Controllable and reusable seesaw circuit based on nicking endonucleases.

Seesaw circuits are essential for molecular computing and biosensing. However, a notable limitation of seesaw circuits lies in the irreversible depletion of components, precluding the attainment of system recovery and rendering nucleic acid circuits non-reusable. We developed a brand-new method for creating controllable and reusable seesaw circuits. By using the nicking endonucleases Nt.BbvCI and Nt.Alwi, we removed "functional components" while keeping the "skeletal components" for recurrent usage. T-inputs were introduced, increasing the signal-to-noise ratio of AND logic from 2.68 to 11.33 and demonstrating compatibility. We identified the logic switching feature and verified that it does not impair circuit performance. We also built intricate logic circuits, such as OR-AND gate, to demonstrate the versatility of our methodology. This controllable reusability extends the applications of nanotechnology and bioengineering, enhancing the practicality and efficiency of these circuits across various domains.

Automatic high-throughput and non-invasive selection of sperm at the biochemical level.

BACKGROUND: Sperm selection, a key step in assisted reproductive technology (ART), has long been restrained at the preliminary physical level (morphology or motility); however, subsequent fertilization and embryogenesis are complicated biochemical processes. Such an enormous "gap" poses tough problems for couples dealing with infertility, especially patients with severe/total asthenozoospermia . METHODS: We developed a biochemical-level, automatic-screening/separation, smart droplet-TO-hydrogel chip (BLASTO-chip) for sperm selection. The droplet can sense the pH change caused by sperm's respiration products and then transforms into a hydrogel to be selected out. FINDINGS: The BLASTO-chip system can select biochemically active sperm with an accuracy of over 90%, and its selection efficiency can be flexibly tuned by nearly 10-fold. All the substances in the system were proven to be biosafe via evaluating mice fertilization and offspring health. Live sperm down to 1% could be enriched by over 76-fold to 76%. For clinical application to patients with severe/total asthenozoospermia, the BLASTO-chip could select live sperm from human semen samples containing 10% live but 100% immotile sperm. The rates of fertilization, cleavage, early embryos, and blastocysts were drastically elevated from 15% to 70.83%, 10% to 62.5%, 5% to 37.5%, and 0% to 16.67%, respectively. CONCLUSIONS: The BLASTO-chip represents a real biochemical-level technology for sperm selection that is completely independent of sperm's motility. It can be a powerful tool in ART, especially for patients with severe/total asthenozoospermia. FUNDING: This work was funded by the Ministry of Science and Technology of China, the Ministry of Education of China, and the Shenzhen-Hong Kong Hetao Cooperation Zone.

Modulation of chronic obstructive pulmonary disease progression by antioxidant metabolites from Pediococcus pentosaceus: enhancing gut probiotics abundance and the tryptophan-melatonin pathway.

Chronic obstructive pulmonary disease (COPD), a condition primarily linked to oxidative stress, poses significant health burdens worldwide. Recent evidence has shed light on the association between the dysbiosis of gut microbiota and COPD, and their metabolites have emerged as potential modulators of disease progression through the intricate gut-lung axis. Here, we demonstrate the efficacy of oral administration of the probiotic Pediococcus pentosaceus SMM914 (SMM914) in delaying the progression of COPD by attenuating pulmonary oxidative stress. Specially, SMM914 induces a notable shift in the gut microbiota toward a community structure characterized by an augmented abundance of probiotics producing short-chain fatty acids and antioxidant metabolisms. Concurrently, SMM914 synthesizes L-tryptophanamide, 5-hydroxy-L-tryptophan, and 3-sulfino-L-alanine, thereby enhancing the tryptophan-melatonin pathway and elevating 6-hydroxymelatonin and hypotaurine in the lung environment. This modulation amplifies the secretion of endogenous anti-inflammatory factors, diminishes macrophage polarization toward the M1 phenotype, and ultimately mitigates the oxidative stress in mice with COPD. The demonstrated efficacy of the probiotic intervention, specifically with SMM914, not only highlights the modulation of intestine microbiota but also emphasizes the consequential impact on the intricate interplay between the gastrointestinal system and respiratory health.

An investigation into multidimensional information encryption through structural color in electrically responsive subwavelength gratings.

In the vanguard of safeguarding data integrity, optical encryption and anti-counterfeiting measures are indispensable. Structural color, with its inherent optical exclusivity, including tunable chromaticity and intricate high-resolution patterning, stands at the forefront of this domain. Despite its promise, the proliferation of structural color technologies in anti-counterfeiting applications is curtailed by the exorbitant production costs and the current limitations in information capacity and security. Addressing these constraints, our study delineates a novel encryption paradigm that interlaces color and digital data within a subwavelength grating matrix. This synergy is fortified by a tri-layered encryption schema, amalgamating electrical response signatures, inherent optical attributes, and the robust RSA algorithm, thereby elevating the information capacity exponentially to 10n and reinforcing multi-faceted security throughout transmission. Our approach heralds a new era in the realm of high density, secure information storage.

Inhibition of kinetic random-distribution in DNA Seesaw gates and biosensors for complete leakage prevention.

DNA nanomaterials have a wide application prospect in biomedical field, among which DNA computers and biosensors based on Seesaw-based DNA circuit is considered to have the most development potential. However, the serious leakage of Seesaw-based DNA circuit prevented its further development and application. Moreover, the existing methods to suppress leakage can't achieve the ideal effect. Interestingly, we found a new source of leakage in Seesaw-based DNA circuit, which we think is the main reason why the previous methods to suppress leakage are not satisfactory. Therefore, based on this discovery, we use DNA triplex to design a new method to suppress the leakage of Seesaw-based DNA circuit. Its ingenious design makes it possible to perfectly suppress the leakage of all sources in Seesaw-based DNA circuit and ensure the normal output of the circuit. Based on this technology, we have constructed basic Seesaw module, AND gate, OR gate, secondary complex circuits and DNA detector. Experimental results show that we can increase the working range of the secondary Seesaw-based DNA circuit by five folds and keep its normal output signal above 90%, and we can improve the LOD of the Seesaw-based DNA detector to 1/11 of the traditional one(1.8pM). More importantly, we successfully developed a detector with adjustable detection range, which can theoretically achieve accurate detection in any concentration range. We believe the established triplex blocking strategy will greatly facilitate the most powerful Seesaw based DNA computers and biosensors, and further promote its application in biological systems.

Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.

MOTIVATION: Pediatric kidney disease is a widespread, progressive condition that severely impacts growth and development of children. Chronic kidney disease is often more insidious in children than in adults, usually requiring a renal biopsy for diagnosis. Biopsy evaluation requires copious examination by trained pathologists, which can be tedious and prone to human error. In this study, we propose an artificial intelligence (AI) method to assist pathologists in accurate segmentation and classification of pediatric kidney structures, named as AI-based Pediatric Kidney Diagnosis (APKD). RESULTS: We collected 2935 pediatric patients diagnosed with kidney disease for the development of APKD. The dataset comprised 93 932 histological structures annotated manually by three skilled nephropathologists. APKD scored an average accuracy of 94% for each kidney structure category, including 99% in the glomerulus. We found strong correlation between the model and manual detection in detected glomeruli (Spearman correlation coefficient r = 0.98, P < .001; intraclass correlation coefficient ICC = 0.98, 95% CI = 0.96-0.98). Compared to manual detection, APKD was approximately 5.5 times faster in segmenting glomeruli. Finally, we show how the pathological features extracted by APKD can identify focal abnormalities of the glomerular capillary wall to aid in the early diagnosis of pediatric kidney disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/ChunyueFeng/Kidney-DataSet.

Gaussian clustering and quantification of the sperm chromatin dispersion test using convolutional neural networks.

Sperm DNA fragmentation is a sign of sperm nuclear damage. The sperm chromatin dispersion (SCD) test is a reliable and economical method for the evaluation of DNA fragmentation. However, the cut-off value for differentiation of DNA fragmented sperms is fixed at 1/3 with limited statistical justification, making the SCD test a semi-quantitative method that gives user-dependent results. We construct a collection of deep neural networks to automate the evaluation of bright-field images for SCD tests. The model can detect valid sperm nuclei and their locations from the input images captured with a 20× objective and predict the geometric parameters of the halo ring. We construct an annotated dataset consisting of N = 3120 images. The ResNet 18 based network reaches an average precision (AP50) of 91.3%, a true positive rate of 96.67%, and a true negative rate of 96.72%. The distribution of relative halo radii is fit to the multi-peak Gaussian function (p > 0.99). DNA fragmentation is regarded as those with a relative halo radius 1.6 standard deviations smaller than the mean of a normal cluster. In conclusion, we have established a deep neural network based model for the automation and quantification of the SCD test that is ready for clinical application. The DNA fragmentation index is determined using Gaussian clustering, reflecting the natural distribution of halo geometry and is more tolerable to disturbances and sample conditions, which we believe will greatly improve the clinical significance of the SCD test.

Gene point mutation information translation and detection: Leveraging single base extension and CRISPR/Cas12a.

Gene point mutations play a significant role in the development of cancer. Therefore, developing a sensitive, specific, and universally applicable method for detecting gene point mutation is crucial for clinical diagnosis, prognosis, and cancer treatment. Recently, gene point mutation detection methods based on CRISPR/Cas12a detection have emerged. However, existing methods generally lack universality and specificity. In this study, we have developed a CRISPR/Cas12a-based method that combines improved allele-specific polymerase chain reaction and single base extension to translate the point mutation information in the target dsDNA into length information in ssDNA activators to overcome the limitations associated with PAM sequences in the CRISPR/Cas12a system. Our method achieved a detection limit of 0.002% for clinically significant EGFR T790M mutation. The CRISPR/Cas12a system we constructed demonstrates high sensitivity, specificity, and universality in detecting gene point mutations, making it a promising tool for clinical cancer screening.

Low-threshold lasing from bound states in the continuum with dielectric metasurfaces.

Bound states in the continuum (BICs) with extremely large quality factors (Q factors) can enhance the light-matter interaction and thus achieve low-threshold lasing. Here, we theoretically propose and experimentally demonstrate the low-threshold lasing at room temperature based on BICs. A threshold of approximately 306.7 W/cm2 (peak intensity) under a 7.5 ns-pulsed optical excitation is presented in an all-dielectric metasurface system consisting of titanium dioxide (TiO2) nanopillars with a dye film. Also, the multimode lasing can be excited by the higher pumping. Our results may find exciting applications in on-chip coherent light sources, filtering, and sensing.

Vitamin E stabilizes iron and mitochondrial metabolism in pulmonary fibrosis.

Introduction: Pulmonary fibrosis (PF) is a fatal chronic lung disease that causes structural damage and decreased lung function and has a poor prognosis. Currently, there is no medicine that can truly cure PF. Vitamin E (VE) is a group of natural antioxidants with anticancer and antimutagenic properties. There have been a few reports about the attenuation of PF by VE in experimental animals, but the molecular mechanisms are not fully understood. Methods: Bleomycin-induced PF (BLM-PF) mouse model, and cultured mouse primary lung fibroblasts and MLE 12 cells were utilized. Pathological examination of lung sections, immunoblotting, immunofluorescent staining, and real-time PCR were conducted in this study. Results: We confirmed that VE significantly delayed the progression of BLM-PF and increased the survival rates of experimental mice with PF. VE suppressed the pathological activation and fibrotic differentiation of lung fibroblasts and epithelial-mesenchymal transition and alleviated the inflammatory response in BLM-induced fibrotic lungs and pulmonary epithelial cells in vitro. Importantly, VE reduced BLM-induced ferritin expression in fibrotic lungs, whereas VE did not exhibit iron chelation properties in fibroblasts or epithelial cells in vitro. Furthermore, VE protected against mitochondrial dysmorphology and normalized mitochondrial protein expression in BLM-PF lungs. Consistently, VE suppressed apoptosis in BLM-PF lungs and pulmonary epithelial cells in vitro. Discussion: Collectively, VE markedly inhibited BLM-induced PF through a complex mechanism, including improving iron metabolism and mitochondrial structure and function, mitigating inflammation, and decreasing the fibrotic functions of fibroblasts and epithelial cells. Therefore, VE presents a highly potential therapeutic against PF due to its multiple protective effects with few side effects.

K+-Dependent Photocycle and Photocurrent Reveal the Uptake of K+ in Light-Driven Sodium Pump.

Engineering light-controlled K+ pumps from Na+-pumping rhodopsins (NaR) greatly expands the scope of optogenetic applications. However, the limited knowledge regarding the kinetic and selective mechanism of K+ uptake has significantly impeded the modification and design of light-controlled K+ pumps, as well as their practical applications in various fields, including neuroscience. In this study, we presented K+-dependent photocycle kinetics and photocurrent of a light-driven Na+ pump called Nonlabens dokdonensis rhodopsin 2 (NdR2). As the concentration of K+ increased, we observed the accelerated decay of M intermediate in the wild type (WT) through flash photolysis. In 100 mM KCl, the lifetime of the M decay was approximately 1.0 s, which shortened to around 0.6 s in 1 M KCl. Additionally, the K+-dependent M decay kinetics were also observed in the G263W/N61P mutant, which transports K+. In 100 mM KCl, the lifetime of the M decay was approximately 2.5 s, which shortened to around 0.2 s in 1 M KCl. According to the competitive model, in high KCl, K+ may be taken up from the cytoplasmic surface, competing with Na+ or H+ during M decay. This was further confirmed by the K+-dependent photocurrent of WT liposome. As the concentration of K+ increased to 500 mM, the amplitude of peak current significantly dropped to approximately ~60%. Titration experiments revealed that the ratio of the rate constant of H+ uptake (kH) to that of K+ uptake (kK) is >108. Compared to the WT, the G263W/N61P mutant exhibited a decrease of approximately 40-fold in kH/kK. Previous studies focused on transforming NaR into K+ pumps have primarily targeted the intracellular ion uptake region of Krokinobacter eikastus rhodopsin 2 (KR2) to enhance K+ uptake. However, our results demonstrate that the naturally occurring WT NdR2 is capable of intracellular K+ uptake without requiring structural modifications on the intracellular region. This discovery provides diverse options for future K+ pump designs. Furthermore, we propose a novel photocurrent-based approach to evaluate K+ uptake, which can serve as a reference for similar studies on other ion pumps. In conclusion, our research not only provides new insights into the mechanism of K+ uptake but also offers a valuable point of reference for the development of optogenetic tools and other applications in this field.

DNA strand displacement and TdT-Mediated DNA extension for swift, convenient, and quantitative evaluation of sperm DNA integrity and its clinical implications.

DNA integrity is crucial for the clinical pregnancy outcome and offspring health, while detection methods currently used (comet assay, TUNNEL assay, SCSA, etc.) can only provide the ratio of positive sperms at the cellular level and are unable to quantitatively detect the breakpoints at the DNA molecular level. Herein, we developed a detection system based on terminal deoxynucleotidyl transferase and DNA strand displacement fluorescent probe, which could efficiently and conveniently measure the number of 3'-OH (equivalent to the number of breakpoints). We further investigated the use of this technique in assisted reproduction after completing the principle verification, system optimization, and research on analytical performance. The detection system was shown to have a good linear range from 0.01 nM to 4 nM, using single-stranded DNA with 3'-OH end as the calibrator. The system underwent thorough optimization for stability and accuracy. In comparison to the widely accepted index DFI detected by SCSA, the new system demonstrated reasonable correlation and better prediction efficiency. Its applicability was also proven through its use in assisted reproductive technology procedures.

Design and Experiment of a Portable Near-Infrared Spectroscopy Device for Convenient Prediction of Leaf Chlorophyll Content.

This study designs a spectrum data collection device and system based on the Internet of Things technology, aiming to solve the tedious process of chlorophyll collection and provide a more convenient and accurate method for predicting chlorophyll content. The device has the advantages of integrated design, portability, ease of operation, low power consumption, low cost, and low maintenance requirements, making it suitable for outdoor spectrum data collection and analysis in fields such as agriculture, environment, and geology. The core processor of the device uses the ESP8266-12F microcontroller to collect spectrum data by communicating with the spectrum sensor. The spectrum sensor used is the AS7341 model, but its limited number of spectral acquisition channels and low resolution may limit the exploration and analysis of spectral data. To verify the performance of the device and system, this experiment collected spectral data of Hami melon leaf samples and combined it with a chlorophyll meter for related measurements and analysis. In the experiment, twelve regression algorithms were tested, including linear regression, decision tree, and support vector regression. The results showed that in the original spectral data, the ETR method had the best prediction effect at a wavelength of 515 nm. In the training set, RMSEc was 0.3429, and Rc2 was 0.9905. In the prediction set, RMSEp was 1.5670, and Rp2 was 0.8035. In addition, eight preprocessing methods were used to denoise the original data, but the improvement in prediction accuracy was not significant. To further improve the accuracy of data analysis, principal component analysis and isolation forest algorithm were used to detect and remove outliers in the spectral data. After removing the outliers, the RFR model performed best in predicting all wavelength combinations of denoised spectral data using PBOR. In the training set, RMSEc was 0.8721, and Rc2 was 0.9429. In the prediction set, RMSEp was 1.1810, and Rp2 was 0.8683.

The PRX-1/TLR4 axis promotes hypoxia-induced radiotherapy resistance in non-small cell lung cancer by targeting the NF-κB/p65 pathway.

Hypoxic lung cancer cells are highly resistant to radiation. Peroxiredoxin-1 (PRX-1), a transcriptional coactivator that enhances the DNA-binding activity of serum reactive factor, has been identified as a target for radiotherapy sensitization, but the underlying molecular mechanism remains unclear. This study aimed to investigate the influence of PRX-1 on radiotherapy sensitivity in hypoxic tumors. Hypoxic lung cancer cells exhibited radiotherapy-resistant phenotypes after irradiation, including increased proliferation, DNA damage repair, cell migration, invasion and stemness. Radio-resistant hypoxic lung cancer cells showed high expression levels of PRX-1. Furthermore, we observed that PRX-1 bound to the promoter region of TRL4 (-300 to -600) and promoted its transcription and expression and that PRX-1/TRL4 activated the NF-κB/p65 signaling pathway. Increased radiotherapy resistance of hypoxic lung cancer cells increased their ability to proliferate, migrate, and maintain stemness in vivo and in vitro. These findings suggest that PRX-1/TRL4 could be used as a target for the treatment of radiotherapy-resistant lung cancer cells and further provide a theoretical basis for the clinical treatment of hypoxic lung cancer cells.

PD-L1 and tumor-infiltrating CD8+ lymphocytes are correlated with clinical characteristics in pediatric and adolescent pituitary adenomas.

Objective: To investigate the levels of tumor-infiltrating CD8+ lymphocytes (CD8+ TILs) and the expression of programmed cell death receptor ligand 1 (PD-L1) in the tumor microenvironment (TME) of pediatric and adolescent pituitary adenomas (PAPAs) and analyze the correlation between their levels and the clinical characteristics. Methods: A series of 43 PAPAs cases were enrolled over a period of 5 years. To compare the TME of PAPAs and adult PAs, 43 PAPAs cases were matched with 60 adult PAs cases (30 cases were between 20 and 40 years old, and 30 cases were older than 40 years) for main clinical characteristics. The expression of immune markers in PAPAs was detected by immunohistochemistry, and their correlation with the clinical outcomes was analyzed using statistical methods. Results: In the PAPAs group, CD8+ TILs level was significantly lower (3.4 (5.7) vs. 6.1 (8.5), p = 0.001), and PD-L1 expression (0.040 (0.022) vs. 0.024 (0.024), p < 0.0001) was significantly higher as compared with the older group. The level of CD8+ TILs was negatively correlated with the expression of PD-L1 (r = -0.312, p = 0.042). Moreover, CD8+ TILs and PD-L1 levels were associated with Hardy (CD8, p = 0.014; PD-L1, p = 0.018) and Knosp (CD8, p = 0.02; PD-L1, p = 0.017) classification. CD8+ TILs level was associated with high-risk adenomas (p = 0.015), and it was associated with the recurrence of PAPAs (HR = 0.047, 95% CI 0.003-0.632, p = 0.021). Conclusion: Compared with the TME in adult PAs, the TME in PAPAs was found to express a significantly altered level of CD8+ TILs and PD-L1. In PAPAs, CD8+ TILs and PD-L1 levels were associated with clinical characteristics.

Phase Separation of DNA-Encoded Artificial Cells Boosts Signal Amplification for Biosensing.

Life-like hierarchical architecture shows great potential for advancing intelligent biosensing, but modular expansion of its sensitivity and functionality remains a challenge. Drawing inspiration from intracellular liquid-liquid phase separation, we discovered that a DNA-encoded artificial cell with a liquid core (LAC) can enhance peroxidase-like activity of Hemin and its DNA G-quadruplex aptamer complex (DGAH) without substrate-selectivity, unlike its gelled core (GAC) counterpart. The LAC is easily engineered as an ultrasensitive biosensing system, benefiting from DNA's high programmability and unique signal amplification capability mediated by liquid-liquid phase separation. As proof of concept, its versatility was successfully demonstrated by coupling with two molecular recognition elements to monitor tumor-related microRNA and profile cancer cell phenotypes. This scalable design philosophy offers new insights into the design of next generation of artificial cells-based biosensors.

Effect of Lactobacillus delbrueckii subsp. lactis on vaginal radiotherapy for gynecological cancer.

The aim of this study was to evaluate the effect of Lactobacillus delbrueckii subsp. lactis (L.del) on vaginal microbiota (VM) dysbiosis and vaginal radiation injury in gynecologic cancer patients. The inhibitory effects of L.del on cervical cancer cells were also studied in vitro. Gynecologic cancer patients receiving radiotherapy were randomized into control and L.del intervention groups. The control group received radiotherapy, while the intervention group received radiotherapy and L.del intervention (1 capsule/day placed into the deep vagina from the first day of radiotherapy until the end of treatment). Vaginal swab samples were collected on the first day pre-treatment and the last day post-treatment. DNA from 54 patients was extracted and assessed by the 16S rRNA sequencing method. Radiotherapy resulted in vaginal microbiome dysbiosis characterized by increased phylogenetic diversity and increased abundance of Brevundimonas, Streptococcus and Prevotella, but a decreased abundance of Lactobacillus. Level 2 vaginal radiation injury was positively associated with the abundance of Brevundimonas and gram-negative non-fermenting bacteria. Administration of L.del attenuated the reduction of Lactobacillus while also inhibiting the abundance of Streptococcus and Prevotella, thereby ameliorating radiotherapy-related vaginal microbiota dysbiosis. CLD inhibited the in vitro proliferation of SiHa cells by altering the expression of BCL2, HPV16-E6, HPV16-E7, IL6, MAP7, BAX, Caspase-3, Caspase-9 and LTF. In conclusion, L. del application can alleviate radiation-induced vaginal dysbiosis and restore Lactobacillus dominance of the vaginal microbiome. Moreover, CLD was found to inhibit cell growth and promote the apoptosis of SiHa cells in vitro. The registration number for this clinical trial is ChiCTR1900021784.

Fluorescent Turn-On Probes for Visualizing GPx4 Levels in Live Cells and Predicting Drug Sensitivity.

Glutathione peroxidase 4 (GPx4) is the membrane peroxidase in mammals that is essential for protecting cells against oxidative damage and critical for ferroptosis. However, no live cell probe is currently available to specifically label GPx4. Herein, we report both inhibitory and noninhibitory fluorescent turn-on probes for specific labeling of GPx4 in live cells. With these probes, the GPx4 expression levels and degradation kinetics in live cells could be visualized, and their real-time responses to the cellular selenium availability were revealed. These probes could also potentially serve as staining reagents to predict the sensitivity of GPx4-related ferroptosis drugs. In view of these features, these GPx4-selective probes will offer opportunities for a deeper understanding of GPx4 function in natural habitats and hold great promise for biomedical applications.

Quantitative image-based collagen structural features predict the reversibility of hepatitis C virus-induced liver fibrosis post antiviral therapies.

The novel targeted therapeutics for hepatitis C virus (HCV) in last decade solved most of the clinical needs for this disease. However, despite antiviral therapies resulting in sustained virologic response (SVR), a challenge remains where the stage of liver fibrosis in some patients remains unchanged or even worsens, with a higher risk of cirrhosis, known as the irreversible group. In this study, we provided novel tissue level collagen structural insight into early prediction of irreversible cases via image based computational analysis with a paired data cohort (of pre- and post-SVR) following direct-acting-antiviral (DAA)-based treatment. Two Photon Excitation and Second Harmonic Generation microscopy was used to image paired biopsies from 57 HCV patients and a fully automated digital collagen profiling platform was developed. In total, 41 digital image-based features were profiled where four key features were discovered to be strongly associated with fibrosis reversibility. The data was validated for prognostic value by prototyping predictive models based on two selected features: Collagen Area Ratio and Collagen Fiber Straightness. We concluded that collagen aggregation pattern and collagen thickness are strong indicators of liver fibrosis reversibility. These findings provide the potential implications of collagen structural features from DAA-based treatment and paves the way for a more comprehensive early prediction of reversibility using pre-SVR biopsy samples to enhance timely medical interventions and therapeutic strategies. Our findings on DAA-based treatment further contribute to the understanding of underline governing mechanism and knowledge base of structural morphology in which the future non-invasive prediction solution can be built upon.

Identifying Influential Nodes in Social Networks: Exploiting Self-Voting Mechanism.

The influence maximization (IM) problem is defined as identifying a group of influential nodes in a network such that these nodes can affect as many nodes as possible. Due to its great significance in viral marketing, disease control, social recommendation, and so on, considerable efforts have been devoted to the development of methods to solve the IM problem. In the literature, VoteRank and its improved algorithms have been proposed to select influential nodes based on voting approaches. However, in the voting process of these algorithms, a node cannot vote for itself. We argue that this voting schema runs counter to many real scenarios. To address this issue, we designed the VoteRank* algorithm, in which we first introduce the self-voting mechanism into the voting process. In addition, we also take into consideration the diversities of nodes. More explicitly, we measure the voting ability of nodes and the amount of a node voting for its neighbors based on the H-index of nodes. The effectiveness of the proposed algorithm is experimentally verified on 12 benchmark networks. The results demonstrate that VoteRank* is superior to the baseline methods in most cases.