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Abstract Despite the abundant production of fruits and vegetables in Xinjiang, there is an increasing trend in waste rates. Gas-controlled packaging techniques are employed post-harvest to enhance freshness and extend shelf life. However, the multi-gas mixing system at the core of this equipment often encounters challenges such as insufficient stability, limited precision, high costs, and inadequate intelligence. In this context, we have developed and designed a multi-gas mixing system for gas-conditioned packaging. The system integrates Internet of Things technology, uses a programmable controller as the core, proposes a ternary gas distribution model based on the ideal gas equation and Dalton’s law of partial pressures, and utilizes RS-485 bus, TCP/IP protocol, among others. This ensures communication between the equipment and data transmission with the cloud server while enabling remote control of the gas mixing and blending process via a mobile phone terminal. The system runs stably through testing, with the average relative deviations of CO2 and O2 gas concentrations being 0.86% and 0.72%, respectively. This fulfills the technical prerequisites for achieving a gas concentration precision of less than 1%, addressing challenges related to inadequate precision in gas blending, unstable performance, and limited visual representation. Moreover, it significantly reduces equipment costs and operational complexities while serving as a valuable reference for advancing multivariate gas mixing and blending technology in Xinjiang’s fruit and vegetable gas-conditioned packaging.

Abstract Black women face the highest mortality-to-incidence ratio from high grade serous ovarian cancer (HGSOC). This study investigated biological differences in HGSOC tumors from Black vs. White women. HGSOC from 35 Black and 31 White patients were analyzed by Infinium Methyation-EPIC array and RNA sequencing. 191 CpG sites were differentially methylated (FDR 10%) and 277 genes were differentially expressed (FDR

Abstract Cuproptosis is an emerging mode of programmed cell death for tumor suppression but sometimes gets resisted by tumor cells resist under specific mechanisms. Inhibiting copper transporter ATPase (ATP7A) was found to disrupt copper ion homeostasis, thereby enhancing the effect of cuproptosis and eventually inhibiting tumor invasion and metastasis. In this study, we develop a multifunctional nanoplatfrom based on Cu9S8 (CAPSH), designed to enhance cuproptosis in tumor cells by specifically targeting ATP7A interference, while combining thermodynamic therapy with immune effects. The release of copper ions from CAPSH and the copper homeostasis interference by siRNA cooperatively increases the concentration of copper ions in tumor cells, which induces effectively cuproptosis and activates immune responses for suppressing development and metastasis of tumor. This nanoplatform simultaneously regulates cuproptosis from both principles of onset and development, facilitating the application of cuproptosis in tumor therapy.

Abstract The Neoproterozoic oxygenation event is a milestone in Earth’s history, yet the redox structure and elemental cycling of the Neoproterozoic ocean remain debated. Here, we investigated iron speciation, molybdenum, and nitrogen isotopes in black shales and manganese carbonates from the upper Ediacaran Doushantuo Formation, South China, to examine the links between redox state, manganese mineralization, and molybdenum cycling. In both lithologies, high pyritic iron ratios (> 0.8) indicate a localized euxinic zone, while estimated seawater molybdenum (1.9‰) and sediment nitrogen isotopic compositions (4.19 ± 1.96‰) resemble modern values, suggesting oxygenated surface waters over euxinic depths. Negative molybdenum isotope in manganese(II) carbonates points to manganese(IV) oxide reduction, acting as a molybdenum shuttle from oxygenated surface to euxinic deep waters. Periodic euxinic contractions drove manganese(II) oxidation and mineralization, shaping molybdenum cycling. This study highlights essential manganese(II) oxidation for manganese carbonate mineralization and offers new insights into molybdenum geochemistry and ancient ocean oxygenation events.

Abstract Understanding Pd effects on NOx storage and release is crucial for designing passive NOx adsorber (PNA) to control NOx emissions during diesel cold-starts. Herein, we report two oxidation states of Pd species on CexZr1-xO2 regulated by metal-support interaction. Pdδ+ (0

Abstract Borayflo Haemostatic matrix is a new absorbable hemostatic gelatin matrix which can be used for intraoperative assisted hemostasis. In a prospective, multicenter, non-inferiority, randomized controlled trial, a total of 354 subjects were recruited from the departments of hepatobiliary surgery, obstetrics and gynaecology and orthopaedics of 4 hospitals and randomly allocated to test group (Borayflo Haemostatic matrix) or control group (Surgiflo Haemostatic matrix) in a 1:1 ratio. In the modified intention-to-treat population, 163 (93.14%) of 175 subjects in the test group versus 167 (94.89%) of 176 subjects in the control group successfully achieved hemostasis within 5 min (P > 0.05). Non-inferiority for effective rates of hemostasis at 5 min to Surgiflo Haemostatic matrix was shown in the study (treatment difference: -1.74% [95%CI, -6.70–3.22%] for modified intention-to-treat population). In terms of efficacy and safety, the new hemostatic gelatin matrix (Borayflo Haemostatic matrix) is equivalent to Surgiflo Haemostatic matrix. There was no significant difference in the incidence of AEs or SAEs between the test and control groups(P > 0.05). In addition, Borayflo Haemostatic matrix is a domestically produced haemostatic gelatin product, an advantage that will reduce the cost of surgical haemostasis for Chinese patients.

Abstract The mechanical deformation of coals occurring extensively during the geological period (tectonically deformed coals) can directly alter their pore structures and then the storage of coalbed methane. This study in-situ investigated the effects of different mechanical deformations on the ultramicropore structure and the methane adsorption of coal molecules using molecular simulations. The results show that the shear deformation (

Abstract The relative risk and benefits of Laparoscopic liver resection (LLR) are still controversial. This study aimed to evaluate perioperative and survival outcomes for three primary malignant liver tumors related outcomes following LLR. Data from three Homogeneous-High-Volume-Expert-Centers were collected. Multivariable logistic regression analysis was performed for the association between LLR, and major complications defined as Clavien-Dindo Classification grade ≥ II. Multivariable Cox proportional hazards regression was used to explore the impact of LLR on primary malignant liver tumor survival. Overall, 5886 patients underwent liver resection, of which 1991 underwent LLR. After adjusting for covariables, LLR had significantly lower rate of CDC grade ≥ II (OR = 0.56, 95% CI: 0.48–0.67, P 0.05). LLR was associated with lower rate of major complications, especially in women, non-drinkers, those without a history of abdominal surgery, and those with normal platelet. For primary malignant liver tumors, the survival outcomes did not differ significantly between LLR and OLR.

Abstract With the aging process of the global population and the development of medical technology, the cases of postoperative cognitive dysfunction (POCD) are also increasing. Due to the complexity of the pathogenesis, urgent treatment has been sought. Neuroinflammation induced by the accumulation of lipid droplets (LDs) in microglia has been closely watched in recent years and is also considered to be an important cause of nerve damage. Our study found that derived from Withania somnifera, Withaferin A (WA) could reduce the accumulation of LDs in the hippocampus of POCD mice, inhibit the expression of inflammatory factor interleukin-1β (IL-1β), and improve the cognitive ability of mice. Further in vitro experimental studies showed that WA increased the autophagy level of microglia, promoted the degradation of LDs, and reduced the production of inflammatory factors. In this regard, our comprehensive research endeavor holds the potential to furnish novel insights into therapeutic strategies aimed at addressing POCD and its associated neural impairments.

Abstract This study investigated the role of mitochondrial dynamics in postoperative cognitive dysfunction (POCD) and assessed the therapeutic potential of mitochondrial modulation, particularly through the inhibition of dynamin-related protein 1 (DRP1) with Mdivi-1. Our findings indicated that DRP1 inhibition substantially mitigated neuroinflammation mediated by microglial cells, contributing to improved cognitive function in POCD models. The administration of Mdivi-1 led to a notable decrease in mitochondrial fission, reduced reactive oxygen species (ROS) production, and stabilization of mitochondrial membrane potential, all of which correlate with diminished neuroinflammation, as evidenced by lower NOD-like receptor family pyrin domain containing 3 (NLRP3)/ interleukin-1β (IL-1β) expression in microglial cells. Importantly, Mdivi-1 treatment was also found to enhance synaptic plasticity, increasing synaptic spine density in the hippocampal region of POCD mice. This improvement in mitochondrial health and synaptic integrity was paralleled by enhanced cognitive performance, as demonstrated in Y-maze tests. These results underscored the critical role of mitochondrial dynamics in the pathophysiology of POCD and suggested that targeting mitochondrial dysfunction, specifically through DRP1 inhibition, could be an effective approach for POCD treatment.

Abstract As a transdermal drug delivery method, microneedles offer minimal invasiveness, painlessness, and precise in-situ treatment. However, current microneedles rely on passive diffusion, leading to uncontrollable drug penetration. To overcome this, we developed a pneumatic microneedle patch that uses live Enterobacter aerogenes as microengines to actively control drug delivery. These microbes generate gas, driving drugs into deeper tissues, with adjustable glucose concentration allowing precise control over the process. Our results showed that this microorganism-powered system increases drug delivery depth by over 200%, reaching up to 1000 μm below the skin. In a psoriasis animal model, the technology effectively delivered calcitriol into subcutaneous tissues, offering rapid symptom relief. This innovation addresses the limitations of conventional microneedles, enhancing drug efficiency, transdermal permeability, and introducing a creative paradigm for on-demand controlled drug delivery.

Abstract Type 1 diabetes (T1D) is a chronic autoimmune condition characterized by hyperglycemia resulting from the destruction of insulin-producing β-cells that is traditionally deemed irreversible, but partial remission (PR) with temporary reversal of hyperglycemia is sometimes observed. Here we use single-cell RNA sequencing to delineate the immune cell landscape across patients in different T1D stages. Together with cohort validation and functional assays, we observe dynamic changes in TIGIT+CCR7− Tregs and CD226+CCR7−CD8+ cytotoxic T cells during the peri-remission phase. Machine learning algorithms further identify TIGIT+CCR7− Tregs and CD226+CD8+ T cells as biomarkers for β-cell function decline in a predictive model, while cell communication analysis and in vitro assays suggest that TIGIT+CCR7− Tregs may inhibit CD226+CCR7−CD8+ T cells via TGF-β signaling. Lastly, in both cyclophosphamide-induced and streptozotocin (STZ)-induced mouse diabetes models, CD226 inhibition postpones insulitis onset and reduces hyperglycemia severity. Our results thus identify two interrelated immune cell subsets that may serve as biomarkers for monitoring disease progression and targets for therapeutic intervention of T1D.

Abstract The deterioration and deformation of brittle rock generally appear in railway tunnels with the operation of large buried deep tunnel. To investigate the macro-micro fracture and acoustic emission evolution characteristics of brittle rock, this paper conducted the uniaxial compression, scanning electron microscope (SEM), and acoustic emission (AE) signal monitoring under different loading rates. The results showed that the loading rate has an obvious enhancement effect on mechanical parameters. The increased loading rate extends the elastic deformation and improves the bearing strength, elastic modulus and deformation modulus. The fracture patterns include shear fracture, composite fracture, and tension fracture. The oblique shear fracture is transformed into composite fracture and tension fracture with the loading rate increasing. The microscopic fracture shows that increasing loading rate inhibits the evolution of oblique shear fractures and promotes the expansion of tensile fractures. The roughness level of tensile fractures is significantly lower than that of oblique shear fracture and composite fracture. The AE parameters and deformation behavior are characterized by simultaneous evolution. The AE amplitude changes from low-level and low-density distribution to high-level and high-density distribution as the loading rate increases. The AE activity intensity of tensile fracture is significantly greater than that of oblique shear fracture and composite fracture. The warning timeliness of cumulative AE events and cumulative AE energy is generally earlier than the AE b-value under the same loading rate, and the early warning timeliness of cumulative AE events is similar to that of cumulative AE energy.

Abstract Topological photonics attract significant interests due to their intriguing fundamental physics and potential applications. Researchers are actively exploring various artificial platforms to realize novel topological phenomena, which provides promising pathways for the development of robust photonic devices. Among these platforms, femtosecond laser direct-written photonic waveguides show unique ability to visualize intricate light dynamics in 2 + 1 dimensions, which rendering them ideal tools for investigating topological photonics. By integrating topological concepts into these waveguides, researchers not only deepen their understanding of topological physics but also provide potential methodology for developing advanced topological photonic integrated devices. In this review, we discuss recent experimental implementations of different topological phases within femtosecond laser direct-written photonic waveguides, as well as the fascinating physical phenomena induced by the interplay of topology with non-Hermiticity, nonlinearity and quantum physics are also introduced. The exploration of topological waveguide arrays shows great promise in advancing the field of topological photonics, providing a solid foundation for further research and innovation in this rapidly developing domain.

Abstract Generalized Anxiety Disorder (GAD) is a chronic anxiety condition characterized by persistent excessive worry, anxiety, and fear. Current diagnostic practices primarily rely on clinicians’ subjective assessments and experience, highlighting a need for more objective and reliable methods. This study collected 10-minute resting-state electroencephalogram (EEG) from 45 GAD patients and 36 healthy controls (HC), focusing on six frontal EEG channels for preprocessing, data segmentation, and frequency band division. Innovatively, this study introduced the “Differential Channel” method, which enhances classification performance by enhancing the information related to anxiety from the data, thereby highlighting signal differences. Utilizing the preprocessed EEG signals, undirected functional connectivity features (Phase Lag Index, Pearson Correlation Coefficient, and Mutual Information) and directed functional connectivity features (Partial Directed Coherence) were extracted. Multiple machine learning models were applied to distinguish between GAD patients and HC. The results show that the Deep Forest classifier achieves excellent performance with a 12-second time window of DiffFeature. In particular, the classification of GAD and HC was successfully obtained by combining OriFeature and DiffFeature on Mutual Information with a maximum accuracy of 98.08%. Furthermore, it was observed that undirected functional connectivity features significantly outperformed directed functional connectivity when fewer frontal channels were used. Overall, the methodologies developed in this study offer accurate and practical identification strategies for the early screening and clinical diagnosis of GAD, offering the necessary theoretical and technical support for further enhancing the portability of EEG devices.

Abstract Maintaining stillness is essential for accurate bioelectrical signal acquisition, but dynamic noise from breathing remains unavoidable. Isotropic adhesives are often used as bioelectronic interfaces to ensure signal fidelity, but they can leave irreversible residues, compromising device accuracy. We propose a hydrogel with selective frequency damping and asymmetric adhesion as a bioelectronic interface. This hydrogel mitigates dynamic noise from breathing, with a damping effect in the breathing frequency range 60 times greater than at other frequencies. It also exhibits an asymmetric adhesion difference of up to 537 times, preventing residues. By homogenizing ion distribution, extending Debye length, and densifying the electric field, the hydrogel ensures stable signal transmission over 10,000 cycles. Additionally, it can non-invasively diagnose otitis media with higher sensitivity than invasive probes and has been effective in clinical polysomnography monitoring, aiding in the diagnosis of obstructive sleep apnea.

Abstract Winter wheat constitutes approximately 20% of China’s total cereal production. However, calculations of total production based on multiplying the planted area by the yield have tended to produce overestimates. In this study, we generated sample points from existing winter wheat maps and obtained samples for different years using a temporal migration method. Random forest classifiers were then constructed using optimized features extracted from spectral and phenological characteristics and elevation information. Maps of the harvested and planted areas of winter wheat in Chinese eight provinces from 2018 to 2022 were then produced. The resulting maps of the harvested areas achieved an overall accuracy of 95.06% verified by the sample points, and the correlation coefficient between the CROPGRIDS dataset is about 0.77. The harvested area was found to be about 13% smaller than the planted area, which can primarily be attributed to meteorological hazards. This study represents the first attempt to map the winter wheat harvested area at 10–m resolution in China, and it should improve the accuracy of yield estimation.

Abstract Patients diagnosed with IgA nephropathy (IgAN) commonly experience a substantial burden of symptoms encompassing both physical and psychological aspects. Presently, there's a dearth of standardized assessment tools to effectively gauge the extent of symptom burden in IgAN patients. Therefore, this study aims to devise an IgAN Symptom Assessment Tool that enables a comprehensive evaluation of patient symptom burden and their self-perceived severity. Employing a prospective observational design, this study conducted a survey among patients diagnosed with IgAN at a hospital in China. The research team formulated an IgAN Symptom Burden Assessment Scale and administered a questionnaire to gauge patient symptom burden. Severity assessment was conducted on a 5-point Likert scale, with higher scores indicating a more pronounced burden of symptoms. The finalized scale comprised 14 distinct symptom items, and the questionnaire survey garnered responses from 200 patients, achieving a 100% response rate. Statistical analysis unveiled that nearly all patients regarded these symptoms as prevalent and significantly impactful on their daily lives, resulting in a considerable burden. Notably, mild oliguria, moderate nasal congestion, bitter taste , throat discomfort, alongside severe manifestations such as muscle weakness, fatigue, and foamy urine, were frequently reported by patients. The findings underscore that a substantial proportion of IgAN patients grapple with a significant burden of symptoms, emphasizing the imperative for healthcare providers to prioritize symptom management and implement proactive measures to alleviate these challenges. This study presents an innovative tool tailored for evaluating symptom burden specifically in IgAN patients. Subsequent research should center on validating this tool within larger patient cohorts to optimize the efficacy of symptom management in this demographic.

Abstract Invasive cervical cancers (ICC), caused by HPV infections, have a heterogeneous molecular landscape. We investigate the detection, timing, and HPV type specificity of somatic mutations in 3929 HPV-positive exfoliated cervical cell samples from individuals undergoing cervical screening in the U.S. using deep targeted sequencing in ICC cases, precancers, and HPV-positive controls. We discover a subset of hotspot mutations rare in controls (2.6%) but significantly more prevalent in precancers, particularly glandular precancer lesions (10.2%), and cancers (25.7%), supporting their involvement in ICC carcinogenesis. Hotspot mutations differ by HPV type, and HPV18/45-positive ICC are more likely to have multiple hotspot mutations compared to HPV16-positive ICC. The proportion of cells containing hotspot mutations is higher (i.e., higher variant allele fraction) in ICC and mutations are detectable up to 6 years prior to cancer diagnosis. Our findings demonstrate the feasibility of using exfoliated cervical cells for detection of somatic mutations as potential diagnostic biomarkers.

Abstract Lettuce (Lactuca sativa L., Asteraceae) is one of the most important vegetable crops, known for its various horticultural types and significant morphological variation. The first reference genome of lettuce, a crisphead type (L. sativa var. capitata cv. Salinas), was previously released. Here, we reported a near-complete chromosome-level reference genome for looseleaf lettuce (L. sativa var. crispa). PacBio high-fidelity sequencing, Oxford Nanopore, and Hi-C technologies were employed to produce genome assembly. The final assembly is 2.59 Gb in length with a contig N50 of 205.47 Mb, anchored onto nine chromosomes, containing 14 recognizable telomeres and only 11 gaps. Repetitive sequences account for 77.11% of the genome, and 41,375 protein-coding genes were predicted, with 99.10% of these assigned functional annotations. This chromosome-level genome enriched genomic resources for various horticultural types of lettuce and will facilitate the characterization of morphological variation and genetic improvement in lettuce.

Abstract Coal seam mining causes fracture and movement of overlying strata in goaf, and endangers the safety of surface structures and underground pipelines. Based on the engineering geological conditions of 22,122 working face in Cuncaota No.2 Coal Mine of China Shenhua Shendong Coal Group Co., Ltd. a similar material model test of mining overburden rock was carried out. The subsidence of overburden rock was obtained through the full-section strain data of distributed optical fiber technology, and the characteristics of mining surface subsidence were studied. The Weibull model was used to adjust the mathematical form of the first half of the surface subsidence curve via the MMF function. On this basis, the prediction model of coal seam mining surface subsidence was established, and the parameters of the prediction model of surface subsidence were determined. The test results show that with the advancement of coal seam mining, the fit goodness of the surface subsidence prediction curve based on the MMF optimization model reaches 0.987. Compared with the measured values, the relative error of the surface subsidence prediction model is reduced to less than 10%. The model displays good prediction accuracy. The time required for settlement stability in the prediction model is positively correlated with parameter a and negatively correlated with parameter b. The research results can be further extended to the prediction of overburden “three zones” subsidence, and provide a scientific basis for the evaluation of surface subsidence compression potential in coal mine goaf.

Abstract The process of printing defect detection usually suffers from challenges such as inaccurate defect extraction and localization, caused by uneven illumination and complex textures. Moreover, image difference-based defect detection methods often result in numerous small-scale pseudo defects. To address these challenges, this paper proposes a comprehensive defect detection approach that integrates brightness correction and a two-stage defect detection strategy for self-adhesive printed materials. Concretely, a joint bilateral filter coupled with brightness correction corrects uneven brightness properly, meanwhile smoothing the grid-like texture in complex printed material images. Then, in the first detection stage, an image difference method based on a bright–dark difference template group is designed to effectively locate printing defects despite slight brightness fluctuations. Afterward, a discriminative method based on feature similarity is employed to filter out small-scale pseudo-defects in the second detection stage. The experimental results show that the improved difference method achieves an average precision of 99.1% in defect localization on five different printing pattern samples. Furthermore, the second stage reduces the false detection rate to under 0.5% while maintaining the low missed rate.

Abstract Microbes have been demonstrated to be closely linked to diseases that pose a major threat to human health. Computing technologies can help researchers find potential microbe-drug associations more quickly and precisely. In this study, we introduced a novel computational prediction model called GLNNMDA based on global and local features of microbes and drugs to infer possible microbe-drug correlations. In GLNNMDA, we first constructed a heterogeneous network based on known microbe-drug relationships by integrating multiple similarity metrics of drugs and microbes. Subsequently, low-dimensional features will be extracted for nodes in the heterogeneous network by adopting the graph attention encoder. Next, based on combining these low-dimensional features with multiple properties of microbes and drugs to form a new comprehensive feature matrix, we would utilize the GLF module to extract the global and local features for microbes and drugs respectively, and then, we would further fuse these global and local features to come up with predictions of possible microbe-drug associations. Moreover, in order to evaluate the prediction performance of GLNNMDA, under the framework of fivefold cross-validation, intensive comparative experiments and case studies were done on different well-known public databases. The results showed that GLNNMDA obtained the highest AUC values as well as AUPR values of 0.9802 ± 0.0011, 0.9773 ± 0.0021 and 0.8586 ± 0.0004, 0.8008 ± 0.0031 in the two databases, MDAD and aBiofilm, respectively, compared to the state-of-the-art competing prediction methods. In addition, case studies of well-known microorganisms and drugs have demonstrated the effectiveness of GLNNMDA in inferring potential microbial drug associations, which implies that GLNNMDA may be a useful tool for microbe-drug association prediction in the future. The source code is available at: “ https://github.com/KuangHaiYue/GLNNMDA.git ”.

Abstract Alkoxycarbonylation reactions are common in the chemical industry, yet process sustainability is limited by the inefficient utilization of CO. In this study, we address this issue and demonstrate that significant improvements can be achieved by adopting a heterogeneously catalyzed process, using a Ru/NbOx catalyst. The Ru/NbOx catalyst enables the direct synthesis of methyl propionate, a key industrial commodity, with over 98% selectivity from CO, ethylene and methanol, without any ligands or acid/base promoters. Under ambient CO pressure, a high CO utilization efficiency (336 mmolestermolCO −1h−1) is achieved. Mechanistic investigations reveal that CO undergoes a methoxycarbonyl (COOCH3) intermediate pathway, attacking the terminal carbon atom of alkene and yielding linear esters. The origins of prevailing linear regioselectivity in esters are revealed. The infrared spectroscopic feature of the key COOCH3 species is observed at 1750 cm−1 (C=O vibration) both experimentally and computationally. The broad substrate applicability of Ru/NbOx catalyst for ester production is demonstrated. This process offers a sustainable and efficient approach with high CO utilization and atom economy for the synthesis of esters.

Abstract Converting solar energy into fuels is pursued as an attractive route to reduce dependence on fossil fuel. In this context, photothermal catalysis is a very promising approach through converting photons into heat to drive catalytic reactions. There are mainly three key factors that govern the photothermal catalysis performance: maximized solar absorption, minimized thermal emission and excellent catalytic property of catalyst. However, the previous research has focused on improving solar absorption and catalytic performance of catalyst, largely neglected the optimization of thermal emission. Here, we demonstrate an optically selective catalyst based Ti3C2Tx Janus design, that enables minimized thermal emission, maximized solar absorption and good catalytic activity simultaneously, thereby achieving excellent photothermal catalytic performance. When applied to Sabatier reaction and reverse water-gas shift (RWGS) as demonstrations, we obtain an approximately 300% increase in catalytic yield through reducing the thermal emission of catalyst by ~70% under the same irradiation intensity. It is worth noting that the CO2 methanation yield reaches 3317.2 mmol gRu −1 h−1 at light power of 2 W cm−2, setting a performance record among catalysts without active supports. We expect that this design opens up a new pathway for the development of high-performance photothermal catalysts.

Abstract Osteoarthritis (OA) is a chronic degenerative disease characterized by articular cartilage destruction and subchondral bone reconstruction in the early stages. Bergenin (Ber) is a cytoprotective polyphenol found in many medicinal plants. It has been proven to have anti-inflammatory, antioxidant, and other biological activities, which may reveal its potential role in the treatment of OA. This study aimed to determine the potential efficacy of Ber in treating OA and explore the possible underlying mechanism through network pharmacology and validation experiments. The potential co-targets and processes of Ber and OA were predicted by using network pharmacology, including a Venn diagram for intersection targets, a protein‒protein interaction (PPI) network to obtain key potential targets, and GO and KEGG pathway enrichment to reveal the probable mechanism of action of Ber on OA. Subsequently, validation experiments were carried out to investigate the effects and mechanisms of Ber in treating OA in vitro and vivo. Ber suppressed IL-1β-induced chondrocyte apoptosis and extracellular matrix catabolism by inhibiting the STAT3, NF-κB and Jun signalling pathway in vitro. Furthermore, Ber suppressed the expression of osteoclast marker genes and RANKL-induced osteoclastogenesis. Ber alleviated the progression of OA in DMM-induced OA mice model. These results demonstrated the protective efficacy and potential mechanisms of Ber against OA, which suggested that Ber could be adopted as a potential therapeutic agent for treating OA.

Abstract With the surge in Xinjiang jujube production, there has been a concurrent increase in storage losses, posing an ongoing challenge for farmers to preserve the freshness of the jujubes. To tackle this issue, a novel storage and freshness control system for jujubes, integrating Internet of Things technology, has been developed. The control system is centered around a programmable logic controller (PLC) and utilizes an HMI as the interface for human–computer interaction. It is structured with distinct layers, including equipment, transportation, and application layers. By integrating with the Internet of Things cloud platform, data transmission between the device layer and the cloud server is ensured through the use of the TCP/IP protocol over a 4G network. A mobile app enables remote control functionality for monitoring and managing the storage and preservation environment. Experimental results demonstrate the system's stable performance, enabling remote monitoring and convenient operation by management personnel during the jujube storage and preservation process. This contributes to enhancing automation levels in jujube storage, extending its storage cycle while maintaining quality standards, thus providing valuable insights into intelligent fruit and vegetable storage practices in Xinjiang.

Abstract Roberts syndrome (RBS) is an autosomal recessive disorder with profound growth deficiency and limb reduction caused by ESCO2 loss-of-function variants. Here, we elucidate the pathogenesis of limb reduction in an Esco2 fl/fl;Prrx1-Cre Tg/0 mouse model using bulk- and single-cell-RNA-seq and gene co-expression network analyses during embryogenesis. Our results reveal morphological and vascular defects culminating in hemorrhage of mutant limbs at E12.5. Underlying this abnormal developmental progression is a pre-apoptotic, mesenchymal cell population specific to mutant limb buds enriched for p53-related signaling beginning at E9.5. We then characterize these p53-related processes of cell cycle arrest, DNA damage, cell death, and the inflammatory leukotriene signaling pathway in vivo. In utero treatment with pifithrin-α, a p53 inhibitor, rescued the hemorrhage in mutant limbs. Lastly, significant enrichments were identified among genes associated with RBS, thalidomide embryopathy, and other genetic limb reduction disorders, suggesting a common vascular etiology among these conditions.

Abstract Tandem repeats (TRs) are genomic regions that tandemly change in repeat number, which are often multiallelic. Their characteristics and contributions to gene expression and quantitative traits in rice are largely unknown. Here, we survey rice TR variations based on 231 genome assemblies and the rice pan-genome graph. We identify 227,391 multiallelic TR loci, including 54,416 TR variations that are absent from the Nipponbare reference genome. Only 1/3 TR variations show strong linkage with nearby bi-allelic variants (SNPs, Indels and PAVs). Using 193 panicle and 202 leaf transcriptomic data, we reveal 485 and 511 TRs act as QTLs independently of other bi-allelic variations to nearby gene expression, respectively. Using plant height and grain width as examples, we identify and validate TRs contributions to rice agronomic trait variations. These findings would enhance our understanding of the functions of multiallelic variants and facilitate rice molecular breeding.

Abstract Deep learning models have been developed for various predictions in glioma; yet, they were constrained by manual segmentation, task-specific design, or a lack of biological interpretation. Herein, we aimed to develop an end-to-end multi-task deep learning (MDL) pipeline that can simultaneously predict molecular alterations and histological grade (auxiliary tasks), as well as prognosis (primary task) in gliomas. Further, we aimed to provide the biological mechanisms underlying the model’s predictions. We collected multiscale data including baseline MRI images from 2776 glioma patients across two private (FAHZU and HPPH, n = 1931) and three public datasets (TCGA, n = 213; UCSF, n = 410; and EGD, n = 222). We trained and internally validated the MDL model using our private datasets, and externally validated it using the three public datasets. We used the model-predicted deep prognosis score (DPS) to stratify patients into low-DPS and high-DPS subtypes. Additionally, a radio-multiomics analysis was conducted to elucidate the biological basis of the DPS. In the external validation cohorts, the MDL model achieved average areas under the curve of 0.892–0.903, 0.710–0.894, and 0.850–0.879 for predicting IDH mutation status, 1p/19q co-deletion status, and tumor grade, respectively. Moreover, the MDL model yielded a C-index of 0.723 in the TCGA and 0.671 in the UCSF for the prediction of overall survival. The DPS exhibits significant correlations with activated oncogenic pathways, immune infiltration patterns, specific protein expression, DNA methylation, tumor mutation burden, and tumor-stroma ratio. Accordingly, our work presents an accurate and biologically meaningful tool for predicting molecular subtypes, tumor grade, and survival outcomes in gliomas, which provides personalized clinical decision-making in a global and non-invasive manner.

Abstract This study aims to assess the global prevalence of kinesiophobia and the potential influencing factors among patients with heart disease. A comprehensive search was conducted in PubMed, Embase, Web of Science, PsycINFO, and Scopus databases to identify studies reporting on the prevalence of kinesiophobia and its influencing factors in heart disease patients up to January 2024. A random-effects model was employed to aggregate prevalence rates. Heterogeneity sources were investigated through subgroup analysis, while differences in the prevalence of kinesiophobia across regions, types of heart disease, and gender were evaluated. Additionally, a qualitative analysis of the factors influencing kinesiophobia was performed. This research incorporated 15 studies from six countries, with 14 providing data on the prevalence of kinesiophobia and nine exploring its potential influencing factors. The findings indicated that the overall prevalence of kinesiophobia among heart disease patients was 61.0% (95% CI 49.4–72.6%). Subgroup analysis revealed that the prevalence in upper-middle-income countries was 71.8% (95% CI 66.2–77.4%), while it stands at 49.9% (95% CI 30.2–69.5%) in high-income countries. The prevalence rates among patients with coronary artery disease, heart failure, and atrial fibrillation were 63.2% (95% CI 45.2–81.3%), 69.2% (95% CI 57.6–80.8%), and 71.6% (95% CI 67.1–76.1%), respectively. Gender-wise, no significant difference was observed in the prevalence of kinesiophobia between men and women (52.2% vs. 51.8%). A total of 24 potential influencing factors of kinesiophobia were identified, with education level, monthly income, anxiety, and exercise self-efficacy being the most recognized. The prevalence of kinesiophobia in patients with heart disease is notably high and is influenced by a multitude of factors. Early implementation of targeted preventive measures is imperative to mitigate the incidence of kinesiophobia in this population.

Abstract Despite advancements in antiretroviral therapy (ART) suppressing HIV-1 replication, existing antiviral drugs pose limitations, including lifelong medication, frequent administration, side effects and viral resistance, necessitating novel HIV-1 treatment approaches. CD4, pivotal for HIV-1 entry, poses challenges for drug development due to neutralization and cytotoxicity concerns. Nevertheless, Ibalizumab, the sole approved CD4-specific antibody for HIV-1 treatment, reignites interest in exploring alternative anti-HIV targets, emphasizing CD4’s potential value for effective drug development. Here, we explore anti-CD4 nanobodies, particularly Nb457 from a CD4-immunized alpaca. Nb457 displays high potency and broad-spectrum activity against HIV-1, surpassing Ibalizumab’s efficacy. Strikingly, engineered trimeric Nb457 nanobodies achieve complete inhibition against live HIV-1, outperforming Ibalizumab and parental Nb457. Structural analysis unveils Nb457-induced CD4 conformational changes impeding viral entry. Notably, Nb457 demonstrates therapeutic efficacy in humanized female mouse models. Our findings highlight anti-CD4 nanobodies as promising HIV-1 therapeutics, with potential implications for advancing clinical treatment against this global health challenge.

Abstract Programmed cell death (PCD) is a process that eliminates infected, damaged, or possibly neoplastic cells to sustain homeostatic multicellular organisms. Although long noncoding RNAs (lncRNAs) are involved in various types of PCD and regulate tumor growth, invasion, and migration, the role of PCD-related lncRNAs in bladder cancer still lacks systematic exploration. In this research, we integrated multiple types of PCD as pan-PCD and identified eight pan-PCD-related lncRNAs (LINC00174, HCP5, HCG27, UCA1, SNHG15, GHRLOS, CYB561D2, and AGAP11). Then, we generated a pan-PCD-related lncRNA prognostic signature (PPlncPS) with excellent predictive power and reliability, which performed equally well in the E-MTAB-4321 cohort. In comparison with the low-PPlncPS score group, the high-PPlncPS score group had remarkably higher levels of angiogenesis, matrix, cancer-associated fibroblasts, myeloid cell traffic, and protumor cytokine signatures. In addition, the low-PPlncPS score group was positively correlated with relatively abundant immune cell infiltration, upregulated expression levels of immune checkpoints, and high tumor mutation burden (TMB). Immunogenomic profiles revealed that patients with both low PPlncPS scores and high TMB had the best prognosis and may benefit from immune checkpoint inhibitors. Furthermore, for patients with high PPlncPS scores, docetaxel, staurosporine, and luminespib were screened as potential therapeutic candidates. In conclusion, we generated a pan-PCD-related lncRNA signature, providing precise and individualized prediction for clinical prognosis and some new insights into chemotherapy and immune checkpoint inhibitor therapy for bladder cancer.

Abstract Sodium is crucial for maintaining cardiovascular health, especially in relation to heart failure. The impact of baseline serum sodium concentrations on the outcomes of newly diagnosed coronary heart disease (CHD) without heart failure remains unclear. This prospective cohort study included 681 patients who were newly diagnosed with CHD. Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to assess the relationship between serum sodium concentrations and major adverse cardiovascular events. The improvement in traditional prediction models by the addition of serum sodium concentrations was assessed using changes in the C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). During a median follow-up of 51.04 months (IQR: 40.88–53.80 months), 131 events were recorded. Multivariate Cox proportional hazards models showed that the L2 group (136–138.9 mmol/L) had the highest MACE risk. Compared to L2, the hazard ratios (HRs) and 95% confidence intervals (CIs) for the L1 (130–135.9 mmol/L), L3 (139–140.9 mmol/L), L4 (141–142.9 mmol/L), and L5 (143–147.0 mmol/L) groups were 0.31 (0.14–0.70, P = 0.005), 0.48 (030–0.78, P = 0.003), 0.56 (0.34–0.92, P = 0.022), and 0.37 (0.22–0.64, P

Abstract Lung adenocarcinoma (LUAD) is a leading cause of cancer mortality, with many patients facing poor prognosis, particularly those with metastatic or drug-resistant tumors. Homologous recombination genes (HRGs) are crucial in tumor progression and therapy resistance, but their clinical significance in LUAD is not well understood. In this study, we systematically characterize key HRGs in LUAD patients, identifying two distinct HR subtypes associated with different outcomes and biological functions. We establish a 5-gene scoring system (XRCC2, RAD51, BRCA1, FANCA, and CHEK1) that reliably predicts patient outcomes and immunotherapy responses in LUAD. Bioinformatics analysis and clinical validation highlight XRCC2 as a crucial biomarker in LUAD. Functional investigations through in vivo and in vitro experiments reveal the role of XRCC2 in promoting lung cancer migration and invasion. Mechanistically, XRCC2 stabilizes vimentin (VIM) protein expression through deubiquitylation. We predict c-MYC as a potential regulator of XRCC2 and demonstrate that inhibiting c-MYC with compound 10058-F4 reduces XRCC2 and VIM expression. Preclinical studies show the synergistic inhibition of metastasis in vivo when combining 10058-F4 with doxorubicin (Dox). Our findings present a potential personalized predictive tool for LUAD prognosis, identifying XRCC2 as a critical biomarker. The c-Myc-XRCC2-VIM axis emerges as a promising therapeutic target for overcoming lung metastasis. This study provides valuable insights into LUAD, proposing a prognostic tool for further clinical validation and unveiling a potential therapeutic strategy for combating lung metastasis by targeting c-Myc-XRCC2-VIM.

Abstract The development of broad-spectrum coronavirus vaccines is essential to prepare for future respiratory virus pandemics. We demonstrated broad neutralization by a trivalent subunit vaccine, formulating the receptor-binding domains of SARS-CoV, MERS-CoV, and SARS-CoV-2 XBB.1.5 with Alum and CpG55.2. Vaccinated mice produced cross-neutralizing antibodies against all three human Betacoronaviruses and others currently exclusive to bats, indicating the epitope preservation of the individual antigens during co-formulation and the potential for epitope broadening.

Abstract Employing machine learning methods for mapping surface ocean pCO2 has reduced the uncertainty in estimating sea-air CO2 flux. However, a general discrepancy exists between the Southern Ocean carbon sinks derived from pCO2 products and those from biogeochemistry models. Here, by performing a boosting ensemble learning feed-forward neural networks method, we have identified an underestimation of the surface Southern Ocean pCO2 due to notably uneven density of pCO2 measurements between summer and winter, which resulted in about 16% overestimating of Southern Ocean carbon sink over the past three decades. In particular, the Southern Ocean carbon sink since 2010 was notably overestimated by approximately 29%. This overestimation can be mitigated by a winter correction in algorithms, with the average Southern Ocean carbon sink during 1992-2021 corrected to −0.87 PgC yr−1 from the original −1.01 PgC yr−1. Furthermore, the most notable underestimation of surface ocean pCO2 mainly occurred in regions south of 60°S and was hiding under ice cover. As the surface ocean pCO2 under sea ice coverage in the winter is much higher than the atmosphere, if sea ice melts completely, there could be a further reduction of about 0.14 PgC yr−1 in the Southern Ocean carbon sink.

Abstract Electrocatalytic semihydrogenation of acetylene (C2H2) provides a facile and petroleum-independent strategy for ethylene (C2H4) production. However, the reliance on the preseparation and concentration of raw coal-derived C2H2 hinders its economic potential. Here, a concave surface is predicted to be beneficial for enriching C2H2 and optimizing its mass transfer kinetics, thus leading to a high partial pressure of C2H2 around active sites for the direct conversion of raw coal-derived C2H2. Then, a porous concave carbon-supported Cu nanoparticle (Cu-PCC) electrode is designed to enrich the C2H2 gas around the Cu sites. As a result, the as-prepared electrode enables a 91.7% C2H4 Faradaic efficiency and a 56.31% C2H2 single-pass conversion under a simulated raw coal-derived C2H2 atmosphere (~15%) at a partial current density of 0.42 A cm−2, greatly outperforming its counterpart without concave surface supports. The strengthened intermolecular π conjugation caused by the increased C2H2 coverage is revealed to result in the delocalization of π electrons in C2H2, consequently promoting C2H2 activation, suppressing hydrogen evolution competition and enhancing C2H4 selectivity.

Abstract The cold tolerance of Litopenaeus vannamei is important for breeding in specific areas. To explore the cold tolerance mechanism of L. vannamei, this study analyzed biochemical indicators, cell apoptosis, and metabolomic responses in cold-tolerant (Lv-T) and common (Lv-C) L. vannamei under low-temperature stress (18 °C and 10 °C). TUNEL analysis showed a significant increase in apoptosis of hepatopancreatic duct cells in L. vannamei under low-temperature stress. Biochemical analysis showed that Lv-T had significantly increased levels of superoxide dismutase (SOD) and triglycerides (TG), while alanine aminotransferase (ALT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH-L), and uric acid (UA) levels were significantly decreased compared to Lv-C (p

Abstract Obesity shapes anti-tumor immunity through lipid metabolism; however, the mechanisms underlying how colorectal cancer (CRC) cells utilize lipids to suppress anti-tumor immunity remain unclear. Here, we show that tumor cell-intrinsic ATP6V0A1 drives exogenous cholesterol-induced immunosuppression in CRC. ATP6V0A1 facilitates cholesterol absorption in CRC cells through RAB guanine nucleotide exchange factor 1 (RABGEF1)-dependent endosome maturation, leading to cholesterol accumulation within the endoplasmic reticulum and elevated production of 24-hydroxycholesterol (24-OHC). ATP6V0A1-induced 24-OHC upregulates TGF-β1 by activating the liver X receptor (LXR) signaling. Subsequently, the release of TGF-β1 into the tumor microenvironment by CRC cells activates the SMAD3 pathway in memory CD8+ T cells, ultimately suppressing their anti-tumor activities. Moreover, we identify daclatasvir, a clinically used anti-hepatitis C virus (HCV) drug, as an ATP6V0A1 inhibitor that can effectively enhance the memory CD8+ T cell activity and suppress tumor growth in CRC. These findings shed light on the potential for ATP6V0A1-targeted immunotherapy in CRC.

Abstract Large language models (LLMs) are seen to have tremendous potential in advancing medical diagnosis recently, particularly in dermatological diagnosis, which is a very important task as skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases. Here we present SkinGPT-4, which is an interactive dermatology diagnostic system based on multimodal large language models. We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly available and proprietary images) along with clinical concepts and doctors’ notes, and designing a two-step training strategy. We have quantitatively evaluated SkinGPT-4 on 150 real-life cases with board-certified dermatologists. With SkinGPT-4, users could upload their own skin photos for diagnosis, and the system could autonomously evaluate the images, identify the characteristics and categories of the skin conditions, perform in-depth analysis, and provide interactive treatment recommendations.

Abstract Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries offer more nuanced and accurate insights into the regulatory mechanisms of RNA editing in the human brain.

Abstract High-quality ocean in situ profile observations are fundamental for ocean and climate research and operational oceanographic applications. Here we describe a new global ocean subsurface temperature profile database named the Chinese Academy of Science (CAS) Oceanography Data Center version 1 (CODC-v1). This database contains over 17 million temperature profiles between 1940–2023 from all available instruments. The major data source is the World Ocean Database (WOD), but CODC-v1 also includes some data from some Chinese institutes which are not available in WOD. The data are quality-controlled (QC-ed) by a new QC system that considers the skewness of local temperature distributions, topographic barriers, and the shift of temperature distributions due to climate change. Biases in Mechanical Bathythermographs (MBTs), eXpendable Bathythermographs (XBTs), and Bottle data (OSD) are all corrected using recently proposed correction schemes, which makes CODC-v1 a bias-corrected dataset. These aspects ensure the data quality of the CODC-v1 database, making it suitable for a wide spectrum of ocean and climate research and applications.

Abstract Stretching elastic materials containing nanoparticle lattices is common in research and industrial settings, yet our knowledge of the deformation process remains limited. Understanding how such lattices reconfigure is critically important, as changes in microstructure lead to significant alterations in their performance. This understanding has been extremely difficult to achieve due to a lack of fundamental rules governing the rearrangements. Our study elucidates the physical processes and underlying mechanisms of three-dimensional lattice transformations in a polymeric photonic crystal from 0% to over 200% strain during uniaxial stretching. Corroborated by comprehensive experimental characterizations, we present analytical models that precisely predict both the three-dimensional lattice structures and the macroscale deformations throughout the stretching process. These models reveal how the nanoparticle lattice and matrix polymer jointly determine the resultant structures, which breaks the original structural symmetry and profoundly changes the dispersion of photonic bandgaps. Stretching induces shifting of the main pseudogap structure out from the 1st Brillouin zone and the merging of different symmetry points. Evolutions of multiple photonic bandgaps reveal potential optical singularities shifting with strain. This work sets a new benchmark for the reconfiguration of soft material structures and may lay the groundwork for the study of stretchable three-dimensional topological photonic crystals.

Abstract The high Faradaic efficiency (FE) of the electrocatalytic deuteration of organics with D2O at a large current density is significant for deuterated electrosynthesis. However, the FE and current density are the two ends of a seesaw because of the severe D2 evolution side reaction at nearly industrial current densities. Herein, we report a combined scenario of a nanotip-enhanced electric field and surfactant-modified interface microenvironment to enable the electrocatalytic deuteration of arylacetonitrile in D2O with an 80% FE at −100 mA cm−2. The increased concentration with low activation energy of arylacetonitrile due to the large electric field along the tips and the accelerated arylacetonitrile transfer and suppressed D2 evolution by the surfactant-created deuterophobic microenvironment contribute to breaking the trade-off between a high FE and large current density. Furthermore, the application of our strategy in other deuteration reactions with improved Faradaic efficiencies at −100 mA cm−2 rationalizes the design concept.

Abstract The human microbiome plays a crucial role in human health. However, the influence of maternal factors on the neonatal microbiota remains obscure. Herein, our observations suggest that the neonatal microbiotas, particularly the buccal microbiota, change rapidly within 24–48 h of birth but begin to stabilize by 48–72 h after parturition. Network analysis clustered over 200 maternal factors into thirteen distinct groups, and most associated factors were in the same group. Multiple maternal factor groups were associated with the neonatal buccal, rectal, and stool microbiotas. Particularly, a higher maternal inflammatory state and a lower maternal socioeconomic position were associated with a higher alpha diversity of the neonatal buccal microbiota and beta diversity of the neonatal stool microbiota was influenced by maternal diet and cesarean section by 24–72 h postpartum. The risk of admission of a neonate to the newborn intensive care unit was associated with preterm birth as well as higher cytokine levels and probably higher alpha diversity of the maternal buccal microbiota.

Abstract RNF214 is an understudied ubiquitin ligase with little knowledge of its biological functions or protein substrates. Here we show that the TEAD transcription factors in the Hippo pathway are substrates of RNF214. RNF214 induces non-proteolytic ubiquitylation at a conserved lysine residue of TEADs, enhances interactions between TEADs and YAP, and promotes transactivation of the downstream genes of the Hippo signaling. Moreover, YAP and TAZ could bind polyubiquitin chains, implying the underlying mechanisms by which RNF214 regulates the Hippo pathway. Furthermore, RNF214 is overexpressed in hepatocellular carcinoma (HCC) and inversely correlates with differentiation status and patient survival. Consistently, RNF214 promotes tumor cell proliferation, migration, and invasion, and HCC tumorigenesis in mice. Collectively, our data reveal RNF214 as a critical component in the Hippo pathway by forming a signaling axis of RNF214-TEAD-YAP and suggest that RNF214 is an oncogene of HCC and could be a potential drug target of HCC therapy.

Abstract Given the marginal penetration of most drugs across the blood-brain barrier, the efficacy of various agents remains limited for glioblastoma (GBM). Here we employ low-intensity pulsed ultrasound (LIPU) and intravenously administered microbubbles (MB) to open the blood-brain barrier and increase the concentration of liposomal doxorubicin and PD-1 blocking antibodies (aPD-1). We report results on a cohort of 4 GBM patients and preclinical models treated with this approach. LIPU/MB increases the concentration of doxorubicin by 2-fold and 3.9-fold in the human and murine brains two days after sonication, respectively. Similarly, LIPU/MB-mediated blood-brain barrier disruption leads to a 6-fold and a 2-fold increase in aPD-1 concentrations in murine brains and peritumoral brain regions from GBM patients treated with pembrolizumab, respectively. Doxorubicin and aPD-1 delivered with LIPU/MB upregulate major histocompatibility complex (MHC) class I and II in tumor cells. Increased brain concentrations of doxorubicin achieved by LIPU/MB elicit IFN-γ and MHC class I expression in microglia and macrophages. Doxorubicin and aPD-1 delivered with LIPU/MB results in the long-term survival of most glioma-bearing mice, which rely on myeloid cells and lymphocytes for their efficacy. Overall, this translational study supports the utility of LIPU/MB to potentiate the antitumoral activities of doxorubicin and aPD-1 for GBM.

Abstract Proteins and nucleic-acids are essential components of living organisms that interact in critical cellular processes. Accurate prediction of nucleic acid-binding residues in proteins can contribute to a better understanding of protein function. However, the discrepancy between protein sequence information and obtained structural and functional data renders most current computational models ineffective. Therefore, it is vital to design computational models based on protein sequence information to identify nucleic acid binding sites in proteins. Here, we implement an ensemble deep learning model-based nucleic-acid-binding residues on proteins identification method, called SOFB, which characterizes protein sequences by learning the semantics of biological dynamics contexts, and then develop an ensemble deep learning-based sequence network to learn feature representation and classification by explicitly modeling dynamic semantic information. Among them, the language learning model, which is constructed from natural language to biological language, captures the underlying relationships of protein sequences, and the ensemble deep learning-based sequence network consisting of different convolutional layers together with Bi-LSTM refines various features for optimal performance. Meanwhile, to address the imbalanced issue, we adopt ensemble learning to train multiple models and then incorporate them. Our experimental results on several DNA/RNA nucleic-acid-binding residue datasets demonstrate that our proposed model outperforms other state-of-the-art methods. In addition, we conduct an interpretability analysis of the identified nucleic acid binding residue sequences based on the attention weights of the language learning model, revealing novel insights into the dynamic semantic information that supports the identified nucleic acid binding residues. SOFB is available at https://github.com/Encryptional/SOFB and https://figshare.com/articles/online_resource/SOFB_figshare_rar/25499452 .