Viral unmasking of cellular 5S rRNA pseudogene transcripts induces RIG-I-mediated immunity.

The sensor RIG-I detects double-stranded RNA derived from RNA viruses. Although RIG-I is also known to have a role in the antiviral response to DNA viruses, physiological RNA species recognized by RIG-I during infection with a DNA virus are largely unknown. Using next-generation RNA sequencing (RNAseq), we found that host-derived RNAs, most prominently 5S ribosomal RNA pseudogene 141 (RNA5SP141), bound to RIG-I during infection with herpes simplex virus 1 (HSV-1). Infection with HSV-1 induced relocalization of RNA5SP141 from the nucleus to the cytoplasm, and virus-induced shutoff of host protein synthesis downregulated the abundance of RNA5SP141-interacting proteins, which allowed RNA5SP141 to bind RIG-I and induce the expression of type I interferons. Silencing of RNA5SP141 strongly dampened the antiviral response to HSV-1 and the related virus Epstein-Barr virus (EBV), as well as influenza A virus (IAV). Our findings reveal that antiviral immunity can be triggered by host RNAs that are unshielded following depletion of their respective binding proteins by the virus.

Proteomes reveal the lipid metabolic network in the complex plastid of Phaeodactylum tricornutum.

Phaeodactylum tricornutum plastid is surrounded by four membranes, and its protein composition and function remain mysterious. In this study, the P. tricornutum plastid-enriched fraction was obtained and 2850 proteins were identified, including 92 plastid-encoded proteins, through label-free quantitative proteomic technology. Among them, 839 nuclear-encoded proteins were further determined to be plastidial proteins based on the BLAST alignments within Plant Proteome DataBase and subcellular localization prediction, in spite of the strong contamination by mitochondria-encoded proteins and putative plasma membrane proteins. According to our proteomic data, we reconstructed the metabolic pathways and highlighted the hybrid nature of this diatom plastid. Triacylglycerol (TAG) hydrolysis and glycolysis, as well as photosynthesis, glycan metabolism, and tocopherol and triterpene biosynthesis, occur in the plastid. In addition, the synthesis of long-chain acyl-CoAs, elongation, and desaturation of fatty acids (FAs), and synthesis of lipids including TAG are confined in the four-layered-membrane plastid based on the proteomic and GFP-fusion localization data. The whole process of generation of docosahexaenoic acid (22:6) from palmitic acid (16:0), via elongation and desaturation of FAs, occurs in the chloroplast endoplasmic reticulum membrane, the outermost membrane of the plastid. Desaturation that generates 16:4 from 16:0 occurs in the plastid stroma and outer envelope membrane. Quantitative analysis of glycerolipids between whole cells and isolated plastids shows similar composition, and the FA profile of TAG was not different. This study shows that the diatom plastid combines functions usually separated in photosynthetic eukaryotes, and differs from green alga and plant chloroplasts by undertaking the whole process of lipid biosynthesis.

Domain Switching Characteristics in Ga-Doped HfO2 Ferroelectric Thin Films with Low Coercive Field.

The gallium-doped hafnium oxide (Ga-HfO2) films with different Ga doping concentrations were prepared by adjusting the HfO2/Ga2O3 atomic layer deposition cycle ratio for high-speed and low-voltage operation in HfO2-based ferroelectric memory. The Ga-HfO2 ferroelectric films reveal a finely modulated coercive field (Ec) from 1.1 (HfO2/Ga2O3 = 32:1) to an exceptionally low 0.6 MV/cm (HfO2/Ga2O3 = 11:1). This modulation arises from the competition between domain nucleation and propagation speed during polarization switching, influenced by the intrinsic domain density and phase dispersion in the film with specific Ga doping concentrations. Higher Ec samples exhibit a nucleation-dominant switching mechanism, while lower Ec samples undergo a transition from a nucleation-dominant to a propagation-dominant reversal mechanism as the electric field increases. This work introduces Ga as a viable dopant for low Ec and offers insights into material design strategies for HfO2-based ferroelectric memory applications.

Inhibition of MMP8 effectively alleviates manic-like behavior and reduces neuroinflammation by modulating astrocytic CEBPD.

There is an intrinsic relationship between psychiatric disorders and neuroinflammation, including bipolar disorder. Ouabain, an inhibitor of Na+/K+-ATPase, has been implicated in the mouse model with manic-like behavior. However, the molecular mechanisms linking neuroinflammation and manic-like behavior require further investigation. CCAAT/Enhancer-Binding Protein Delta (CEBPD) is an inflammatory transcription factor that contributes to neurological disease progression. In this study, we demonstrated that the expression of CEBPD in astrocytes was increased in ouabain-treated mice. Furthermore, we observed an increase in the expression and transcript levels of CEBPD in human primary astrocytes following ouabain treatment. Transcriptome analysis revealed high MMP8 expression in human primary astrocytes following CEBPD overexpression and ouabain treatment. We confirmed that MMP8 is a CEBPD-regulated gene that mediates ouabain-induced neuroinflammation. In our animal model, treatment of ouabain-injected mice with M8I (an inhibitor of MMP8) resulted in the inhibition of manic-like behavior compared to ouabain-injected mice that were not treated with M8I. Additionally, the reduction in the activation of astrocytes and microglia was observed, particularly in the hippocampal CA1 region. Excessive reactive oxygen species formation was observed in ouabain-injected mice, and treating these mice with M8I resulted in the reduction of oxidative stress, as indicated by nitrotyrosine staining. These findings suggest that MMP8 inhibitors may serve as therapeutic agents in mitigating manic symptoms in bipolar disorder.

Comparative assessment of established and deep learning-based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis.

In this study, our objective was to assess the performance of two deep learning-based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two established techniques, FreeSurfer-Aseg and FSL-FIRST, using three-dimensional T1-weighted MRI scans (n = 1447) procured from public databases. Our evaluation focused on the accuracy and reproducibility of these tools in estimating hippocampal volume. The findings suggest that both SynthSeg and TigerBx are on a par with Aseg and FIRST in terms of segmentation accuracy and reproducibility, but offer a significant advantage in processing speed, generating results in less than 1 min compared with several minutes to hours for the latter tools. In terms of Alzheimer's disease classification based on the hippocampal atrophy rate, SynthSeg and TigerBx exhibited superior performance. In conclusion, we evaluated the capabilities of two deep learning-based segmentation techniques. The results underscore their potential value in clinical and research environments, particularly when investigating neurological conditions associated with hippocampal structures.

Virtual MOLLI Target: Generative Adversarial Networks Toward Improved Motion Correction in MRI Myocardial T1 Mapping.

BACKGROUND: The modified Look-Locker inversion recovery (MOLLI) sequence is commonly used for myocardial T1 mapping. However, it acquires images with different inversion times, which causes difficulty in motion correction for respiratory-induced misregistration to a given target image. HYPOTHESIS: Using a generative adversarial network (GAN) to produce virtual MOLLI images with consistent heart positions can reduce respiratory-induced misregistration of MOLLI datasets. STUDY TYPE: Retrospective. POPULATION: 1071 MOLLI datasets from 392 human participants. FIELD STRENGTH/SEQUENCE: Modified Look-Locker inversion recovery sequence at 3 T. ASSESSMENT: A GAN model with a single inversion time image as input was trained to generate virtual MOLLI target (VMT) images at different inversion times which were subsequently used in an image registration algorithm. Four VMT models were investigated and the best performing model compared with the standard vendor-provided motion correction (MOCO) technique. STATISTICAL TESTS: The effectiveness of the motion correction technique was assessed using the fitting quality index (FQI), mutual information (MI), and Dice coefficients of motion-corrected images, plus subjective quality evaluation of T1 maps by three independent readers using Likert score. Wilcoxon signed-rank test with Bonferroni correction for multiple comparison. Significance levels were defined as P < 0.01 for highly significant differences and P < 0.05 for significant differences. RESULTS: The best performing VMT model with iterative registration demonstrated significantly better performance (FQI 0.88 ± 0.03, MI 1.78 ± 0.20, Dice 0.84 ± 0.23, quality score 2.26 ± 0.95) compared to other approaches, including the vendor-provided MOCO method (FQI 0.86 ± 0.04, MI 1.69 ± 0.25, Dice 0.80 ± 0.27, quality score 2.16 ± 1.01). DATA CONCLUSION: Our GAN model generating VMT images improved motion correction, which may assist reliable T1 mapping in the presence of respiratory motion. Its robust performance, even with considerable respiratory-induced heart displacements, may be beneficial for patients with difficulties in breath-holding. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 1.

Irreversible Electroporation-Induced Inflammation Facilitates Neutrophil-Mediated Drug Delivery to Enhance Pancreatic Cancer Therapy.

Pancreatic cancer is a deadly disease with a five-year overall survival rate of around 11%. Chemotherapy is a cornerstone in the treatment of this malignancy, but the intratumoral delivery of chemotherapy drugs is impaired by the highly fibrotic tumor-associated stroma. Irreversible electroporation (IRE) is an ablative technique for treating locally advanced pancreatic cancer. During a typical IRE procedure, high-intensity electric pulses are released to kill tumor cells through the irreversible disruption of the cytoplasm membranes. IRE also induces rapid tumor infiltration by neutrophils and offers an opportunity for neutrophil-mediated drug delivery. We herein showed that the IRE-induced neutrophil trafficking was facilitated by the upregulation of neutrophil chemotaxis and migration as well as the release of several chemoattractants. Doxorubicin-loaded bovine serum albumin nanoparticles were prepared and loaded into neutrophils at a ratio of 9.9 ± 1.2 to 11.7 ± 2.0 pg of doxorubicin per cell. The resultant formulation (NP@NEs) efficiently accumulated in the IRE-treated KPC-A377 murine pancreatic tumors with an uptake value of 10.7 ± 1.5 (percent of injected dose per gram of tissue, abbreviated as %ID/g) at 48 h after intravenous injection. In both Panc02 and KPC-A377 murine pancreatic tumor models, the combination of IRE + NP@NEs inhibited tumor growth more effectively than either monotherapy. The tumors treated with the combination also exhibited the lowest frequency of Ki67+ proliferating cells and the highest abundance of terminal deoxynucleotidyl transferase dUTP nick end labeling+ (TUNEL+) apoptotic cells among the experiment groups. Minimal treatment-associated toxicity was observed. Our findings suggest that neutrophil-mediated delivery of chemotherapy drugs is a useful tool to enhance the response of pancreatic cancer to IRE.

High-performance MoS2phototransistors with Hf1-xAlxO back-gate dielectric layer grown by plasma enhanced atomic layer deposition.

Molybdenum sulfide (MoS2) as an emerging optoelectronic material, shows great potential for phototransistors owing to its atomic thickness, adjustable band gap, and low cost. However, the phototransistors based on MoS2have been shown to have some issues such as large gate leakage current, and interfacial scattering, resulting in suboptimal optoelectronic performance. Thus, Al-doped hafnium oxide (Hf1-xAlx) is proposed to be a dielectric layer of the MoS2-based phototransistor to solve this problem because of the relatively higher crystallization temperature and dielectric constant. Here, a high-performance MoS2phototransistor with Hf1-xAlxO gate dielectric layer grown by plasma-enhanced atomic layer deposition has been fabricated and studied. The results show that the phototransistor exhibits a high responsivity of 2.2 × 104A W-1, a large detectivity of 1.7 × 1017Jones, a great photo-to-dark current ratio of 2.2 × 106%, and a high external quantum efficiency of 4.4 × 106%. The energy band alignment and operating mechanism were further used to clarify the reason for the enhanced MoS2phototransistor. The suggested MoS2phototransistors could provide promising strategies in further optoelectronic applications.

Influence of Hydrothermal Modification on Adsorptive Performance of Clay Minerals for Malachite Green.

Artificially modified adsorbing materials mainly aim to remedy the disadvantages of natural materials as much as possible. Using clay materials such as rectorite, sodium bentonite and metakaolinite (solid waste material) as base materials, hydrothermally modified and unmodified materials were compared. CM-HT and CM (adsorbing materials) were prepared and used to adsorb and purify wastewater containing malachite green (MG) dye, and the two materials were characterized through methods such as BET, FT-IR, SEM and XRD. Results: (1) The optimal conditions for hydrothermal modification of CM-HT were a temperature of 150 °C, a time of 2 h, and a liquid/solid ratio 1:20. (2) Hydrothermal modification greatly increased the adsorptive effect. The measured maximum adsorption capacity of CM-HT for MG reached 290.45 mg/g (56.92% higher than that of CM). The theoretical maximum capacity was 625.15 mg/g (186.15% higher than that of CM). (3) Because Al-OH and Si-O-Al groups were reserved in unmodified clay mineral adsorbing materials with good adsorbing activity, after hydrothermal modification, the crystal structure of the clay became loosened along the direction of the c axis, and the interlayer space increased to partially exchange interlayer metal cations connected to the bottom oxygen, giving CM-HT higher electronegativity and creating more crystal defects and chemically active adsorbing sites for high-performance adsorption. (4) Chemical adsorption was the primary way by which CM-HT adsorbed cationic dye, while physical adsorption caused by developed pore canal was secondary. The adsorption reaction occurred spontaneously.

Effect of the Side-Chain Length in Polycarboxylic Superplasticizer on the Competition Adsorption in the Presence of Montmorillonite: A Density Functional Theory Study.

Polycarboxylic superplasticizers (PCEs) exhibit numerous advantages as concrete additives, effectively improving the stability and strength of concrete. However, competitive adsorption of PCEs occurs in the presence of clay, which may affect the cement dispersion and water-reducing performance. Extensive research has been conducted on the physical and mechanical properties of PCEs; however, the effect of the diverse structures of PCEs on the competitive adsorption on clay and cement hydration products has been rarely studied. This study employs Ca-montmorillonite (CaMMT) as a clay representative, by constructing adsorption models of PCEs on CaMMT and cement hydration products. A comparison of the adsorption energies considering different side-chain lengths of PCEs is included. Typically, the adsorption energy on CaMMT is lower than that on hydration products, leading PCEs to preferentially adsorb on the clay, thereby reducing its effective dosage in the cement particles. The challenge of PCE adsorption on CaMMT increases with the polymerization degree, and methylallyl polyoxyethylene ether (HPEG) exhibits lower adsorption energies on CaMMT. The density of states (DOS) analysis indicated the highest peak values of allyl polyethylene ether (APEG) as well as the peak area at n (polymerization degree) = 1. The total number of transferred electrons for APEG was 0.648, surpassing those of other PCEs. The interaction mechanism of PCEs with clay and hydration products is further elucidated through electronic gain/loss analysis, also providing a basis for the theoretical analysis on how to reduce the adsorption of PCEs on clay and the structural design of mud-resistant PCEs.

Ethnic-specificity, evolution origin and deleteriousness of Asian BRCA variation revealed by over 7500 BRCA variants derived from Asian population.

Pathogenic variation in BRCA1 and BRCA2 (BRCA) causes high risk of breast and ovarian cancer, and BRCA variation data are important markers for BRCA-related clinical cancer applications. However, comprehensive BRCA variation data are lacking from the Asian population despite its large population size, heterogenous genetic background and diversified living environment across the Asia continent. We performed a systematic study on BRCA variation in Asian population including extensive data mining, standardization, annotation and characterization. We identified 7587 BRCA variants from 685 592 Asian individuals in 40 Asia countries and regions, including 1762 clinically actionable pathogenic variants and 4915 functionally unknown variants (https://genemutation.fhs.um.edu.mo/Asian-BRCA/). We observed the highly ethnic-specific nature of Asian BRCA variants between Asian and non-Asian populations and within Asian populations, highlighting that the current European descendant population-based BRCA data is inadequate to reflect BRCA variation in the Asian population. We also provided archeological evidence for the evolutionary origin and arising time of Asian BRCA variation. We further provided structural-based evidence for the deleterious variants enriched within the functionally unknown Asian BRCA variants. The data from our study provide a current view of BRCA variation in the Asian population and a rich resource to guide clinical applications of BRCA-related cancer for the Asian population.

Exendin-4 ameliorates tau hyperphosphorylation and cognitive impairment in type 2 diabetes through acting on Wnt/ß-catenin/NeuroD1 pathway.

BACKGROUND: Type 2 diabetes (T2D) is an independent risk factor for Alzheimer's disease (AD). Exendin-4 (Ex-4), a widely used glucagon-like peptide-1 receptor agonist drug in the treatment of T2D, has been demonstrated the therapeutic effects on diabetic encephalopathy (DE). Especially, the Ex-4 ameliorates the tau hyperphosphorylation and cognitive impairment in DE. And these crucial alterations are also important bridge between T2D and AD. However, its unique mechanism is unclear. METHODS: The db/db mice, high-fat-diet (HFD) / streptozotocin (STZ)-induced diabetic (HF-diabetic) mice, and high-glucose-damaged (HGD) HT-22 hippocampal cells were enrolled to examine the effects of Ex-4 on AD-like changes in T2D. The Novel object recognition test (NORT) and Morris water maze test (MWMT) were conducted to evaluate the cognitive impairment. The Dickkopf-1 (DKK1) was employed to weaken the activation of the Wnt/ß-catenin pathway to explore the mechanism of Ex-4 in protecting the brain functions. The JASPAR was based to predict the interaction between NeuroD1 and the promoter region of Ins2. Moreover, the chromatin immunoprecipitation coupled with quantitative polymerase chain reaction (ChIP-qPCR) and luciferase reporter assays were performed. RESULTS: Ex-4 alleviated the tau hyperphosphorylation, increased the brain-derived insulin, and improved the PI3K/AKT/GSK3-ß signalling in db/db mice, HF-diabetic mice, and HGD HT-22 hippocampal neuronal cells. The NORT and MWMT indicated that Ex-4 alleviated the learning and memory deficits in HF-diabetic mice. The inhibitor Dickkopf-1 (DKK1) of the Wnt/ß-catenin pathway significantly blocked the protective effects of Ex-4. Regarding further molecular mechanisms, NeuroD1 was affected by Ex-4 in vivo and in vitro, and the knockdown or overexpression of NeuroD1 suggested its crucial role in promoting the brain insulin by Ex-4. Meanwhile, the ChIP‒qPCR and luciferase reporter assays confirmed the combination between NeuroD1 and the promoter region of the insulin-encoding gene Ins2. And this interaction could be promoted by Ex-4. CONCLUSIONS: Our study proposes that Ex-4 alleviates tau hyperphosphorylation and cognitive dysfunction by increasing Ins2-derived brain insulin through the Wnt/ß-catenin/NeuroD1 signaling in T2D. And its also show new lights on part of the progress and mechanism on treatment targets for the DE in T2D.

The Emergence, Diversification, and Transmission of Subgroup J Avian Leukosis Virus Reveals that the Live Chicken Trade Plays a Critical Role in the Adaption and Endemicity of Viruses to the Yellow-Chickens.

The geographical spread and inter-host transmission of the subgroup J avian leukosis virus (ALV-J) may be the most important issues for epidemiology. An integrated analysis, including phylogenetic trees, homology modeling, evolutionary dynamics, selection analysis and viral transmission, based on the gp85 gene sequences of the 665 worldwide ALV-J isolates during 1988-2020, was performed. A new Clade 3 has been emerging and was evolved from the dominating Clade 1.3 of the Chinese Yellow-chicken, and the loss of a α-helix or ß-sheet of the gp85 protein monomer was found by the homology modeling. The rapid evolution found in Clades 1.3 and 3 may be closely associated with the adaption and endemicity of viruses to the Yellow-chickens. The early U.S. strains from Clade 1.1 acted as an important source for the global spread of ALV-J and the earliest introduction into China was closely associated with the imported chicken breeders in the 1990s. The dominant outward migrations of Clades 1.1 and 1.2, respectively, from the Chinese northern White-chickens and layers to the Chinese southern Yellow-chickens, and the dominating migration of Clade 1.3 from the Chinese southern Yellow-chickens to other regions and hosts, indicated that the long-distance movement of these viruses between regions in China was associated with the live chicken trade. Furthermore, Yellow-chickens have been facing the risk of infections of the emerging Clades 2 and 3. Our findings provide new insights for the epidemiology and help to understand the critical factors involved in ALV-J dissemination. IMPORTANCE Although the general epidemiology of ALV-J is well studied, the ongoing evolutionary and transmission dynamics of the virus remain poorly investigated. The phylogenetic differences and relationship of the clades and subclades were characterized, and the epidemics and factors driving the geographical spread and inter-host transmission of different ALV-J clades were explored for the first time. The results indicated that the earliest ALV-J (Clade 1.1) from the United States, acted as the source for global spreads, and Clades 1.2, 1.3 and 3 were all subsequently evolved. Also the epidemiological investigation showed that the early imported breeders and the inter-region movements of live chickens facilitated the ALV-J dispersal throughout China and highlighted the needs to implement more effective containment measures.

Deriving a robust deep-learning model for subcortical brain segmentation by using a large-scale database: Preprocessing, reproducibility, and accuracy of volume estimation.

Increasing the accuracy and reproducibility of subcortical brain segmentation is advantageous in various related clinical applications. In this study, we derived a segmentation method based on a convolutional neural network (i.e., U-Net) and a large-scale database consisting of 7039 brain T1-weighted MRI data samples. We evaluated the method by using experiments focused on three distinct topics, namely, the necessity of preprocessing steps, cross-institutional and longitudinal reproducibility, and volumetric accuracy. The optimized model, MX_RW-where "MX" is a mix of RW and nonuniform intensity normalization data and "RW" is raw data with basic preprocessing-did not require time-consuming preprocessing steps, such as nonuniform intensity normalization or image registration, for brain MRI before segmentation. Cross-institutional testing revealed that MX_RW (Dice similarity coefficient: 0.809, coefficient of variation: 4.6%, and Pearson's correlation coefficient: 0.979) exhibited a performance comparable with that of FreeSurfer (Dice similarity coefficient: 0.798, coefficient of variation: 5.6%, and Pearson's correlation coefficient: 0.973). The computation time per dataset of MX_RW was generally less than 5 s (even when tested without graphics processing units), which was notably faster than FreeSurfer. Thus, for time-restricted applications, MX_RW represents a competitive alternative to FreeSurfer.

Imaging Dynamic Processes in Multiple Dimensions and Length Scales.

Optical microscopy has become an invaluable tool for investigating complex samples. Over the years, many advances to optical microscopes have been made that have allowed us to uncover new insights into the samples studied. Dynamic changes in biological and chemical systems are of utmost importance to study. To probe these samples, multidimensional approaches have been developed to acquire a fuller understanding of the system of interest. These dimensions include the spatial information, such as the three-dimensional coordinates and orientation of the optical probes, and additional chemical and physical properties through combining microscopy with various spectroscopic techniques. In this review, we survey the field of multidimensional microscopy and provide an outlook on the field and challenges that may arise.

The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net.

BACKGROUND: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. METHODS: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10-3 mm2/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal-Wallis test with Tukey-Kramer post-hoc tests were used for comparison. A p < .05 was considered statistically significant. RESULTS: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10-3 mm2/s and 0.8 × 10-3 mm2/s (p < .001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10-3 mm2/s (p = .062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10-3 mm2/s achieved the highest DSC in the segmentation of AIS lesion. CONCLUSIONS: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10-3 mm2/s in segmentating AIS lesion with highest DSC. KEY POINTS: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10-3 mm2/s.

Prevalence and spectrum of DNA mismatch repair gene variation in the general Chinese population.

BACKGROUND: Identifying genetic disease-susceptible individuals through population screening is considered as a promising approach for disease prevention. DNA mismatch repair (MMR) genes including MLH1, MSH2, MSH6 and PMS2 play essential roles in maintaining microsatellite stability through DNA mismatch repair, and pathogenic variation in MMR genes causes microsatellite instability and is the genetic predisposition for cancer as represented by the Lynch syndrome. While the prevalence and spectrum of MMR variation has been extensively studied in cancer, it remains largely elusive in the general population. Lack of the knowledge prevents effective prevention for MMR variation-caused cancer. In the current study, we addressed the issue by using the Chinese population as a model. METHODS: We performed extensive data mining to collect MMR variant data from 18 844 ethnic Chinese individuals and comprehensive analyses for the collected MMR variants to determine its prevalence, spectrum and features of the MMR data in the Chinese population. RESULTS: We identified 17 687 distinct MMR variants. We observed substantial differences of MMR variation between the general Chinese population and Chinese patients with cancer, identified highly Chinese-specific MMR variation through comparing MMR data between Chinese and non-Chinese populations, predicted the enrichment of deleterious variants in the unclassified Chinese-specific MMR variants, determined MMR pathogenic prevalence of 0.18% in the general Chinese population and determined that MMR variation in the general Chinese population is evolutionarily neutral. CONCLUSION: Our study provides a comprehensive view of MMR variation in the general Chinese population, a resource for biological study of human MMR variation, and a reference for MMR-related cancer applications.

Smart Contract Vulnerability Detection Based on Deep Learning and Multimodal Decision Fusion.

With the rapid development and widespread application of blockchain technology in recent years, smart contracts running on blockchains often face security vulnerability problems, resulting in significant economic losses. Unlike traditional programs, smart contracts cannot be modified once deployed, and vulnerabilities cannot be remedied. Therefore, the vulnerability detection of smart contracts has become a research focus. Most existing vulnerability detection methods are based on rules defined by experts, which are inefficient and have poor scalability. Although there have been studies using machine learning methods to extract contract features for vulnerability detection, the features considered are singular, and it is impossible to fully utilize smart contract information. In order to overcome the limitations of existing methods, this paper proposes a smart contract vulnerability detection method based on deep learning and multimodal decision fusion. This method also considers the code semantics and control structure information of smart contracts. It integrates the source code, operation code, and control-flow modes through the multimodal decision fusion method. The deep learning method extracts five features used to represent contracts and achieves high accuracy and recall rates. The experimental results show that the detection accuracy of our method for arithmetic vulnerability, re-entrant vulnerability, transaction order dependence, and Ethernet locking vulnerability can reach 91.6%, 90.9%, 94.8%, and 89.5%, respectively, and the detected AUC values can reach 0.834, 0.852, 0.886, and 0.825, respectively. This shows that our method has a good vulnerability detection effect. Furthermore, ablation experiments show that the multimodal decision fusion method contributes significantly to the fusion of different modalities.

The Design and Fabrication of Large-Area Under-Screen Fingerprint Sensors with Optimized Aperture and Microlens Structures.

In this paper, we designed and fabricated an optical filter structure applied to the FoD (Fingerprint on Display) technology of the smartphone, which contains the microlens array, black matrix, and photodetector to recognize the fingerprint on a full touchscreen. First, we used optical ray tracing software, ZEMAX, to simulate a smartphone with FoD and a touching finger. We then further discussed how the aperture and microlens influence the fingerprint image in this design. Through numerical analysis and process constraint adjustment to optimize the structural design, we determined that a modulation transfer function (MTF) of 60.8% can be obtained when the thickness of the black matrix is 4 µm, allowing successful manufacturing using photolithography process technology. Finally, we used this filter element to take fingerprint images. After image processing, a clearly visible fingerprint pattern was successfully captured.

[Platelet-to-lymphocyte ratio as a biomarker for predicting coronary artery lesions in Chinese children with Kawasaki disease: a Meta analysis]. / è¡€å°æ¿ä¸Žæ·‹å·´ç»†èƒžæ¯”å€¼å¯¹ä¸­å›½å·å´Žç— æ‚£å„¿å† çŠ¶åŠ¨è„‰ç— å˜é¢„æµ‹ä»·å€¼çš„Meta分析.

OBJECTIVES: To systematically evaluate the value of the platelet-to-lymphocyte ratio (PLR) in predicting coronary artery lesions (CAL) in Chinese children with Kawasaki Disease (KD). METHODS: A comprehensive search was conducted in databases including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Data, China Biomedical Literature Database, and China Science and Technology Journal Database from inception to December 2022. The quality of the included literature was assessed using the Newcastle-Ottawa Scale, and a Meta analysis was performed using Stata 15.1. RESULTS: A total of ten published reports, involving 3 664 Chinese children with KD, were included in this Meta analysis, of whom 1 328 developed CAL. The Meta analysis revealed a sensitivity of 0.78 (95%CI: 0.71-0.83), specificity of 0.71 (95%CI: 0.61-0.80), overall diagnostic odds ratio of 8.69 (95%CI: 5.02-15.06), and an area under the curve of the summary receiver operating characteristic of 0.82 (95%CI: 0.78-0.85) for PLR in predicting CAL in the children with KD. The sensitivity, specificity, and area under the curve of summary receiver operating characteristic were lower for PLR alone compared to PLR in combination with other indicators. Sensitivity analysis demonstrated the stability of the Meta analysis results with no significant changes upon excluding individual studies. However, a significant publication bias was observed (P<0.001). CONCLUSIONS: PLR demonstrates certain predictive value for CAL in Chinese children with KD.