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Abstract Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

Abstract Sharing the hardware platform between diverse information systems to establish full cooperation among different functionalities has attracted substantial attention. However, broadband multifunctional integrated systems with large operating frequency ranges are challenging due to the bandwidth and computing speed restrictions of electronic circuitry. Here, we report an analog parallel processor (APP) based on the silicon photonic platform that directly discretizes and parallelizes the broadband signal in the analog domain. The APP first discretizes the signal with the optical frequency comb and then adopts optical dynamic phase interference to reassign the analog signal into 2N parallel sequences. Via photonic analog parallelism, data rate and data volume in each sequence are simultaneously compressed, which mitigates the requirement on each parallel computing core. Moreover, the fusion of the outputs from each computing core is equivalent to directly processing broadband signals. In the proof-of-concept experiment, two-channel analog parallel processing of broadband radar signals and high-speed communication signals is implemented on the single photonic integrated circuit. The bandwidth of broadband radar signal is 6 GHz and the range resolution of 2.69 cm is achieved. The wireless communication rate of 8 Gbit/s is also validated. Breaking the bandwidth and speed limitations of the single-computing core along with further exploring the multichannel potential of this architecture, we anticipate that the proposed APP will accelerate the development of powerful opto-electronic processors as critical support for applications such as satellite networks and intelligent driving.

The collapse and damage of inclined rock and soil masses caused by subsidence in mining goaf areas pose serious geological risks. These hazards are not only highly destructive and widespread but also occur suddenly, endangering mine operations and human safety. Traditional stability evaluation methods often overlook the variations in thrust caused by the settlement of goaf blocks at the leading edge locking section, making it difficult to dynamically evaluate mine slope stability. This limits the effectiveness of early warning and prevention strategies for geological disasters in mines. To address these challenges, this study introduces a dynamic stability evaluation method tailored for mine slopes, targeting the landslide formation mechanisms in mining goaf areas. The first involves constructing a settlement analysis model for the goaf areas to calculate the settlement range of the rock mass above the goaf and the resulting impact forces. The proposed model helps analyze how settlement affects the stress field of slopes. Therefore, the traditional unbalanced thrust method is modified. During stability evaluation, the safety factor of the slope’s locking section under the subsidence effect of the goaf was analyzed. When the safety factor of the locking section (SFk) is less than 1, the residual strength needs to be considered to calculate the overall safety factor (SF) of the slope. If SFk exceeds 1, the section remains intact, allowing the SF to be calculated under original working conditions. The Jiweishan case in Wulong, Chongqing, illustrates the limitations of traditional methods, which neglected the settlement and locking section damage, overestimating the safety factor at 1.355. The improved method, accounting for these effects, found the locking section’s safety factor at 0.667, indicating damage and an overall landslide safety factor of 0.979. This finding aligns with the observed failure and instability mechanism of the mine goaf landslide. When the weight of the settlement slope at the rear edge is large, settlement causes instantaneous shear failure of the landslide locking section, substantially reducing the stability of the Jiweishan landslide. The settlement–horizontal displacement ratio (SHDR) of the slope is crucial in dynamic stability analysis for goaf areas. An SHDR greater than 0.73 indicates significant stability variations, leading to instability under working conditions previously deemed safe. This improved method offers a more accurate assessment of mine slope stability by considering goaf settlement and locking section damage, providing a valuable tool for managing similar geological disasters.

The interface friction between prosthetic socket and residual limb tends to cause skin injury and pain. The frictional pain was systematically studied based on skin tribological behaviors and brain activation. The results showed that the skin frictional pain was affected by the combination of friction and mechanical properties of anatomic regions and liner materials. The low elastic modulus and good viscoelasticity of anatomic regions or high adhesion and good compliance of liner materials both can increase the frictional pain threshold and decease the injury. The main brain activation related to frictional pain located in the primary somatosensory cortex (SI), secondary somatosensory cortex (SII), and prefrontal cortex (PFC). The brain negative activation increased and the activation area decreased with the increased pain intensity. The features of $\alpha $ activity, $\beta $ activity, and $\alpha _{\text {peak}}$ extracted from EEG signals were effective in the recognition of pain state, but cannot recognize the pain intensities.

Abstract Background There are still gaps in the study of the miRNA and its SNPs in some diseases such as non-small cell lung cancer (NSCLC). The study aimed to provide useful information on the treatment of NSCLC by investigating the association between miR-21 and its SNPs and NSCLC susceptibility. Methods The serum of NSCLC patients (n = 205) and cancer-free controls (n = 217) were collected in this study for RNA extraction. The qRT-PCR was used to evaluate the expression of miR-21 and Taqman qPCR was used for genotyping and quantifying miR-21 SNPs (rs1292037, rs6504593). The association of the expression of miR-21, the miR-21 SNPs and their interactions with the susceptibility of NSCLC patients were analysed using logistic regression analysis in this study. Results This study showed that the overexpression of miR-21 was related to NSCLC. The C allele and CC genotypes of rs1292037 and rs6504593 were associated with the increased risk of NSCLC susceptibility. Moreover, the interactions of rs1292037 and rs6504593 were also a risk factor for NSCLC. The CC genotypes of rs1292037 and rs6504593 were associated with the increase of miR-21 expression. Conclusion The overexpression of miR-21, the miR-21 SNPs rs1292037 and rs6504593 and their interactions were associated with NSCLC susceptibility. MiR-21 and its SNPs have potential for being targets in the therapy of NSCLC. This study provided important information for the treatment of NSCLC.

This study aims to explore how to deepen the construction of pharmacology course challenges based on the "golden course" standards and evaluate its application effects in improving course quality and students' comprehensive abilities. By integrating cutting-edge technologies with disciplinary knowledge, multidisciplinary teaching content was designed to promote curriculum innovation. A teaching method combining a three-tiered interactive model with case analysis was adopted to enhance student engagement in class. The study also incorporated virtual simulation experiments and innovative practices to further strengthen the integration of theory and practice, helping students better apply their knowledge to real-world scenarios. A comprehensive assessment of teaching effectiveness was conducted to scientifically measure students' learning outcomes and capability improvements. Through optimized instructional design, intensified skill training, enriched practical approaches, and balanced evaluation mechanisms, this study not only significantly enhanced course quality and student abilities but also provided valuable practical insights for the development of higher education.

Scoliosis is among the most prevalent diseases affecting teenagers. However, traditional scoliosis screening methods often resort to physical examination or radiographic imaging. The two ways both rely on experts with high costs, which are not suitable for wide-range screening. Besides, estimating Cobb angle level only using natural images are challenging. To tackle these issues, we propose a multi-grained scoliosis detection framework by jointly estimating severity level and Cobb angle level of scoliosis from a natural image instead of a radiographic image, which has not been explored before. Specifically, we regard scoliosis estimation as an ordinal regression problem, and transform it into a series of binary classification sub-problems. Besides, we adopt the visual attention network with large kernel attention as the backbone for feature learning, which can model local and global correlations with efficient computations. The feature learning and the ordinal regression is put into an end-to-end framework, in which the two tasks of scoliosis severity level estimation and scoliosis angle level estimation are jointly learned and can contribute to each other. Extensive experiments demonstrate that our approach outperforms state-of-the-art methods as well as human performance, which provides a promising and economical solution to wide-range scoliosis screening. Particularly, our approach achieves accuracies of 94.90% and 79.62% in estimating severity level and Cobb angle level, improving large margins of 4.90% and 12.15% over existing natural image based scoliosis detection performance, respectively. The code is available at https://github.com/RuiChen-stack/MGScoliosis.

Abstract In recent years, combined drug screening has played a very important role in modern drug discovery. Generally, synergistic drug combinations are crucial in treatment for many diseases. However, the toxic side effects of drug combinations are probably increased with the increase of drugs numbers, so the accurate prediction of toxic side effects of drug combinations is equally important. In this paper, we built a Metapath-based Aggregated Embedding Model on Single Drug–Side Effect Heterogeneous Information Network (MAEM-SSHIN), which extracts feature from a heterogeneous information network of single drug side effects, and a Graph Convolutional Network on Combinatorial drugs and Side effect Heterogeneous Information Network (GCN-CSHIN), which transforms the complex task of predicting multiple side effects between drug pairs into the more manageable prediction of relationships between combinatorial drugs and individual side effects. MAEM-SSHIN and GCN-CSHIN provided a united novel framework for predicting potential side effects in combinatorial drug therapies. This integration enhances prediction accuracy, efficiency, and scalability. Our experimental results demonstrate that this combined framework outperforms existing methodologies in predicting side effects, and marks a significant advancement in pharmaceutical research.

ABSTRACT Objective Total hip arthroplasty (THA) is currently one of the most effective treatment methods for end‐stage hip joint disease, and its long‐term effectiveness largely depends on the accurate placement of the acetabular prosthesis. In conventional surgery, the placement of the acetabular prosthesis mainly relies on the surgeon's clinical experience and surgical techniques. To further improve the accuracy of prosthesis placement, a new robotic system for THA is designed. The purpose of this study is to verify the effectiveness and safety of THA assisted by this robotic system. Method A multicenter, prospective, randomized controlled, superiority study design was adopted with statistical methods of t test and Chi‐squared test. Participants undergoing primary THA have been enrolled in three centers of joint surgery in China since July 17, 2023. Robotic THA was operated in the experimental group, and conventional instruments were used in the control group. The primary outcome is the proportion of anteversion and inclination angles in the safe zone. The secondary outcomes include operation time, WOMAC score, Harris score, SF‐36 health questionnaire, dislocation rate of hip joint, and rates of adverse events and serious adverse events. Results A total of 138 patients were included in this study. The proportion of both anteversion and inclination angles in the safe zone was 92.2% in the experimental group and 50.8% in the control group, with significant difference (p 0.05). The dislocation rate of hip joint in the experimental group and control group were 3.0% and 1.5%, respectively, without significant difference (p > 0.05). The rate of adverse events and severe adverse events in the experimental group and control group also showed no significant difference (p > 0.05). No adverse events or serious adverse events were judged to be “definitely related” to the experimental instruments. Conclusion Robotic THA could prolong the operation time within an acceptable range, but more precise acetabular prosthesis positioning could be obtained when compared with conventional surgery. Besides, no significant difference was found in function scores, dislocation rate or other adverse events, which indicates that this new robot system shows both good effectiveness and safety in THA. Trial Registration Clinical Trials: NCT05947734

Friction is a considerable boundary condition in aluminum alloy hot extrusion. In this study, ball-on-disc friction tests at temperatures of 25–500 °C were performed to equivalently simulate the interface tribological behaviors between Al–Mg–Si–Cu alloy and die steel in hot extrusion. The wear tracks and wear debris on disc samples were observed by means of ultradepth 3D microscopy, field-emission scanning microscope and energy dispersive spectroscopy. The change trends of wear depth, width and wear rate of aluminium disc with temperature and wear cycles were investigated. The evolutions of wear mechanism and friction coefficient with temperature were revealed. A mechanical analytical model for identifying adhesion and ploughing friction components during friction was established. The results show that as temperature rises, wear rate of aluminum disc increases gradually, while the average friction coefficient increases first rapidly and then decreases, which is associated with the changes of friction and wear mechanisms. The adhesion friction force constitutes the majority of total friction force, while ploughing friction force accounts for less than 3 %. Compared with the large variation of adhesion friction coefficient during friction, shear friction stress can tend to be stable and is not affected by the change of contact area, which may can better characterize the adhesion frictional behavior of die interface in aluminum alloy hot extrusion. The quantitative relationship between temperature and steady shear friction stress was described by an inverse polynomial peak function.

Abstract Background Pancreatic cancer (PC) is a highly aggressive malignancy with a poor prognosis due to its late-stage diagnosis and limited treatment options. Objectives This study aimed to elucidate the molecular mechanisms underlying PC progression and identify potential molecular targets for its diagnosis and treatment. Methods DAZAP1 expression in PC tissues, normal tissues and cell lines was assessed using immunohistochemistry (IHC), reverse transcription–quantitative polymerase chain reaction (RT–qPCR) and western blotting. DAZAP1 knockdown was achieved through plasmid transfection, and its effects on ferroptosis and PC progression were evaluated using RT–qPCR, western blotting, CCK-8 assays, EdU staining, Fe2+ content measurement, reactive oxygen species (ROS) detection, wound healing and Transwell migration assays. Results DAZAP1 expression was significantly upregulated in PC tissues and cell lines compared to normal counterparts. DAZAP1 knockdown suppressed PC cell proliferation and induced ferroptosis, while ferroptosis inhibition reversed these effects, enhancing PC cell proliferation and metastasis. Conclusions DAZAP1 suppression promotes ferroptosis, thereby inhibiting PC cell proliferation and metastasis. These findings suggest that DAZAP1 is a potential therapeutic target for PC.

Abstract Air pollution is strongly associated with autoimmune diseases (ADs), however, the genetic causality between them remains poorly understood. Therefore, the aim of this study is to determine the relationship between common air pollutants and ADs through Mendelian randomization (MR) analysis. We conducted a MR study using aggregated data from publicly available genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) associated with 5 common air pollutants are used as instrumental variables. Random-effects inverse variance weighted (IVW) is used as the primary method to assess causal relationships, with results reported in terms of odds ratios (OR). In addition, we used a two-step MR to assess the mediating role of common risk factors for ADs in the effects of air pollution on ADs. Our analysis revealed causal associations between selected air pollutants and specific ADs. Exposure to nitrogen oxides was positively associated with the risk of rheumatoid arthritis (RA) (OR = 1.47,95% CI 1.01–2.14, P = 0.043), Sjogren’s syndrome (SS) (OR = 2.29,95% CI 1.08–4.89, P = 0.032), and systemic lupus erythematosus (OR = 7.26,95% CI 2.25–23.40, P = 9.10E−04). Genetically predicted PM2.5 and PM10 were risk factors for ulcerative colitis (OR = 1.68,95% CI 1.05–2.68, P = 0.032) and psoriasis (OR = 1.34,95% CI 1.02–1.76, P = 0.037), respectively. Our results also suggest a negative causal relationship between PM2.5–10 and SS (OR = 0.29, 95% CI 0.10–0.90, P = 0.032). In risk factor-related mediation analyses, BMI and smoking mediated 6% (95% CI 1–10%) and 9% (95% CI 2–17%) of the effect of nitrogen oxides on RA, respectively. This study provides evidence of a causal relationship between air pollutants and specific ADs risks, suggesting that improving air pollution may be important in preventing ADs.

Based on the good reducibility and non-pollution of phenolic acid, the phenolic acid-based gold nanosensor system was established to realize sensitive detection of nitrite and sulfite. Different phenolic acids were used to reduce chlorauric acid to prepare gold nanoparticles (AuNPs). The optimal phenolic acid was gallic acid (GA) by ultraviolet spectrum and electrochemical impedance spectrum method. The GA@AuNPs@Au electrodes were prepared by electrodeposition and the electrochemical behaviors of nitrite and sulfite were characterized by linear scanning voltammetry (LSV). The optimized system conditions were as follows: GA concentration 1 mmol/L, incubation temperature 70 ℃, reaction time 60 min, pH6.0 phosphate buffer solution concentration 0.15 mol/L. The concentration of nitrite and sulfite in the range of 0.001 to 7 mmol/L showed a good linear relationship with the peak oxidation current (R2>0.994), and the detection limits were 0.20 μmol/L and 0.24 μmol/L (S/N=3), respectively. The modified electrode has good reproducibility and stability, and it can be used for the simultaneous determination of nitrite and sulfite in real samples.

To investigate the differences in the ability of egg yolk lipids to alleviate the decline in learning and cognitive abilities in mice under different temperature treatments. This study utilized a mouse model of cognitive impairment to compare the varying impacts on learning and cognitive functions resulting from 95 ℃ (30 min in water bath) and 121 ℃ (30 min in sterilization pot) heat treatments of egg yolk lipid components. The research results showed that compared with 121 ℃ heat treatment of egg yolk lipids, 95 ℃ heat treatment of egg yolk lipids effectively reduced the phosphorylation of Tau protein and the expression of Aβ1-40 and GSK-3β, downregulated the expression of pro-inflammatory factors, and had a better effect on improving the learning and memory abilities of mice. The levels of polyunsaturated fatty acids and DHA in 95 ℃ heat treatment of egg yolk lipids were significantly increased compared to those treated at 121 ℃ (P

Abstract Background Motion complexity is necessary for adapting to external changes, but little is known about trunk motion complexity during seated perturbation in individuals with spinal cord injury (SCI). We aimed to investigate changes following SCI in trunk segmental motion complexity across different perturbation directions and how they affect postural control ability in individuals with SCI. Methods A total of 17 individuals with SCI and 18 healthy controls participated in challenging sagittal-seated perturbations with hand protection. Upper arm activation was measured using surface electromyography for trial consistency. Motion complexity parameters, quantified across three degrees of freedom, was assessed using relative angular acceleration from six trunk segments obtained through motion capturing system. Motion performance parameters were assessed using center of pressure (CoP) measurements from a force plate, including settling time, maximum CoP displacement (MD) variability, and steady-state error. Statistical analyses examined group and direction differences, while complexity-performance relationships were evaluated using multiple response least partial squares regression. Results Compared to healthy controls, individuals with SCI showed significantly lower motion complexity in the lumbar and upper thoracic segments (approximately10% − 20%), with identical settling time and higher MD variability. Backward perturbations, as opposed to forward perturbations, resulted in reduced complexity in the aforementioned segments and increased steady-state error. Lower lumbar rotation complexity negatively correlated with MD variability (β = -0.240) and steady-state error (β = -0.485) in individuals with SCI, while showing a minor positive correlation with settling time (β = 0.152) during backward perturbation. Conclusion Simplified motion control in individuals with SCI may arise from uncoordinated lumbar and overactive thoracic neuromuscular control, compromising stability despite maintaining speed. Increasing lumbar motion complexity could enhance postural stability and accuracy during backward perturbation, representing a potential target for developing seated balance rehabilitation strategies and promoting more adaptive trunk control.

Semantic segmentation techniques for remote sensing scene understanding have significantly advanced, enhancing the refined Earth observation. However, most methods highly depend on extensive annotated data, leading to performance deterioration in complex high-resolution remote sensing cross-domain scenes, where variations in image conditions and environments are prevalent. Domain adaptive semantic segmentation (DASS) has been proposed to mitigate the reliance on dense and costly annotations, typically using stagewise training. This article addresses three key challenges in existing DASS methods: 1) insufficient warmup training, limiting potential performance gains; 2) rigid pseudolabel threshold settings in self-training (ST) result in performance bottlenecks; 3) entropy-based prediction bias alone fails to effectively identify high-confidence noise early in ST. To address these issues, we propose a novel threshold-free pseudolabel learning framework, TPL-DA. During the warmup stage, we introduce a multiview bidirectional consistency learning mechanism within a teacher–student architecture. This mechanism employs a bias-free data augmentation strategy, fostering consistent bidirectional predictions in teacher–student networks, thereby enhancing domain generalization and feature robustness. Our multiscale context-enhanced prediction module further amplifies this. In the ST stage, we propose a dynamic threshold-free pseudolabel learning strategy that utilizes well-aligned feature prototypes in the feature space to guide pseudolabel generation in the probability space, eliminating the threshold constraints. In addition, we model uncertainty using relative entropy and incorporate it into the optimization objective to manage high-confidence noise. Extensive experiments on the LoveDA, Potsdam, and Vaihingen datasets demonstrate that TPL-DA consistently outperforms existing methods and popular benchmarks, significantly enhancing DASS performance across diverse cross-domain scenes.

Abstract Objective Ovarian tissue cryopreservation has become a promising alternative for fertility preservation in cancer patients, allowing ovarian tissue to be stored for future autotransplantation. Oxidative stress damage occurring during the cryopreservation process may impact tissue quality and function. This study aims to investigate the protective effects and potential mechanisms of Mitoquinone (MitoQ), a mitochondria-targeted derivative of the antioxidant ubiquinone, during the vitrification of ovarian tissue in mice. Methods KGN cells were treated with various concentrations (0.1, 1, 10, and 50 μM) of MitoQ to determine the optimal concentration. Female ICR mice were divided into three groups: control, conventional vitrification, and MitoQ-supplemented vitrification. Ovarian samples were cryopreserved, thawed, and assessed for tissue morphology using Hematoxylin and Eosin (H&E) staining, and mitochondrial changes using immunofluorescence, transmission electron microscopy, and Western blot analysis. RNA sequencing (RNA-seq) was employed to explore potential protective mechanisms. Autotransplantation experiments were conducted, and the long-term effects of MitoQ on ovarian function were evaluated by counting follicle numbers through H&E staining and measuring serum estradiol and AMH levels using ELISA. Results MitoQ at 1 μM was found to be the optimal concentration for maintaining follicular morphology after vitrification. It effectively reduced mitochondrial oxidative damage, preserved mitochondrial morphology, and regulated the expression of mitochondrial dynamics proteins (Drp1 and Mfn2). RNA-seq and Western blot analyses revealed that MitoQ inhibited the p38 MAPK pathway, thereby reducing apoptosis. Additionally, autotransplantation experiments showed that MitoQ treatment significantly increased follicle counts, estradiol (E2), and anti-Müllerian hormone (AMH) levels compared to conventional vitrification. Conclusions MitoQ effectively mitigates vitrification-induced oxidative damage, maintains mitochondrial homeostasis, and preserves both follicular reserve and endocrine function. These findings suggest that MitoQ is a valuable adjunct in ovarian tissue cryopreservation and could significantly improve fertility preservation outcomes for cancer patients.

Abstract Extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue (EMZL) is an indolent B-cell lymphoma that can involve various anatomic sites. EMZL is derived from post-germinal center marginal zone B cells and typically lacks bcl-6 expression. Herein, we report two post-treatment cases of EMZL where unexpected bcl-6 protein expression was observed in specimens obtained following recurrence or progression. This contrasts with the primary specimens, which were negative for the bcl-6. Additionally, we confirm that the altered bcl6 expression observed in relapsed EMZL cases is independent of BCL6 gene rearrangement, as demonstrated by fluorescence in situ hybridization analysis. Relevant literature was reviewed and summarized to enhance the understanding of this phenomenon, particularly for pathologists.

As an important group of widespread organic substances in aquatic ecosystems, dissolved organic matter (DOM) plays an essential role in carbon recycling and transformation processes. The photochemical behavior of DOM is one of the main ways it participates in these processes, and it attracts extensive attention. However, due to a variety of sources and water conditions, including both freshwater and seawater environments, the photochemical properties of DOM exhibit great differences. Nowadays, a large number of studies have focused on the generation process of reactive species (RS) from sunlit DOM, while little effort has been made so far to provide a comprehensive summary of the photochemical behavior of DOM, especially in fresh and saline aquatic ecosystems. In this review, we analyzed the research hotspot on DOM photochemistry over the last 30 years, summarizing the generation of photoreactive species in natural water environments containing DOM (both freshwater and seawater) and listing the main factors affecting the rate, yield, and species of RS photoproduction. Compared with freshwater, seawater has unique characteristics such as high pH value, high ionic strength, and halide ions, which affect the photogeneration of RS, the photoconversion process, as well as the reaction pathways of various environmental substances. In general, DOM-induced surface water photochemistry has important impacts on the environmental transformation and toxic effects of aquatic pollutants and can even contribute significantly to the Earth's carbon cycle, which would have potential implications for both human and ecological health.

Abstract Methamphetamine (MA), as one kind of overflowed synthetic illicit drugs, has posed severe threats to health and social security. However, the on-site and visible fluorescence detection to MA remains limited. Herein, through covalently coupling diphenylacridine (DPA) and dimethylacridine (DMA) with pyridine, two ratiometric fluorescence probes (PyDPA and PyDMA) are constructed, which present rapid response, bathochromic-shifts over 100 nm and visible fluorescence color changes from blue to cyan upon the exposure to methylphenethylamine (MPEA, a simulant of MA). And the similar responses are observed for MA in confiscated samples. Further, a smartphone-based quantitative detected system is established to provide the on-site trace detection of MPEA as ppb level. Specially, PyDPA or PyDMA can identify MPEA from its interferences according to the unique ratiometric response based on their dual-emission-enhancement. Here, we show two ratiometric fluorescence probes to MA and MPEA with high potential for on-site application.

Abstract Background This study systematically reviews recent research comparing clinical outcomes and gait function changes in patients undergoing total knee arthroplasty (TKA) versus unicompartmental knee arthroplasty (UKA). Methods A systematic search of the Web of Science, PubMed, and Embase databases was conducted, covering publications from January 2013 to September 2024, to identify studies evaluating changes in clinical scores and gait parameters in patients undergoing TKA or UKA. Following stringent selection criteria, data were synthesized from studies involving 171 TKA and 148 UKA patients, focusing on reported gait outcomes and aggregating findings for comprehensive analysis. Direct comparisons between TKA and UKA were performed to assess differences in clinical scores and gait parameters, aiming to elucidate the relative efficacy of each surgical approach and provide robust evidence for clinical decision-making. Results Ten studies met the inclusion criteria for post-operative gait outcome comparisons between TKA and UKA, with seven studies also addressing clinical scores. One study reported greater improvement in WOMAC scores for the UKA group at 6 months post-operation (P 0.05). All ten studies assessed gait parameter recovery, with three studies showing no significant differences at 1 year (P > 0.05). However, seven studies identified superior gait recovery in the UKA group across various parameters, including walking speed, step and stride length, single support time, heel strike force, knee joint range of motion, knee flexion angles during different gait phases, peak knee adduction moment, peak tibial internal rotation moment, gait symmetry, and stride length symmetry (P

Abstract Segmentation of brain tissue from MR images provides detailed quantitative brain analysis for accurate diagnosis, detection, and classification of brain diseases, and plays an important role in neuroimaging research and clinical environments. Recently, a plethora of deep learning-based approaches have been employed to achieve brain tissue segmentation in fetuses, infants, and adults with impressive outcomes. However, owing to the existence of noise, motion artifacts, and edge blurriness in MR images, automatically segmenting brain tissue accurately from MR images is still a very challenging task. This survey examines both deep learning and MRI, providing an overview of the latest advances in fetal, infant, and adult brain tissue segmentation techniques based on deep learning. It includes the performance and quantitative analysis of the state-of-the-art methods. Over 100 scientific papers covering various technical aspects, including network architecture, prior knowledge, and attention mechanisms, were reviewed and analyzed. This article also comprehensively discusses these technologies and their potential applications in the future. Brain tissue segmentation provides detailed quantitative brain analysis for accurate diagnosis, detection, and classification of brain diseases, and plays an important role in neuroimaging research and clinical environments.

Abstract Objective The long‐term effectiveness of total hip arthroplasty (THA) largely depends on the accuracy of acetabular prosthesis placement. To improve the accuracy of acetabular prosthesis placement, we utilized a new surgical navigation system: visual treatment solution (VTS). The purpose of this study was to verify the efficacy and safety of this system in assisting THA. Methods This was a prospective, multicenter, randomized controlled trial. One hundred and twenty‐four patients undergoing primary THAs were included. The experimental group underwent VTS‐assisted THA, and the control group underwent traditional surgical techniques. The main efficacy evaluation indicators were the proportion of anteversion and inclination angles in the Lewinnek safe zone, and secondary evaluation indicators included operation time, Western Ontario and McMaster University Osteoarthritis index (WOMAC) score, Harris score, short‐form‐36 (SF‐36) score, and hip dislocation rate. Statistical analysis was performed mainly by t‐test and chi‐square test. Results The proportion of both anteversion and inclination angles in the safe zone was 93.1% in the experimental group and 50.9% in the control group; the difference was significant (p 0.05). The dislocation rate was 0% in the experimental group and 1.6% in the control group; the difference was not significant (p > 0.05). Conclusion VTS‐assisted THA can significantly improve the accuracy of acetabular prosthesis placement. However, there were no differences in short‐term clinical outcomes or dislocation rates between the two groups.

The exposure of ethanol increases the risk of head and neck inflammation and tumor progression. However, limited studies have investigated the composition and functionality of laryngeal microbiota under ethanol exposure. We established an ethanol-exposed mouse model to investigate the changes in composition and function of laryngeal microbiota using Metagenomic shotgun sequencing. In the middle and late stages of the experiment, the laryngeal microbiota of mice exposed to ethanol exhibited obvious distinguished from that of the control group on principal-coordinate analysis (PCoA) plots. Among the highly abundant species, Salmonella enterica and Mycobacterium marinum were likely to be most impacted. Our findings indicated that the exposure to ethanol significantly increased their abundance in larynxes in mice of the same age, which has been confirmed through FISH experiments. Among the species-related functions and genes, metabolism is most severely affected by ethanol. The difference was most obvious in the second month of the experiment, which may be alleviated later because the animal established tolerance. Notable enrichments concerning energy, amino acid, and carbohydrate metabolic pathways occurred during the second month under ethanol exposure. Finally, based on the correlation between species and functional variations, a network was established to investigate relationships among microbiota, functional pathways, and related genes affected by ethanol. Our data first demonstrated the continuous changes of abundance, function and their interrelationship of laryngeal microbiota under ethanol exposure by Metagenomic shotgun sequencing. Importance: Ethanol may participate in the inflammation and tumor progression by affecting the composition of the laryngeal microbiota. Here, we applied the metagenomic shotgun sequencing instead of 16 S rRNA sequencing method to identify the laryngeal microbiota under ethanol exposure. Salmonella enterica and Mycobacterium marinum are two dominant species that may play a role in the reconstruction of the laryngeal microenvironment, as their local abundance increases following exposure to ethanol. The metabolic function is most evidently impacted, and several potential metabolic pathways could be associated with alterations in microbiota composition. These findings could help us better understand the impact of prolonged ethanol exposure on the microbial composition and functionality in the larynx.

Imidazolium-based ionic liquids (ILs) have been regarded as green solvents owing to their unique properties. Among these, the melting point is key to their excellent performance in applications such as catalysis, biomass processing, and energy storage, where stability and operational temperature range are critical. The utilization of neural networks for forecasting the melting point is highly significant. Nevertheless, the excessive selection of descriptors obtained by density functional theory (DFT) calculations always leads to huge computational costs. Herein, this study strategically selected only 12 kinds of quantum chemical descriptors by employing a much more efficient semi-empirical method (PM7) to reduce computational costs. Four principles of data pre-processing were proposed, and the innovative use of a simulated annealing algorithm to search for the lowest energy molecular conformation improved accuracy. Based on these descriptors, a multi-layer perceptron neural network model was constructed to efficiently predict the melting points of 280 imidazolium-based ILs. The R2 value of the current model reached 0.75, and the mean absolute error reached 25.03 K, indicating that this study achieved high accuracy with very little computational cost. This study reveals a strong correlation between descriptors and melting points. Additionally, the model accurately predicts unknown melting points of imidazolium-based ILs, achieving good results efficiently.

Abstract The artificial engineering of an enzyme’s structural conformation and dynamic properties to promote its catalytic activity and stability outside cellular environments is highly pursued in industrial biotechnology. Here, we describe an elegant strategy of combining the rationally designed liquid-solid hybrid microreactor with a tailor-made polyethylene glycol functional ionic liquid (PEG-IL) microenvironment to exercise a high level of control over the configuration of enzymes for practical continuous-flow biocatalysis. As exemplified by a lipase driven kinetic resolution reaction, the obtained system exhibits a 2.70 to 30.35-fold activity enhancement compared to their batch or traditional IL-based counterparts. Also, our results demonstrate that the thermal stability of encapsulated lipase can be significantly strengthened in the presence of PEG groups, showcasing a long-term continuous-flow stability even up to 1000 h at evaluated temperature of 60 oC. Through systematic experiment and molecular dynamics simulation studies, the conformational changes of the active site cavity in the modified lipases are correlated with enzymatic properties alteration, and the pronounced effects of PEG-groups in stabilizing enzyme’s secondary structures by delaying unfolding at elevated temperatures are identified. We believe that this study will guide the design of high-performance enzymatic systems, promoting their utilization in real-world biocatalysis applications.

Concerns about the durability of transportation infrastructure due to freeze–thaw (F–T) cycles are particularly significant in the Chinese plateau region, where concrete aging and performance deterioration pose substantial challenges. The current national standards for the frost resistance design of concrete structures are based predominantly on the coldest monthly average temperature and do not adequately address the comprehensive effects of the spatiotemporal variance, amplitude, and frequency of F–T cycles. To address this issue, this study introduced a spatiotemporal distribution model to analyze the long-term impact of F–T action on concrete structures by employing statistical analysis and spatial interpolation techniques. Cluster analysis was applied to create a nationwide zonation of F–T action level from data on the freezing temperature, temperature difference, and the number of F–T cycles. Furthermore, this study explored the similarity between natural environmental conditions and laboratory-accelerated tests using hydraulic pressure and cumulative damage theories. A visualization platform that incorporates tools for meteorological data queries, environmental characteristic analyses, and F–T action similarity calculations was designed. This research lays theoretical groundwork and provides technical guidance for assessing service life and enhancing the quantitative durability design of concrete structures in the Chinese plateau region.

Susceptibility to pathogens in the elderly is heightened with age, largely because of immunosenescence. As an immune regulatory organ, bone marrow creates immune cells that move to other organs and tissues through the blood. Despite the significance of this process of this organ, there is limited research on changes in immune cell generation in the bone marrow and their effects on immunosenescence. In this study, the compositions of immune cells in bone marrow from young (three months) and old (24+ months) mice were compared by means of mass cytometry, with further validation obtained through the reanalysis of single-cell RNA sequencing data and cell sorting via flow cytometry. The effects of differential immune cells on immunosenescence in old mice were evaluated using the Clostridium difficile (C. difficile) infection model. Our results showed that aged mice presented with a reduction in bone trabeculae structure, which was accompanied by a notable increase in polymorphonuclear (PMN)-myeloid-derived suppressor cell (MDSC) abundance. Through bulk-seq and reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis, we identified differential genes associated with the immune response—specifically, the Th17 cell differentiation pathway. Furthermore, the increase in exported PMN-MDSCs to the large intestine resulted in increased gut permeability and inflammatory damage to the colon following C. difficile infection. After clearing the PMN-MDSCs in old mice using the anti-Gr-1 antibody, the symptoms induced by C. difficile were significantly relieved, as evidenced by an inhibited IL-17 pathway in the colon and reduced gut permeability. In conclusion, aging increases the number of PMN-MDSCs in both the generated bone marrow and the outputted intestine, which contributes to susceptibility to C. difficile infection. This study provides a novel target for anti-aging therapy for immunosenescence, which is beneficial for improving immune function in elders.

Abstract Background Recent advances in ultrasound technology have led to widespread adoption of ultrasonic energy devices in liver resections. While various studies have assessed the comparative advantages of ultrasonic devices and traditional clamp-crushing, their findings vary. Moreover, a specific systematic review on this topic has not yet been conducted. Objectives This study aims to present a comprehensive, up-to-date analysis comparing outcomes between ultrasonic devices and conventional clamp-crushing methods in liver resection, based on currently available literature. Patients and methods We conducted a systematic literature search in databases such as PubMed, Embase, Web of Science, and CNKI up to November 2023. Studies that compared the efficacy or safety of ultrasonic devices against traditional clamp-crushing methods in hepatectomy were included. The analysis covered intraoperative outcomes like operating time, blood loss, and transfusion rate, as well as postoperative outcomes such as complication rate, mortality, postoperative bleeding, and bile leakage. Review Manager version 5.3 (Cochrane Collaboration, Oxford, UK) and Stata 17.0 (Stata Corp, College Station, TX, USA) were used for data analysis. Results Thirteen studies, involving a total of 1,417 patients (630 using ultrasonic devices and 787 using clamp-crushing methods), were included. The clamp-crush method resulted in a shorter operation time. Contrarily, the ultrasonic device group experienced reduced blood loss and lower transfusion rates. Postoperatively, there was no significant difference in mortality or postoperative bleeding between the groups. However, the ultrasonic group had a lower overall complication rate, particularly a reduced incidence of bile leakage. Overall, the ultrasonic devices were associated with improved perioperative outcomes. Conclusions The findings suggest that ultrasonic devices provide better outcomes in hepatectomy compared to traditional clamp-crushing techniques. Nonetheless, large-scale randomized controlled trials are needed to confirm these results due to potential heterogeneity and biases. The choice of using ultrasonic devices should consider the surgeon’s experience and individual patient circumstances.

Abstract Background Bioactive peptides are important bioactive molecules composed of short-chain amino acids that play various crucial roles in the body, such as regulating physiological processes and promoting immune responses and antibacterial effects. Due to their significance, bioactive peptides have broad application potential in drug development, food science, and biotechnology. Among them, understanding their biological mechanisms will contribute to new ideas for drug discovery and disease treatment. Results This study employs generative adversarial capsule networks (CapsuleGAN), gated recurrent units (GRU), and convolutional neural networks (CNN) as base classifiers to achieve ensemble learning through voting methods, which not only obtains high-precision prediction results on the angiotensin-converting enzyme (ACE) inhibitory peptides dataset and the anticancer peptides (ACP) dataset but also demonstrates effective model performance. For this method, we first utilized the protein language model—evolutionary scale modeling (ESM-2)—to extract relevant features for the ACE inhibitory peptides and ACP datasets. Following feature extraction, we trained three deep learning models—CapsuleGAN, GRU, and CNN—while continuously adjusting the model parameters throughout the training process. Finally, during the voting stage, different weights were assigned to the models based on their prediction accuracy, allowing full utilization of the model's performance. Experimental results show that on the ACE inhibitory peptide dataset, the balanced accuracy is 0.926, the Matthews correlation coefficient (MCC) is 0.831, and the area under the curve is 0.966; on the ACP dataset, the accuracy (ACC) is 0.779, and the MCC is 0.558. The experimental results on both datasets are superior to existing methods, demonstrating the effectiveness of the experimental approach. Conclusion In this study, CapsuleGAN, GRU, and CNN were successfully employed as base classifiers to implement ensemble learning, which not only achieved good results in the prediction of two datasets but also surpassed existing methods. The ability to predict peptides with strong ACE inhibitory activity and ACPs more accurately and quickly is significant, and this work provides valuable insights for predicting other functional peptides. The source code and dataset for this experiment are publicly available at https://github.com/Zhou-Jianren/bioactive-peptides .

Abstract Background This study aims to explore the accuracy of Convolutional Neural Network (CNN) models in predicting malignancy in Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging (DCE-BMRI). Methods A total of 273 benign lesions (benign group) and 274 malignant lesions (malignant group) were collected and randomly divided into a training set (246 benign and 245 malignant lesions) and a testing set (28 benign and 28 malignant lesions) in a 9:1 ratio. An additional 53 lesions from 53 patients were designated as the validation set. Five models—VGG16, VGG19, DenseNet201, ResNet50, and MobileNetV2—were evaluated. Model performance was assessed using accuracy (Ac) in the training and testing sets, and precision (Pr), recall (Rc), F1 score (F1), and area under the receiver operating characteristic curve (AUC) in the validation set. Results The accuracy of VGG19 on the test set (0.96) is higher than that of VGG16 (0.91), DenseNet201 (0.91), ResNet50 (0.67), and MobileNetV2 (0.88). For the validation set, VGG19 achieved higher performance metrics (Pr 0.75, Rc 0.76, F1 0.73, AUC 0.76) compared to the other models, specifically VGG16 (Pr 0.73, Rc 0.75, F1 0.70, AUC 0.73), DenseNet201 (Pr 0.71, Rc 0.74, F1 0.69, AUC 0.71), ResNet50 (Pr 0.65, Rc 0.68, F1 0.60, AUC 0.65), and MobileNetV2 (Pr 0.73, Rc 0.75, F1 0.71, AUC 0.73). S4 model achieved higher performance metrics (Pr 0.89, Rc 0.88, F1 0.87, AUC 0.89) compared to the other four fine-tuned models, specifically S1 (Pr 0.75, Rc 0.76, F1 0.74, AUC 0.75), S2 (Pr 0.77, Rc 0.79, F1 0.75, AUC 0.77), S3 (Pr 0.76, Rc 0.76, F1 0.73, AUC 0.75), and S5 (Pr 0.77, Rc 0.79, F1 0.75, AUC 0.77). Additionally, S4 model showed the lowest loss value in the testing set. Notably, the AUC of S4 for BI-RADS 3 was 0.90 and for BI-RADS 4 was 0.86, both significantly higher than the 0.65 AUC for BI-RADS 5. Conclusions The S4 model we propose has demonstrated superior performance in predicting the likelihood of malignancy in DCE-BMRI, making it a promising candidate for clinical application in patients with breast diseases. However, further validation is essential, highlighting the need for additional data to confirm its efficacy.

Objective A robotic system was recently introduced to improve prosthetic alignment during total knee arthroplasty (TKA). The purpose of this multicenter, prospective, randomized controlled trial (RCT) was to determine whether robotic‐arm‐assisted TKA improves clinical and radiological outcomes when compared to conventional TKA. Methods One hundred and thirty patients who underwent primary TKA were enrolled in this prospective, randomized controlled trial, which was conducted at three hospitals. Five patients were lost to follow‐up 6 weeks after surgery. Therefore, 125 participants (63 in the intervention group and 62 in the control group) remained in the final analysis. The primary outcome was the rate at which the mechanical axis of the femur deviated by less than 3° from the mechanical axis of the tibia. This was evaluated by full‐length weight‐bearing X‐rays of the lower limb 6 weeks postoperatively. Secondary outcomes included operation times, 6‐week postoperative functional outcomes evaluated by the American Knee Society score (KSS) and the Western Ontario and McMaster Universities osteoarthritis index (WOMAC), short form‐36 (SF‐36) health survey results, and the occurrence of adverse events (AEs) and serious adverse events (SAEs). Results At 6 weeks postoperatively, we found that the rate of radiographic inliers was significantly higher in the intervention group (78.7% vs 51.6%; p = 0.00; 95% confidence interval, 10.9% to 43.2%). The operation was significantly longer in the intervention group than in the control group (119.5 vs 85.0 min; p = 0.00). There were no significant differences in the 6‐week postoperative functional outcomes, SF‐36, AEs, and SAEs between the two groups. There were no AEs or SAEs that were determined to be “positively related” to the robotic system. Conclusion Robotic‐arm‐assisted TKA is safe and effective, as demonstrated in this trial.

Abstract Objective To investigate the sonographic characteristics of thyroid nodules with a halo, explore the value of contrast-enhanced ultrasound (CEUS) combined with fine needle aspiration (FNA) in identifying nodules with a halo, and predict the risk of metastasis by analyzing the pathological features of the halo. Methods A retrospective analysis was conducted on 185 postoperative cases of thyroid nodules accompanied by halos between January 2019 and December 2022. After describing the ultrasound characteristics of the thyroid nodules and their halos, all patients were divided into three groups, the first group (group I = CEUS only) of patients underwent CEUS, the second group (group II = CEUS + FNA) underwent FNA based on the first group, and the third group (group III = FNA only) underwent FNA directly. The CEUS and FNA results were graded using the Chinese Thyroid Imaging Report and Data System (C-TIRADS) and Bethesda Reporting System for Thyroid Cytopathology, respectively. Those graded below C-TIRADS 4b or Bethesda IV were defined as benign, and the results of FNA were referenced when the two methods were combined. The surgical pathology results were used as the gold standard. We plotted working curves to compare the diagnostic efficacy of CEUS and FNA alone and in combination in the diagnosis of thyroid nodules with halos. The pathological features of the halo were analyzed and the number of patients with cervical lymph node metastases was recorded. Results One hundred and sixty patients met the requirements. Benign nodules were mainly characterized by a thin (0.75 ± 0.31 mm) and uniform halo with good integrity, while malignant nodules had a thicker (1.48 ± 0.51 mm) halo with uneven and irregular margins (P

Abstract Background To investigate the efficiency of a new method for the prevention of argentinian flag sign during the process of continuous, circular, and centered anterior capsulotomy (CCC) on the anterior capsule in cortically liquefied intumescent cataracts. This study was registered in an appropriate registry and the registration number of registration was xyy11[2022]-XJSFX-087; The date of of registration was 2022-04-29. Methods Preoperative examinations including slit-lamp examination, ocular A-scan ultrasonography, and Ultrasound Biomicroscopy (UBM) UBM were conducted on 61 patients with intumescent cataracts. Cases with cortically liquefied intumescent cataracts were selected and after staining with indocyanine green, the anterior chamber air bubble technique was used to compress the anterior capsule, and liquefied cortex was aspirated using a puncture needle. Corrected Distance Visual Acuity (CDVA) and intraocular pressure were recorded on postoperative days 1, 1 week, 1 month, and 6 months. Intraoperative and postoperative complications were documented and analyzed. Results Fifty eyes were identified as having cortically liquefied intumescent cataracts. No cases of the Argentinian flag sign occurred, and standard capsulorrhexis was achieved, facilitating smooth phacoemulsification. All patients achieved satisfactory outcomes at follow-ups of 1 day, 1 week, 1 month, and 6 months postoperatively. Mild corneal edema was observed in three cases on the first postoperative day, with no other complications noted. Conclusions The anterior chamber air bubble technique combined with cortical fluid release technique can prevent the occurrence of the Argentinian flag sign in cortically liquefied intumescent cataracts, this method is simple, convenient and economic for the clinical promotion.

Abstract Microfine mineral particles have a small size, light weight, and low inertia, making it difficult for them to deviate from streamlines and collide with bubbles. Conventional flotation operations consume a large amount of reagents and exhibit poor flotation indicators. This study employs computational fluid dynamics (CFD) simulation and hydrodynamic testing to investigate the flow field within a high-turbulence microfine particle flotation machine equipped with a multilayer impeller–stator configuration, and validates the practical application performance of the microfine particle flotation machine through single-batch flotation experiments. Result shows that the impeller region of the traditional mechanical stirring flotation machine has a turbulent energy dissipation rate of 20 m²/s³, whereas that for the microfine particle flotation machine averages over 120 m²/s³. In the flotation verification, the cumulative recovery rate of the fine particle flotation machine is increased by 28% compared with that of the traditional KYF flotation machine. The flotation rate is also 1.3 times that of the KYF, demonstrating stronger selectivity for fine particle concentrates. It has certain guiding significance for the resource utilization of fine particle minerals.

Abstract Background The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus’s high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential. Methods We analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits. Results Our analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10−9 within the 24 HASV traits, located across 93 chromosomal regions. Notably, the regions 12q14.3, 17q21.31, 12q24.22, 6q21, 9q33.1, 6q25.1, and 2q24.2 were found to influence multiple HASVs. Gene set analysis revealed enrichment of neural differentiation and signaling pathways, as well as protein binding and degradation. Of 240 HASV-neuropsychiatric trait pairs, 75 demonstrated significant genetic correlations (P

The Three Gorges ground-based remote sensing vertical observation system, as the first pilot project of the "short board repair project" by the China Meteorological Administration, can monitor the fine structure and evolution of the atmospheric vertical profile in the Three Gorges Reservoir Region. The atmospheric temperature and humidity profiles are retrieved from the microwave radiometer in the Three Gorges ground-based remote sensing vertical observation system. Evaluating their retrieval bias and improving their accuracy is of great significance for precision monitoring of the vertical observation system in the Three Gorges Reservoir Region. By using microwave radiometer data, radiosonde data, automatic weather station data, and millimeter wave cloud gauge data of Three Gorges from November 2022 to June 2023, this study evaluates the bias of temperature and humidity at 83 height layers retrieved from microwave radiometer under sunny, cloudy, and rainy days. Then a linear regression correction method based on radiosonde data after the regrouping of the 83 height layers for temperature and humidity profile of the microwave radiometer was proposed. Finally, the applicability of the correction method by using the accuracy changes before and after the correction was evaluated using the observation from a rainy and snowy weather process. The results are as follows: (1) The temperature of the microwave radiometer has good consistency with radiosonde temperature under three weather conditions, and the bias of most height layers is less than 2 ℃. (2) On sunny days, the humidity of the microwave radiometer is higher than that of the radiosonde at all height layers. Above 6 km, the root mean square error (RMSE) of the humidity can reach 30% on cloudy and rainy days. (3) The correction method established after the regrouping of the 83 height layers can improve the temperature and humidity profile accuracy of the microwave radiometer. (4) The corrected temperature and humidity profiles of the microwave radiometer are closer to the reality in the case of a rain and snow event.

Abstract Background Hepatic venous pressure gradient (HVPG) is considered the gold standard for diagnosing portal hypertension (PHT). Laparoscopic splenectomy plus esophagogastric devascularization (LSED) is an important surgery for treating PHT. However, the variation trend of HVPG after surgery is not clear. Moreover, whether HVPG can provide precise prognostic information for patients undergoing surgery remains to be further studied. This study aimed to investigate the independent prognostic value of HVPG in LSED. Methods From January 2016 to March 2023, 135 patients with PHT underwent LSED at our hospital were retrospectively evaluated. We analyzed the correlations between clinical indicators and history of upper gastrointestinal bleeding (UGIB). Among them, 57 patients remeasured postoperative HVPG. We further investigated the postoperative alterations of HVPG and correlative factors, as well as the relationship between the HVPG and postoperative UGIB. Results In this study, we found that 94 patients with preoperative UGIB (16.27 ± 5.73 mmHg) had a higher baseline HVPG than the other 41 patients without (14.02 ± 5.90 mmHg) (p = 0.04). The mean postoperative HVPG significantly decreased (-3.57 ± 8.09 mmHg, p = 0.001) compared to the baseline, and 66% of patients (38/57) experienced a decreased HVPG-response after surgery. The baseline HVPG and preoperative CTP class B were associated with the decreased HVPG-response (p20% from baseline exhibited better recurrent hemorrhage-free survival rates than those without (log-rank, p = 0.013). Conclusion We found that LSED led to a significantly decreased HVPG, and patients with postoperative HVPG decreased >20% obtained better UGIB-free survival benefits than those without.

Abstract This paper aims to propose a faster and more accurate network for human spatiotemporal action localization tasks. Like the YOWO model, we also use convolutional neural networks (CNNs) for feature extraction, but our model differs from YOWO in three significant ways: firstly, we don’t use the feature fusion strategy, we only use spatial features extracted by 2D CNNs for action localization and spatiotemporal features extracted by 3D CNNs for action recognition; secondly, we make an improvement to the 2D CNNs network by introducing a coordinate attention mechanism and utilize the CIoU loss instead of the coordinate offset loss for bounding box regression; thirdly, we provide a more lightweight and faster spatiotemporal action localization architecture, which reduces the number of parameters by 21.76 million and achieves a speed of 39 fps on 16-frame input clips compared to the YOWO model. We test our model’s performance on three public datasets: UCF-Sports, JHMDB-21 and UCF101-24. Compared with the YOWO model, we improve frame-mAP (@IoU 0.5) by 17.09% and 7.15% on the UCF-Sports and JHMDB-21 datasets, and for video-mAP, we improve by 2.7%, 8.7% and 14.4% at IoU thresholds of 0.2, 0.5 and 0.75 on the JHMDB-21 dataset.

Abstract Background The gut microbiota is a key regulator of bone metabolism. Investigating the relationship between the gut microbiota and bone remodeling has revealed new avenues for the treatment of bone-related disorders. Despite significant progress in understanding gut microbiota-bone interactions in mammals, research on avian species remains limited. Birds have unique bone anatomy and physiology to support egg-laying. However, whether and how the gut microbiota affects bone physiology in birds is still unknown. In this study, we utilized laying hens as a research model to analyze bone development patterns, elucidate the relationships between bone and the gut microbiota, and mine probiotics with osteomodulatory effects. Results Aging led to a continuous increase in bone mineral density in the femur of laying hens. The continuous deposition of medullary bone in the bone marrow cavity of aged laying hens led to significant trabecular bone loss and weakened bone metabolism. The cecal microbial composition significantly shifted before and after sexual maturity, with some genera within the class Clostridia potentially linked to postnatal bone development in laying hens. Four bacterial strains associated with bone development, namely Blautia coccoides CML164, Fournierella sp002159185 CML151, Anaerostipes caccae CML199 (ANA), and Romboutsia lituseburensis CML137, were identified and assessed in chicks with low bacterial loads and chicken primary osteoblasts. Among these, ANA demonstrated the most significant promotion of bone formation both in vivo and in vitro, primarily attributed to butyrate in its fermentation products. A long-term feeding experiment of up to 72 weeks confirmed that ANA enhanced bone development during sexual maturity by improving the immune microenvironment of the bone marrow in laying hens. Dietary supplementation of ANA for 50 weeks prevented excessive medullary bone deposition and mitigated aging-induced trabecular bone loss. Conclusions These findings highlight the beneficial effects of ANA on bone physiology, offering new perspectives for microbial-based interventions for bone-related disorders in both poultry and possibly extending to human health. Video Abstract Graphical Abstract

Abstract We explore the generalized holographic complexity of odd-dimensional Myers-Perry asymptotically Anti-de Sitter (MP-AdS) black holes with equal angular momenta within the “complexity equals anything” proposal. We begin by determining the codimension-one generalized volume complexity by finding the extremum of the generally covariant volume functional. Locally, we show that its late-time growth rate aligns with the critical momenta associated with the extremal hypersurfaces. Globally, we discover diverse phase transitions for the complexity at early times, including first-order, second-order, and multicritical transitions. An area law and a phase diagram are proposed to adapt to these phase behaviours, highlighting the effects of the black hole’s angular momentum. At zero time, we define the generalized holographic complexity of formation and examine its scaling relations for both large near-extremal MP-AdS black holes and static charged black holes. We find that the scaling behaviours of the generalized volume complexity of formation maintain uniformity with those of the original holographic complexity formulations, except in cases where the scalar functional defining the generalized holographic complexity is infinite in the vacuum limit or at spatial infinity. Additionally, we show that these findings can be applied to codimension-zero observables.

Abstract Background The curriculum system is a central component in achieving the goals and specifications of talent training schemes. However, problems and difficulties exist in curriculum provision due to a lack of curriculum system design logic. This study aimed to investigate the correlation between the university curriculum system and graduate quality and to reveal the design logic of the curriculum system. Methods A total of 699 stomatology graduates from a university in Zhejiang were selected as research subjects from 2015 to 2022. The students’ curriculum system and graduate quality data were collected and classified. The graduate quality information contained (1) the National Board Dental Examination (NBDE) pass rate and score, (2) the postgraduate entrance rate and destination, and (3) the employment rate and work institution. Regression analysis was also conducted to assess the correlation between the curriculum system and graduate quality. Results Regression analysis revealed significant associations between general education, specialization, and stomatology X courses and NBDE score, postgraduate entrance rate and destination, and work institution. All courses except public elective courses had significant impacts on NBDE score. General basic, medical English, and employment guidance courses significantly influenced the postgraduate entrance rate and destination. Restricted elective and public elective courses had significant effects on employment rate and work institution. Conclusions Increasing the quality of specialized and stomatology X courses in the curriculum system is beneficial for deepening graduates’ expertise and enhancing their education. Moreover, English courses are suggested to be offered in the early stage to lay a better language foundation.

Abstract Objectives To identify risk factors correlated with atrioventricular block (AVB) in the general population. Methods Participants in the Atherosclerosis Risk in Communities study (ARIC) and the Cardiovascular Health study (CHS) were enrolled. The presence of AVB was confirmed at an electrocardiogram (ECG) reading center using Minnesota ECG Classification. Cox proportional hazards models were performed to investigate potential risk factors of AVB, after adjustment for age, sex, race and traditional cardiovascular risk factors. Results During the 17 years of follow-up, a total of 731 high-degree AVB cases were identified. Age and sex-standardized rate of AVB was 2.79 and 2.35 per 1000 person-years in the white and the black population, respectively. With the increase of the geriatric population, the incidence of high-degree AVB will increase from 378,816 in 2020 to 535,076 in 2060, and most increment would occur among the elderly. Older age, male sex, the white race, overweight, comorbidities, declined forced vital capacity (FVC), elevated inflammation biomarkers, left bundle branch block and bifascicular block were independently associated with the incidence of high-degree AVB. Conclusion To conclude, older age, male sex, white population, overweight, combined diabetes or chronic kidney disease, impaired FVC, elevated inflammation biomarkers, left bundle branch block and bifascicular block were independent predictors for high-degree AVB. The next 40 years would witness a dramatic increase in the incidence of high-degree AVB.

Abstract Background CXC chemokine CXCL12 is involved in the pathological development of rheumatoid arthritis (RA) through abnormal migration of peripheral immune cells in the joint. Although low dose methotrexate (MTX) is clinically used to treat RA patients, CXCL12 signaling responses to MTX-mediated treatments is still not well understood. Methods In this study, we examined the expression of CXCR4 (cognatic receptor for CXCL12) in peripheral T cells from RA patients and arthritis mice models received from low dose MTX therapies. The effects of low dose MTX on CXCR4 were further determined via both in vitro CD3+ T cells and Cxcr4 conditional knockout (CKO) arthritis mice models. Results Our clinical data shows that low dose MTX treatment was clinically associated with down-regulated expression of chemokine receptor CXCR4 on patient peripheral T cells. In vitro, low dose MTX significantly decreased cell transmigration through down-regulated CXCR4’s expression in CD3+ T cells. Consistently, CD3+ T cells treated with low dose MTX demonstrated an increased genomic hypermethylation across the promoter region of Cxcr4 gene. Furthermore, our preclinical studies showed that low dose MTX-mediated downregulation of CXCR4 significantly improved the pathological development in mouse arthritis models. Conditional disruption of the Cxcr4 gene in peripheral immune cells potentially alleviated inflammation of joints and lung tissue in the arthritis mice, though genetic modification itself overall did not change their clinical scores of arthritis, except for a significant improvement on day 45 in CXCR4 CKO arthritis mice models during the recovery phase. Conclusion Our findings suggest that the effect of low dose MTX treatment could serve to eliminate inflammation in RA patients through impairment of immune cell transmigration mediated by CXCR4.

ObjectiveTo analyze the whole-genome characteristics of four coxsackievirus B5 (CVB5) strains isolated in Yunnan province, China in 2022. MethodsPrimers were designed to amplify and sequence the whole genome of CVB5 isolates. The whole genome was amplified in segments, and sequenced using the "primer walking" method. Sequence splicing and assembly were performed. Genetic characteristics of the CVB5 strains were analyzed using software such as MEGA 7.0, Simplot 3.5.1, and DNAStar 7.1. ResultsBased on VP1 and whole-genome phylogenetic analysis, all four CVB5 isolates belonged to genotype C. Compared with the prototype strain, multiple amino acid mutations occurred in the VP1 region of the four strains. Phylogenetic analysis of P1, P2, and P3 regions and Simplot recombination analysis showed that the CVB5 isolates in this study may have undergone recombination with multiple enterovirus B strains. ConclusionThe four CVB5 strains isolated from clinical samples of hand, foot and mouth disease (HFMD) patients in Kunming, Yunnan province in 2022 all belonged to genotype C.

Background: Fatigue is often accompanied by comorbid sleep disturbance and psychiatric distress following the COVID-19 infection. However, identifying individuals at risk for developing post-COVID fatigue remains challenging. This study aimed to identify the neurobiological markers underlying fatigue susceptibility and further investigate their effect on COVID-19-related neuropsychiatric symptoms. Methods: Individuals following a mild SARS-CoV-2 infection (COV+) underwent neuropsychiatric measurements (n = 335) and MRI scans (n = 271) within 1 month (baseline), and 191 (70.5 %) of the individuals were followed up 3 months after infection. Sixty-seven healthy controls (COV−) completed the same recruitment protocol. Results: Whole-brain voxel-wise analysis showed that gray matter volume (GMV) during the acute phase did not differ between the COV+ and COV− groups. GMV in the right dorsolateral prefrontal cortex (DLPFC) and left dorsal anterior cingulate cortex (dACC) were associated with fatigue severity only in the COV+ group at baseline, which were assigned to the frontal system and limbic system, respectively. Furthermore, fatigue mediated the associations between volume differences in fatigue susceptibility and COVID-related sleep, post-traumatic stress disorder, anxiety and depression. Crucially, the initial GMV in the right DLPFC can predict fatigue symptoms 3 months after infection. Conclusions: We provide novel evidence on the neuroanatomical basis of fatigue vulnerability and emphasize that acute fatigue is an important link between early GMV in the frontal-limbic regions and comorbid neuropsychiatric symptoms at baseline and 3 months after infection. Our findings highlight the role of the frontal-limbic system in predisposing individuals to develop post-COVID fatigue.

Underwater hyperspectral target detection (HTD) technology holds pivotal value in enhancing maritime military power. However, the absorption and scattering properties of the water bodies result in the inevitable issue of mixed pixels in underwater hyperspectral images (HSIs). To address the issue, a joint hyperspectral unmixing and target detection network for underwater HSI is proposed, denoted as HUTDNet, which utilizes the material type and abundance information for downstream semantic tasks. Specifically, a nonlinear underwater unmixing network is designed to extract pure underwater endmembers and their associated abundance information, which is essential in assisting the subsequent target detection task. The network also extracts underwater virtual endmembers and their abundance values to reconstruct a more realistic underwater HSI. Then, the abundance weighting module determines the abundance weighting factor by calculating the spectral distance between a priori target spectra and the estimated underwater pure endmembers, generating a weighted abundance map. Finally, due to the inherent limitations in the characterization capabilities of abundance maps and endmembers, the detection network extracts key spectral feature maps from the input underwater HSI. These feature maps serve as complementary terms, fused with the original and weighted abundance maps. Subsequently, convolutional and fully connected layers are employed to extract deeper features and generate the target detection maps. Experiments on both real and synthetic datasets demonstrate the superior performance and efficiency of the proposed method in this paper compared to other state-of-the-art methods.

The conduction delay time is one of the main technical parameters of the surface flashover triggered vacuum switch (STVS). Detailed research and optimization of conduction delay time characteristics are necessary for the development of high-performance STVS. In this paper, the conduction performance of STVS with different electrode structures and operating parameters is investigated in detail. Based on the analysis of the conduction process, the factors affecting the STVS conduction delay time are discussed. The experimental platform is built by using a detachable vacuum chamber, and the conduction delay time characteristics of STVS are compared under different electrode structures and operating parameters. This research analyzes and discusses the reasons for the influence of electrode structures and operating parameters on conduction delay time. The experimental results show that the structure with the trigger gap flashover surface parallel to the cathode surface has a better conduction delay time than the structure with both perpendicular to each other. Both reducing the trigger electrode embedment depth and extending the trigger gap flashover surface length can optimize the conduction delay time of STVS. However, increasing the trigger gap flashover surface length only reduces the conduction delay time at the initial stage of STVS operation. The shorter the main gap distance, the smaller the conduction delay time of the STVS. In addition, increasing the trigger current and operating voltage can diminish the conduction delay time of STVS.