandrosteronesulfate, Acetylca Glycerol3-phosphate, 3-dehydrocarnitine, Margarate17:0, Docosapentaenoaten3;22:5n3), 3 Aminoacids (Isovalerylcarnitine,3-methyl-2-oxobutyrate,Methionine), 2 Cofactors and vitamins [Bilirubin(E,ZorZ,E),X-11593--O-methylascorbate], 1Carbohydrate(1,6-anhydroglucose). We also identified several metabolic pathways that involved in the pathogenesis of OSA. CONCLUSION: MR (mendelian randomization) approach was performed to identify 6 protective factors and 12 risk factors for OSA in the present study. 3-Dehydrocarnitine was the most significant risk factors for OSA. Our study also confirmed several significant metabolic pathways that were involved in the pathogenesis of OSA. Valine, leucine and isoleucine biosynthesis metabolic pathways were the most significant metabolic pathways that were involved in the pathogenesis of OSA.

Identifying causal genes for migraine by integrating the proteome and transcriptome.

BACKGROUND: While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. METHODS: We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. RESULTS: We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. CONCLUSIONS: Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.

Correlation between neutrophil gelatinase phase lipocalin and cerebral small vessel disease.

Background: Cerebral small vessel disease (CSVD) is common in the elderly population. Neutrophil gelatinase-associated lipocalin (NGAL) is closely related to cardiovascular and cerebrovascular diseases. NGAL causes pathological changes, such as damage to the vascular endothelium, by causing inflammation, which results in other related diseases. The purpose of this study was to investigate whether serum NGAL levels could predict disease severity in patients with CSVD. Methods: The patients with CSVD who visited the Department of Neurology at the First Affiliated Hospital of Zhengzhou University between January 2018 and June 2022 were prospectively included. The total CSVD burden score was calculated using whole-brain magnetic resonance imaging (MRI), and the patients were divided into a mild group (total CSVD burden score < 2 points) and a severe group (total CSVD burden score ≥ 2 points). Age, sex, height, smoking and alcohol consumption history, medical history, and serological results of patients were collected to perform the univariate analysis. Multivariate logistic regression was used to analyze the risk factors that affect CSVD severity. The multiple linear regression method was used to analyze which individual CSVD markers (periventricular white matter hyperintensities, deep white matter hyperintensities, lacune, and cerebral microbleed) play a role in the association between total CSVD burden score and NGAL. Results: A total of 427 patients with CSVD (140 in the mild group and 287 in the severe group) were included in the study. A multivariate logistic regression analysis showed that the following factors were significantly associated with CSVD severity: male sex [odds ratio(OR), 1.912; 95% confidence interval (CI), 1.150-3.179], age (OR, 1.046; 95% CI, 1.022-1.070), history of cerebrovascular disease (OR, 3.050; 95% CI, 1.764-5.274), serum NGAL level (OR, 1.005; 95% CI, 1.002-1.008), and diabetes (OR, 2.593; 95% CI, 1.424-4.722). A multivariate linear regression shows that periventricular white matter hyperintensities and cerebral microbleed are associated with serum NGAL concentrations (P < 0.05). Conclusion: Serum NGAL level is closely related to CSVD severity and is a risk factor for the burden of CSVD brain damage. Serum NGAL has high specificity in reflecting the severity of CSVD.

NOTCH2NLC expanded GGC repeats in patients with cerebral small vessel disease.

OBJECTIVE: GGC repeat expansions in the human-specific NOTCH2NLC gene have been reported as the cause of neuronal intranuclear inclusion disease (NIID). Given the clinical overlap of cognitive impairment in NIID and cerebral small vessel disease (CSVD), both diseases have white matter hyperintensity on T2-fluid-attenuated inversion recovery sequences of brain MRI, and white matter hyperintensity is a primary neuroimaging marker of CSVD on MRI. Therefore, we hypothesised that the GGC repeat expansions might also contribute to CSVD. To further investigate the relationship between NOTCH2NLC GGC repeat expansions and CSVD, we performed a genetic analysis of 814 patients with the disease. METHODS: We performed a comprehensive GGC repeat expansion screening in NOTCH2NLC from 814 patients with sporadic CSVD. Their Fazekas score was greater than or equal to 3 points. Repeat-primed PCR and fluorescence amplicon length analyses were performed to identify GGC repeat expansions, and whole-exome sequencing was used to detect any pathogenic mutation in previously reported genes associated with CSVD. RESULTS: We identified nine (1.11%) patients with pathogenic GGC repeat expansions ranging from 41 to 98 repeats. The minor allele frequency of expanded GGC repeats in NOTCH2NLC was 0.55%. CONCLUSION: Our findings suggest that intermediate-length and longer-length GGC repeat expansions in NOTCH2NLC are associated with sporadic CSVD. This provides new thinking for studying the pathogenesis of CSVD.

Genetic analysis of the ATP11B gene in Chinese Han population with cerebral small vessel disease.

BACKGROUND: A loss-of-function mutation in ATPase phospholipid transporting 11-B (putative) (ATP11B) gene causing cerebral small vessel disease (SVD) in vivo, and a single intronic nucleotide polymorphism in ATP11B: rs148771930 that was associated with white matter hyperintensities burden in European patients with SVD, was recently identified. Our results suggest that ATP11B may not play an essential role in SVD in the Chinese population. RESULTS: We performed target region sequencing including ATP11B gene in 182 patients with sporadic SVD, and identified five rare variants and two novel variants of ATP11B. A case-control study was then performed in 524 patients and matched 550 controls to investigate the relationship between ATP11B and sporadic SVD in the Chinese Han population. Although none of these variants were significantly associated with SVD in our samples, it is important to mention that we identified a novel variant, p. G238W, which was predicted to be pathogenic in silico. This variant was present in our cohort of patients with an extremely low frequency and was absent in the controls. CONCLUSION: Our results suggest that ATP11B may not play an essential role in SVD in the Chinese population.

Multi-Party Cryptographic Key Distribution Protocol over a Public Network Based on a Quick-Response Code.

In existing cryptographic key distribution (CKD) protocols based on computational ghost imaging (CGI), the interaction among multiple legitimate users is generally neglected, and the channel noise has a serious impact on the performance. To overcome these shortcomings, we propose a multi-party interactive CKD protocol over a public network, which takes advantage of the cascade ablation of fragment patterns (FPs). The server splits a quick-response (QR) code image into multiple FPs and embeds different "watermark" labels into these FPs. By using a CGI setup, the server will acquire a series of bucket value sequences with respect to different FPs and send them to multiple legitimate users through a public network. The users reconstruct the FPs and determine whether there is an attack in the public channel according to the content of the recovered "watermark" labels, so as to complete the self-authentication. Finally, these users can extract their cryptographic keys by scanning the QR code (the cascade ablation result of FPs) returned by an intermediary. Both simulation and experimental results have verified the feasibility of this protocol. The impacts of different attacks and the noise robustness have also been investigated.

Secondary Complementary Balancing Compressive Imaging with a Free-Space Balanced Amplified Photodetector.

Single-pixel imaging (SPI) has attracted widespread attention because it generally uses a non-pixelated photodetector and a digital micromirror device (DMD) to acquire the object image. Since the modulated patterns seen from two reflection directions of the DMD are naturally complementary, one can apply complementary balanced measurements to greatly improve the measurement signal-to-noise ratio and reconstruction quality. However, the balance between two reflection arms significantly determines the quality of differential measurements. In this work, we propose and demonstrate a simple secondary complementary balancing mechanism to minimize the impact of the imbalance on the imaging system. In our SPI setup, we used a silicon free-space balanced amplified photodetector with 5 mm active diameter which could directly output the difference between two optical input signals in two reflection arms. Both simulation and experimental results have demonstrated that the use of secondary complementary balancing can result in a better cancellation of direct current components of measurements, and can acquire an image quality slightly better than that of single-arm single-pixel complementary measurement scheme (which is free from the trouble of optical imbalance) and over 20 times better than that of double-arm dual-pixel complementary measurement scheme under optical imbalance conditions.

Gradient-Descent-like Ghost Imaging.

Ghost imaging is an indirect optical imaging technique, which retrieves object information by calculating the intensity correlation between reference and bucket signals. However, in existing correlation functions, a high number of measurements is required to acquire a satisfied performance, and the increase in measurement number only leads to limited improvement in image quality. Here, inspired by the gradient descent idea that is widely used in artificial intelligence, we propose a gradient-descent-like ghost imaging method to recursively move towards the optimal solution of the preset objective function, which can efficiently reconstruct high-quality images. The feasibility of this technique has been demonstrated in both numerical simulation and optical experiments, where the image quality is greatly improved within finite steps. Since the correlation function in the iterative formula is replaceable, this technique offers more possibilities for image reconstruction of ghost imaging.

Targeting ß-Catenin Signaling by Natural Products for Cancer Prevention and Therapy.

The mutations and deregulation of Wnt signaling pathway occur commonly in human cancer and cause the aberrant activation of ß-catenin and ß-catenin-dependent transcription, thus contributing to cancer development and progression. Therefore, ß-catenin has been demonstrated as a promising target for cancer prevention and therapy. Many natural products have been characterized as inhibitors of the ß-catenin signaling through down-regulating ß-catenin expression, modulating its phosphorylation, promoting its ubiquitination and proteasomal degradation, inhibiting its nuclear translocation, or other molecular mechanisms. These natural product inhibitors have shown preventive and therapeutic efficacy in various cancer models in vitro and in vivo. In the present review, we comprehensively discuss the natural product ß-catenin inhibitors, their in vitro and in vivo anticancer activities, and underlying molecular mechanisms. We also discuss the current ß-catenin-targeting strategies and other potential strategies that may be examined for identifying new ß-catenin inhibitors as cancer preventive and therapeutic drugs.

AAV/BBB-Mediated Gene Transfer of CHIP Attenuates Brain Injury Following Experimental Intracerebral Hemorrhage.

Cell death is a hallmark of secondary brain injury following intracerebral hemorrhage (ICH). The E3 ligase CHIP has been reported to play a key role in mediating necroptosis-an important mechanism of cell death after ICH. However, there is currently no evidence supporting a function of CHIP in ICH. In the present study, we aimed to determine whether CHIP plays an essential role in brain injury after ICH. Our findings indicated that CHIP expression was increased in the peri-hematomal area in rat models of ICH. The AAV/BBB viral platform enables non-invasive, widespread, and long-lasting global neural expression of target genes. Treatment with AAV/BBB-CHIP ameliorated brain injury and inhibited neuronal necroptosis and inflammation in wild type (WT) rats following ICH. Furthermore, rats with CHIP deficiency experienced severe brain injury and increased levels of neuronal necroptosis and inflammation relative to their WT counterparts. However, treatment with AAV/BBB-CHIP attenuated the effects of CHIP deficiency after ICH. Collectively, our results demonstrate that CHIP inhibits necroptosis and pathological inflammation following ICH, and that overexpression of CHIP may represent a therapeutic intervention for ICH. Moreover, the AAV/BBB viral platform may provide a novel avenue for the treatment of brain injury.

Pseudo-thermal imaging by using sequential-deviations for real-time image reconstruction.

Ghost imaging technologies acquire images through intensity correlation of reference patterns and bucket values. Among them, an interesting method named correspondence imaging can generate positive-negative images by only conditionally averaging reference patterns, but still requires full/over sampling to treat the ensemble average of bucket values as a selection criteria, causing a long acquisition time. Here, we propose a sequential-deviation ghost imaging approach, which can realize real-time reconstructions of positive-negative images with a high image quality close to that of differential ghost imaging. Since it is no longer necessary to compare with the ensemble average, this method can improve the real-time performance. An explanation of its essence is also given here. Both simulation and experimental results have demonstrated the feasibility of this technique. This work may complement the theory of ghost imaging.

Single-Pixel Imaging with Origami Pattern Construction.

Single-pixel compressive imaging can recover images from fewer measurements, offering many benefits especially for the imaging modalities where array detection is unavailable. However, the widely used random projections fail to explore internal relations between coding patterns and image reconstruction. Here, we propose a single-pixel imaging method based on a deterministic origami pattern construction that can lead to a more accurate pattern ordering sequence and better imaging quality. It can decrease the sampling ratio, closer to the upper bounds. The experimental realization of this approach is a big step forward towards practical applications.

Super Sub-Nyquist Single-Pixel Imaging by Means of Cake-Cutting Hadamard Basis Sort.

Single-pixel imaging via compressed sensing can reconstruct high-quality images from a few linear random measurements of an object known a priori to be sparse or compressive, by using a point/bucket detector without spatial resolution. Nevertheless, random measurements still have blindness, limiting the sampling ratios and leading to a harsh trade-off between the acquisition time and the spatial resolution. Here, we present a new compressive imaging approach by using a strategy we call cake-cutting, which can optimally reorder the deterministic Hadamard basis. The proposed method is capable of recovering images of large pixel-size with dramatically reduced sampling ratios, realizing super sub-Nyquist sampling and significantly decreasing the acquisition time. Furthermore, such kind of sorting strategy can be easily combined with the structured characteristic of the Hadamard matrix to accelerate the computational process and to simultaneously reduce the memory consumption of the matrix storage. With the help of differential modulation/measurement technology, we demonstrate this method with a single-photon single-pixel camera under the ulta-weak light condition and retrieve clear images through partially obscuring scenes. Thus, this method complements the present single-pixel imaging approaches and can be applied to many fields.

Cryptographic key distribution over a public network via variance-based watermarking in compressive measurements.

Optical communication has an increasing need for security in public transmission scenarios. Here, we present a protocol for cryptographic key distribution over a public network via a photon-counting compressive imaging system with watermarking, which utilizes a watermarking technique to distribute secure keys, and uses reconstructed images for simultaneous identity authentication and tampering identification. The watermark is embedded in the rearranged compressed measurements of the object, and then the signal is transmitted through a public network. At the receiving terminal, legitimate users can easily extract the watermark as the cryptographic key by using initial keys and the variance characteristic of random measurements. Artificial tampering and attacks can be detected by accurately retrieved images. The realization of this protocol is a step forward toward practical applications, and will be beneficial for the broader fields of optical security in many ways.

Evaluation criterion of thermal light ghost imaging based on the receiver operating characteristic analysis.

The performances of different thermal ghost imaging (GI) algorithms are compared in an experiment of computational GI using a digital micromirror device. Here we present a rather different evaluation criterion named receiver operating characteristic (ROC) analysis that serves as the performance of merit for the quantitative comparison. A ROC curve is created by plotting the true positive rate against the false positive rate at various threshold settings. Both theoretical analysis and experimental results demonstrate that the ROC curve and the area under the curve are better and more intuitive indicators of the performance of the GI, compared with conventional evaluation methods. Additionally, for examining gray-scale objects, the calculation of the volume under the ROC surface is analyzed and serves as a performance metric. Our scheme should attract general interest and open exciting prospects for ROC analysis in thermal GI.

Iterative denoising of ghost imaging.

We present a new technique to denoise ghost imaging (GI) in which conventional intensity correlation GI and an iteration process have been combined to give an accurate estimate of the actual noise affecting image quality. The blurring influence of the speckle areas in the beam is reduced in the iteration by setting a threshold. It is shown that with an appropriate choice of threshold value, the quality of the iterative GI reconstructed image is much better than that of differential GI for the same number of measurements. This denoising method thus offers a very effective approach to promote the implementation of GI in real applications.