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Pulmonary fibrosis (PF) is a lethal lung disease that predominantly affects older adults; however, whether and how aging triggers fibrosis remains unclear. To pinpoint the predominant initiating factors of PF, we first analyzed single-cell RNA sequencing (scRNA-seq) data from the lung tissues of 45 normal donors and 51 PF patients and found that aging might serve as the primary catalyst for PF development. To further investigate the influence of aging on PF formation, we conducted a comprehensive and thorough study employing a natural aging mouse model. We found that dynamic alterations in the quantity and types of collagen fibers during aging-induced PF progression, especially in collagenous (Col) I, emerged as the predominant driver of PF. We then investigated the regulation of Col I synthesis during aging using primary alveolar type 2 (AT2) cells and A549 cells line through conditioned media and Transwell coculture, and found that secretions—particularly plasminogen activator inhibitor (PAI)-1—from aged AT2 cells promoted fibrosis and enhanced collagen type I alpha 1 (Col1al) production via the transforming growth factor (TGF)-β/small mother against decapentaplegic (Smad)2/3 pathway. Furthermore, scRNA-seq and a histological analysis of human lung tissue demonstrated a significant upregulation of SERPINE1 (the gene encoding PAI-1) and PAI-1 expression in both aging lung tissue and AT2 cells, which was consistent with our findings from animal experiments, providing additional evidence for the pivotal role of PAI-1 during aging and the development of PF. Our research demonstrates that PAI-1, a crucial factor secreted by aging AT2 cells, exerts a pivotal role in promoting the synthesis of Col1a1 in fibroblasts, subsequently leading to Col I deposition, and in driving the progression of PF by mediating the TGF-β/Smad2/3 pathway. Our findings offer critical evidence for the involvement of epithelial dysfunction in age-related PF and provides potential novel therapeutic targets for clinical intervention.

Abstract Cervical cancer is the fourth most common malignant tumor among women globally, posing a significant threat to women’s health. In 2022, approximately 600,000 new cases were reported, and 340,000 deaths occurred due to cervical cancer. Magnetic resonance imaging (MRI) is the preferred imaging method for diagnosing, staging, and evaluating cervical cancer. However, manual segmentation of MRI images is time-consuming and subjective. Therefore, there is an urgent need for automatic segmentation models to identify cervical cancer lesions in MRI scans accurately. All MRIs in our research are from cervical cancer patients diagnosed by pathology at Tongren City People’s Hospital. Strict data selection criteria and clearly defined inclusion and exclusion conditions were established to ensure data consistency and accuracy of research results. The dataset contains imaging data from 122 cervical cancer patients, with each patient having 100 pelvic dynamic contrast-enhanced MRI scans. Annotations were jointly completed by medical professionals from Universiti Putra Malaysia and the Radiology Department of Tongren City People’s Hospital to ensure data accuracy and reliability. Additionally, a novel computer-aided diagnosis model named SwinUNeCCt is proposed. This model incorporates (i) A bidirectional hash-based agent multi-head self-attention mechanism, which optimizes the interaction between local and global features in MRI, aiding in more accurate lesion identification. (ii) Reduced computational complexity of the self-attention mechanism. The effectiveness of the SwinUNeCCt model has been validated through comparisons with state-of-the-art 3D medical models, including nnUnet, TransBTS, nnFormer, UnetR, UnesT, SwinUNetR, and SwinUNeLCsT. In semantic segmentation tasks without a classification module, the SwinUNeCCt model demonstrates excellent performance across multiple key metrics: achieving a 95HD of 6.25, an IoU of 0.669, and a DSC of 0.802, all of which are the best results among the compared models. Simultaneously, SwinUNeCCt strikes a good balance between computational efficiency and model complexity, requiring only 442.7 GFLOPs of computational power and 71.2 M parameters. Furthermore, in semantic segmentation tasks that include a classification module, the SwinUNeCCt model also exhibits powerful recognition capabilities. Although this slightly increases computational overhead and model complexity, its performance surpasses other comparative models. The SwinUNeCCt model demonstrates excellent performance in semantic segmentation tasks, achieving the best results among state-of-the-art 3D medical models across multiple key metrics. It balances computational efficiency and model complexity well, maintaining high performance even with the inclusion of a classification module.

This study demonstrates the benefits of high-quality and high-efficiency supersonic flame spraying, aids smart decision-making, and lays a theoretical basis for the practical application of iron-based amorphous coatings. By implementing an artificial neural network, a comprehensive design study that considers several factors and levels may effectively direct the optimization of process parameters, improve product surface performance, minimize expenses, and boost efficiency. This enables the raw materials to attain maximum efficiency in real-world applications. This work examined the technological parameters and properties of Fe-based amorphous nanocrystalline coating using supersonic flame spraying technology, utilizing a multi-factor and multi-level design analysis approach to conduct experimental parameter design. A BP neural network model was developed to investigate the impact of coal oil quantity, oxygen quantity, powder feeding rate and spraying distance on the porosity, hardness, bonding strength, and deposition efficiency of the coating. The powder and coating’s microstructures were analyzed using scanning electron microscopy and transmission electron microscopy. In addition, X-ray diffraction, synchronous thermal analysis, and other techniques were employed to observe and analyze the phase constitution and amorphous content of both the powder and the coating that was created. The computer simulation results were validated while optimizing the process parameters. The measurement of the ideal spraying process parameter range further improved the coating performance. The text discusses the mechanism of pore development at a microscopic level during spraying, as well as the connection between the formation principle of amorphous nanocrystalline and the coating performance. The results revealed that several components have mutual influence on the coating. Theoretically, the most favorable spray parameters for achieving optimal coating are as follows: a diesel flow rate of 23 L·h−1, oxygen flow rate of 51 L·h−1, a powder feeding rate of 72 g·min−1, and a spraying distance of 280 mm. To develop a high quality coating of Fe-based amorphous alloy that improves material surface performance, one must carefully select a suitable spraying material and employ the proper thermal spraying procedure. The coating yielded the following results: a thickness of 270 μm, a porosity of 1.3%, a binding strength of 80 MPa, and a hardness of 1110 HV0.3. The amorphousness degree of the coating was exhibited around 80%, with a nanocrystalline diameter was ranging from 3–5 nm. Crystallization of the coating is only possible above 600 ℃.

Interest in the phase behavior of hydrocarbons in shale reservoirs has grown in recent years. Petroleum fluid phase behavior has been observed to differ significantly between conventional reservoirs and shale reservoirs. Within shale reservoirs, notable surface-fluid interactions can lead to non-uniform molecule distribution and an alteration in fluid phase behavior, primarily caused by the existence of nano-scale porous materials. In this work, we study the phase behavior of methane in single cylindrical pore models. We apply the gauge Gibbs ensemble Monte Carlo (gauge-GEMC) simulation technique to investigate the phase behavior of methane in 4–10 nm single nanopores and calculate the saturation pressures at various temperatures using the grand canonical Monte Carlo (GCMC) simulation technique. A shift in the phase diagram has been found for methane in nanopores. As pore size decreases, the shift becomes more significant.

Background: The study aims to investigate the pharmacological basis and molecular mechanisms of resveratrol in the treatment of Alzheimer's disease (AD) and Parkinson's disease (PD) through the approach of treating different diseases with the same method, guided by traditional Chinese medicine theory. Utilizing network pharmacology and bioinformatics methods, this research aims to provide modern medical evidence for the theory of treating different diseases with the same method in traditional Chinese medicine. Methods: Omnibus from Swiss Target Prediction, TCMSP, SuperPred, SEA, HIT, CTD, TCMIP and Gene Expression Disease datasets for resveratrol related genes, Alzheimer's disease, and Parkinson's disease were obtained from the GEO database. Core targets were identified by weighted gene coexpression network analysis (WGCNA) and minimum absolute contraction and selection operator (LASSO). The expression of core targets was verified in AD and PD cell models. The immune characteristics of AD and PD were analyzed by CIBERSORT algorithm. Finally, the potential mechanism of resveratrol intervention on the core target was studied by molecular docking technique. Results: The results of network pharmacological analysis showed that resveratrol acted on 85 common targets such as STAT3 and CASP3, affected AGE-RAGE signaling pathway and PI3K-Akt signaling pathway, and showed the effect of ''same disease and different treatment'' for AD and PD. Three core targets associated with AD and PD (PLK4, FCGRT, and PRKAR2A) were finally identified through comprehensive transcriptome analysis, and experimentally verified in cell models of AD and PD. At the same time, the analysis of immune cell infiltration suggested that AD and PD had dysregulation of inflammation, and the core target was significantly related to M2 macrophages. Conclusion: Resveratrol may play a potential mechanism of ''treating the same disease with different diseases'' and target three core targets (PLK4, FCGRT and PRKAR2A) to improve the disease process of AD and PD by participating in the regulation of immune and inflammatory pathways. These findings have potential implications for clinical practice and future research.

Abstract BackgroundHypertension, a key modifiable risk factor for cardiovascular disease, is more prevalent among Black and low-income individuals. To address this health disparity, leveraging safety-net emergency departments for scalable mobile health (mHealth) interventions, specifically using text messaging for self-measured blood pressure (SMBP) monitoring, presents a promising strategy. This study investigates patterns of engagement, associated factors, and the impact of engagement on lowering blood pressure (BP) in an underserved population. ObjectiveWe aimed to identify patterns of engagement with prompted SMBP monitoring with feedback, factors associated with engagement, and the association of engagement with lowered BP. MethodsThis is a secondary analysis of data from Reach Out, an mHealth, factorial trial among 488 hypertensive patients recruited from a safety-net emergency department in Flint, Michigan. Reach Out participants were randomized to weekly or daily text message prompts to measure their BP and text in their responses. Engagement was defined as a BP response to the prompt. The k-means clustering algorithm and visualization were used to determine the pattern of SMBP engagement by SMBP prompt frequency—weekly or daily. BP was remotely measured at 12 months. For each prompt frequency group, logistic regression models were used to assess the univariate association of demographics, access to care, and comorbidities with high engagement. We then used linear mixed-effects models to explore the association between engagement and systolic BP at 12 months, estimated using average marginal effects. ResultsFor both SMBP prompt groups, the optimal number of engagement clusters was 2, which we defined as high and low engagement. Of the 241 weekly participants, 189 (78.4%) were low (response rate: mean 20%, SD 23.4) engagers, and 52 (21.6%) were high (response rate: mean 86%, SD 14.7) engagers. Of the 247 daily participants, 221 (89.5%) were low engagers (response rate: mean 9%, SD 12.2), and 26 (10.5%) were high (response rate: mean 67%, SD 8.7) engagers. Among weekly participants, those who were older (>65 years of age), attended some college (vs no college), married or lived with someone, had Medicare (vs Medicaid), were under the care of a primary care doctor, and took antihypertensive medication in the last 6 months had higher odds of high engagement. Participants who lacked transportation to appointments had lower odds of high engagement. In both prompt frequency groups, participants who were high engagers had a greater decline in BP compared to low engagers. ConclusionsParticipants randomized to weekly SMBP monitoring prompts responded more frequently overall and were more likely to be classed as high engagers compared to participants who received daily prompts. High engagement was associated with a larger decrease in BP. New strategies to encourage engagement are needed for participants with lower access to care.

Maternal diet is indispensable for the proper development of offspring, and the establishment of a well-functioning intestinal barrier is crucial for normal growth and development. Edible bird’s nest (EBN) has positive impacts on intestinal health, but the underlying mechanisms are unknown. Our study showed that maternal EBN supplementation downregulated the serum levels of diamine oxidase and D-lactate, elevated expression of tight junction proteins ZO-1, Occludin, and Claudin-1, and regulated the intestinal microbiota in rat offspring. Spearman’s correlation analysis revealed that Claudin-1, transforming growth factor-β (TGF-β), and transcription factor RUNX3 were positively correlated with changes in intestinal bacteria. EBN may upregulate the expression of TGF-β by modulating the intestinal microbiota composition, enhancing RUNX3 binding to the Claudin-1 promoter region to upregulate its expression. In conclusion, we demonstrated that maternal EBN supplementation during gestation and lactation enhanced intestinal barrier function by upregulating Claudin-1 in rat offspring.

Electric field measurement holds immense significance in various domains. The power supply and signal acquisition units of the sensor may be coupled with ground wire interference, which could result in reduced measurement accuracy. Moreover, this problem is often ignored by researchers. This paper investigated the origin of ground coupling interference in electric field sensors and its impact on measurement accuracy. A miniature undistorted electric field sensor with wireless transmission was compared with existing D-dot, microelectromechanical systems (MEMS), and optical sensors. The results indicate that MEMS and D-dot exhibit diminished accuracy in measuring electric fields under uniform conditions, owing to interference from ground wires. In the case of transmission lines with non-uniform conditions, the wireless sensor exhibited a measurement error of 5%, whereas the optical sensor showed an error rate of approximately 8%. However, the D-dot sensor displayed a measurement error exceeding 50%, whereas the MEMS sensor yielded an error as high as 150%. This means that the wireless sensor isolates the ground-coupled interference signal and realizes the distortion-free measurement of the electric field. The wireless sensors will find extensive applications in new power systems for intelligent equipment status perception, fault warning, and other scenarios.

The rock mass of open pit in cold regions is often affected by freezing-thawing cycles and long-term loads. In order to explore the influence of cold region environment on the stability of rock mass, the red sandstone of a project in northern Shaanxi is taken as the research object, starting with the macroscopic creep characteristics and meso-structure evolution characteristics of freezing-thawing rocks. The evolution of macro-mechanical indexes and meso-parameters during the creep process of freezing-thawing red sandstone is quantitatively analyzed through the loading and unloading creep test of freezing-thawing rock and the NMR detection. The results show that the pore size distribution fluctuates in a small range when the stress level is between 0.3σucs−0.5σucs, and when the stress level increases to 0.5σucs−0.6σucs, the proportion of small holes (T210 ms) increases, and freezing-thawing aggravates the increase of porosity in the creep stage, and the effect of freezing and thawing on porosity growth is more significant at high stress levels. The fractal theory is introduced to characterize the complexity of pore structure. It is found that the large pores have obvious fractal characteristics, while the fractal characteristics of small pores are not obvious. The total pore fractal dimension DT is positively correlated with porosity. The complexity of pore structure only affects the creep mechanical properties of rock when the porosity is large. The freezing-thawing-damage creep model of freezing-thawing effect and creep damage is established. The model curve can well reflect the creep characteristics of the freezing-thawing rock, which is in good agreement with the experimental curve. This study can provide a theoretical basis for rock engineering construction in freezig-thawing environment.

With the development of the petroleum industry and advancements in technology, gas injection techniques have gradually matured and become an important means to enhance oil recovery in reservoir development. Gas channeling is a major challenge in the process of gas injection development. The presence of gas channeling can lead to a decrease in the swept volume of gas flooding, severely affecting the effectiveness of gas injection development. This paper focuses on low-permeability reservoirs, comprehensively analyzing the development characteristics of low-permeability reservoirs and the dynamic characteristics of gas flooding production. It selects and evaluates indicators for assessing the development degree of gas channeling and establishes a fuzzy comprehensive evaluation method for evaluating gas channeling in the gas injection development of low-permeability reservoirs. Based on the evaluation values derived from the fuzzy comprehensive evaluation, it classifies the development levels of gas channeling. Application in oilfield cases shows that the evaluation results of this method are generally consistent with the dynamic response of production data, with high evaluation accuracy. This provides strong support for implementing gas channeling prevention and control measures on site and improving the effectiveness of gas injection development.

IntroductionNitrososphaeria, formerly known as Thaumarchaeota, constitute a diverse and widespread group of ammonia-oxidizing archaea (AOA) inhabiting ubiquitously in marine and terrestrial environments, playing a pivotal role in global nitrogen cycling. Despite their importance in Earth’s ecosystems, the cellular organization of AOA remains largely unexplored, leading to a significant unanswered question of how the machinery of these organisms underpins metabolic functions.MethodsIn this study, we combined spherical-chromatic-aberration-corrected cryo-electron tomography (cryo-ET), scanning transmission electron microscopy (STEM), and energy dispersive X-ray spectroscopy (EDS) to unveil the cellular organization and elemental composition of Nitrosopumilus maritimus SCM1, a representative member of marine Nitrososphaeria.Results and DiscussionOur tomograms show the native ultrastructural morphology of SCM1 and one to several dense storage granules in the cytoplasm. STEM-EDS analysis identifies two types of storage granules: one type is possibly composed of polyphosphate and the other polyhydroxyalkanoate. With precise measurements using cryo-ET, we observed low quantity and density of ribosomes in SCM1 cells, which are in alignment with the documented slow growth of AOA in laboratory cultures. Collectively, these findings provide visual evidence supporting the resilience of AOA in the vast oligotrophic marine environment.

Abstract Compared with traditional rigid actuators, soft actuators exhibit a large number of advantages, including enhanced flexibility, reconfigurability, and adaptability, which motivate us to develop artificial soft actuators with widespread applications. Soft actuators with MXene nanomaterials are regarded as highly promising candidates for advancing the development of bioinspired soft robotics as a consequence of their unprecedented physicochemical characteristics, such as high electronic conductivity, thermal conductivity, photothermal conversion capability, and abundant surface functional groups. Herein, a comprehensive overview of the recent advancement of soft actuators with MXene nanomaterials and their extensive applications from the perspective of bioinspiration is provided. First, synthetic methods of MXene and their properties are briefly summarized. Subsequently, soft actuators with MXene nanomaterials (including photoresponsive soft actuators, electroresponsive soft actuators, and chemoresponsive soft actuators) are sequentially investigated with a focus on the fabrication approaches, actuation properties, underlying mechanisms, and promising applications. At the end, the future challenges and opportunities for the rapid development of soft actuators with MXene nanomaterials are discussed.

As one of the most important ecosystems, the water body is losing water during the rapid development of the city. To understand the impacts on water body change during the rapid urbanization period, this study combines data from the OpenStreetMap platform with Landsat 5/Thematic Mapper images to effectively and accurately identify small urban water bodies. The findings indicate that the trained U-net convolutional neural network (U-Net) water body extraction model and loss function combining Focal Loss and Dice Loss adopted in this study demonstrate high precision in identifying water bodies within the main urban area of Hangzhou, with an accuracy rate of 94.3%. Trends of decrease in water areas with a continuous increase in landscape fragmentation, particularly for the plain river network, were observed from 1985 to 2010, indicating a weaker connection between water bodies resulting from rapid urbanization. Large patches of water bodies, such as natural lakes and big rivers, located at divisions at the edge of the city are susceptible to disappearing during the rapid outward expansion. However, due to the limitations and strict control of development, water bodies, referring to as wetland, slender canals, and plain river networks, in the traditional center division of the city, are preserved well. Combined with the random forest classification method and the U-Net water body extraction model, land use changes from 1985 to 2010 are calculated. Reclamation along the Qiantang River accounts for the largest conversion area between water bodies and cultivated land, constituting more than 90% of the total land use change area, followed by the conversion of water bodies into construction land, particularly in the northeast of Xixi Wetland. Notably, the conversion of various land use types within Xixi Wetland into construction land plays a significant role in the rise of the carbon footprint.

Micro- and nano-plastics (MNPs) are increasingly prevalent contaminants in marine ecosystems and have a variety of negative impacts on marine organisms. While their toxic impact on freshwater microalgae has been well-documented, limited research has been conducted on the influence of MNPs on marine red tide algae, despite their significant implications for human health and coastal ecological stability. This study investigated the physiological, biochemical and molecular reactions of the common harmful algal species, Heterosigma akashiwo, when exposed to polystyrene (PS) MNPs of 80 nm and 1 µm in size with the concentrations of 0, 1, 10, and 20 mg L−1 in 12 days. The results showed that 80 nm-sized MNPs (at concentrations of 10 mg L−1 and 20 mg L−1) inhibited algal growth. Despite the increased superoxide dismutase (SOD) activity and up-regulation of glutathione metabolism, exposure-induced oxidative stress remained the main cause of the inhibition. Up-regulation of aminoacyl-tRNA biosynthesis and amino acid biosynthesis pathways provide the necessary amino acid feedstock for the synthesis of antioxidant enzymes such as SOD. 1 µm sized PS MNPs increased chlorophyll a (Chl-a) content without significant effects on other parameters. In addition, H. akashiwo have an effective self-regulation ability to defend against two sized MNPs stress at concentrations of 1 mg L−1 by upregulating gene expression related to endocytosis, biotin metabolism, and oxidative phosphorylation. These results provided evidence that H. akashiwo was able to resist exposure to 1 µm MPs, whereas 80 nm NPs exerted a toxic effect on H. akashiwo. This study deepens our understanding of the interaction between MNPs and marine harmful algal at the transcriptional level, providing valuable insights for further evaluating the potential impact of PS MNPs on harmful algal blooms in marine ecosystems.

Harmful algal blooms (HABs) pose a global threat to the biodiversity and stability of local aquatic ecosystems. Rapid and accurate classification of microalgae and cyanobacteria in water is increasingly desired for monitoring complex water environments. In this paper, we propose a pulse feature-enhanced classification (PFEC) method as a potential solution. Equipped with a rapid measurement prototype that simultaneously detects polarized light scattering and fluorescence signals of individual particles, PFEC allows for the extraction of 38 pulse features to improve the classification accuracy of microalgae, cyanobacteria, and other suspended particulate matter (SPM) to 89.03%. Compared with microscopic observation, PFEC reveals three phyla proportions in aquaculture samples with an average error of less than 14%. In this paper, PFEC is found to be more accurate than the pulse-average classification method, which is interpreted as pulse features carrying more detailed information about particles. The high consistency of the dominant and common species between PFEC and microscopy in all field samples also demonstrates the flexibility and robustness of the former. Moreover, the high Pearson correlation coefficient accounting for 0.958 between the cyanobacterial proportion obtained by PFEC and the cyanobacterial density given by microscopy implies that PFEC serves as a promising early warning tool for cyanobacterial blooms. The results of this work suggest that PFEC holds great potential for the rapid and accurate classification of microalgae and cyanobacteria in aquatic environment monitoring.

Perfluoroalkyl substance (PFAS) existed ubiquitously in the environment and could be ingested unconsciously with food which posed a disease risk to human health. Swordtip squid (Uroteuthis edulis) is one of the most popular and highly consumed seafood worldwide, with wide distribution and abundant biomass. Therefore, it is of great importance to the health of the public by reducing the health risks of squid consumption while preserving the benefits of squid to humans. In this study, the PFAS and fatty acids in squids were tested from the southeast coastal regions of China, a major habitat for squids. Relative higher concentrations of PFAS in squid were found in the subtropical zone of southern China (mean: 15.90 ng/g·dw) compared to those of the temperate zone of northern China (mean: 11.77 ng/g·dw). The digestive system had high tissue/muscle ratio (TMR) values, and the pattern of TMR among the same carbon-chain PFAS was similar. Cooking methods have a significant contribution to eliminating PFAS (in squids). PFAS were transferred from squids to other mediums after cooking, so juice and oil should be poured out to minimize PFAS exposure into body. The result showed that squids can be regarded as a healthy food by health benefits associated with fatty acids. Estimated daily intake (EDI) had the highest level in Korea via consuming squids through cooking processes compared with other countries. Based on the assessment of the hazard ratios (HRs), there was a high exposure risk of perfluoropentanoic acid (PFPeA) via taking squids for human health. This research provided the theoretical guidance of aquatic product processing in improving nutrition and reducing harmful substances.

Per- and polyfluoroalkyl substances (PFAS) have widespread application in industrial and civil areas due to their unique physical and chemical properties. With the increasingly stringent regulations of legacy PFAS, various novel alternatives have been developed and applied to meet the market demand. Legacy and novel PFAS pose potential threats to the ecological safety of coastal areas, however, little is known about their accumulation and transfer mechanism, especially after cooking treatment. This study investigated the biomagnification and trophic transfer characteristics of PFAS in seafood from the South China Sea, and assessed their health risks after cooking. Fifteen target PFAS were all detected in the samples, of which perfluorobutanoic acid (PFBA) was dominant with concentrations ranging from 0.76 to 4.12 ng/g ww. Trophic magnification factors (TMFs) > 1 were observed for perfluorooctane sulfonate (PFOS) and 6:2 chlorinated polyfluoroalkyl ether sulfonic acid (F-53B), indicating that these compounds experienced trophic magnification in the food web. The effects of different cooking styles on PFAS occurrence were further explored and the results suggested that ΣPFAS concentrations increased in most organisms after baking, while ΣPFAS amounts decreased basically after boiling and frying. Generally, there is a low health risk of exposure to PFAS when cooked seafood is consumed. This work provided quantitative evidence that cooking methods altered PFAS in seafood. Further, suggestions to mitigate the health risks of consuming PFAS-contaminated seafood were provided.

Translational efficiency change is an important mechanism for regulating protein synthesis. Experiments with paired ribosome profiling (Ribo-seq) and mRNA-sequencing (RNA-seq) allow the study of translational efficiency by simultaneously quantifying the abundances of total transcripts and those that are being actively translated. Existing methods for Ribo-seq data analysis either ignore the pairing structure in the experimental design or treat the paired samples as fixed effects instead of random effects. To address these issues, we propose a hierarchical Bayesian generalized linear mixed effects model which incorporates a random effect for the paired samples according to the experimental design. We provide an analytical software tool, “riboVI,” that uses a novel variational Bayesian algorithm to fit our model in an efficient way. Simulation studies demonstrate that “riboVI” outperforms existing methods in terms of both ranking differentially translated genes and controlling false discovery rate. We also analyzed data from a real ribosome profiling experiment, which provided new biological insight into virus-host interactions by revealing changes in hormone signaling and regulation of signal transduction not detected by other Ribo-seq data analysis tools.