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Bioactive ceramics have been used in bone tissue repair and regeneration. However, because of the complex in vivo osteogenesis process, long cycle, and difficulty of accurately tracking, the mechanism of interaction between materials and cells has yet to be fully understood, hindering its development. The ceramic microbridge microfluidic chip system may solve the problem and provide an in vitro method to simulate the microenvironment in vivo. Nevertheless, the complex microenvironment parameters of the chip system need to be studied in detail. Computer simulation bionics can provide clues for the setting of microenvironment parameters. This study used a computational bionic model to simulate the bone growth process in the presence of immune-related factors. The osteoblast differentiation of mesenchymal stem cells of calcium phosphate ceramics in a macrophage-dominated immune microenvironment was studied using a microfluidic chip system. The computational biomimetic model and microfluidic chip findings were basically consistent with the reported results of the animal experiments. These findings suggest that studying the osteogenic behavior of calcium phosphate ceramics using a microfluidic chip model is feasible. The method model provided in this study can be extended to other biomaterials, providing a viable path for their research and evaluation.

Abstract Exploring the optimization of communication strategies for animation films in the context of cross-cultural communication, this research integrates the Internet of Things (IoT) and convolutional networks. The research constructs a collaborative filtering (CF) movie recommendation model based on a graph convolutional neural network (GCN) and investigates its application in cross-cultural communication. The fusion of IoT and convolutional networks in movie communication is also analyzed, and the effectiveness of the proposed GCN-CF model is validated through comparative experiments. The results indicate that, compared to other models, the GCN-CF model achieves the lowest Root Mean Square Error (RMSE) on the MovieLens 100 K and MovieLens 1 M datasets, with values of 0.8762 and 0.8275, respectively. Compared to traditional models, the GCN-CF model exhibits significantly superior performance in terms of RMSE, with reductions ranging from 0.6 to 5.2%, highlighting its heightened detection accuracy and overall performance. Moreover, the performance of the GCN-CF model is enhanced after introducing attention mechanisms and auxiliary information on both datasets, showing an improvement of 0.4% compared to the scenario without these additions. This data demonstrates the effectiveness of attention mechanisms and auxiliary information. Finally, the research presents an animation film communication strategy based on IoT and convolutional networks, offering novel insights for film production and communication, along with positive implications for cultural exchange and the advancement of the global media industry.

Abstract Enzymes with high catalytic activity and stability are essential for industrial production, yet most natural enzymes do not meet these requirements. Therefore, efficient strategies for enzyme engineering are crucial. In this study, we developed a cost-effective computational design strategy to enhance the activity of tyrosine phenol-lyase (TPL) for the production of L-DOPA. By integrating structural analysis with computational design, and guided by our understanding of conformational flexibility of TPL, we identified a region where enhanced stability is most likely to facilitate enzyme activity. We screened stabilizing mutations by Cartesian_ddg in Rosetta. After identifying single stabilizing mutations, we grouped the nearby positions harboring multiple stabilizing mutations and calculated the energy of combinatorial variants. We found two promising groups where most variants exhibited lower calculated energy than the wild-type. Experimental validation showed five variants in these groups exhibit increased activity, with the two best variants showing catalytic activity enhancements of 1.8-fold and 1.6-fold compared to the wild-type enzyme.

Abstract Loss of ARID1A has been reported to drive the progression of lung adenocarcinoma, yet the underlying mechanism remains elusive. In this study, we performed secretome analysis to identify the key secreted proteins regulating lung adenocarcinoma progression. We showed that the VASN level was significantly elevated in the conditioned medium from ARID1A-depleted A549 and H1299 cells. Restoration of ARID1A in ARID1A-depleted lung adenocarcinoma cells prevented the upregulation and secretion of VASN. Clinical analysis demonstrated a negative correlation between ARID1A and VASN expression in ARID1A-mutated lung adenocarcinomas. The patients with ARID1A-mutated lung adenocarcinoma had significantly higher concentrations of serum VASN than healthy controls. Moreover, serum VASN concentrations were associated with TNM stage, lymph node metastasis, and overall survival of the patients with ARID1A-mutated lung adenocarcinoma. Functional studies indicated that VASN overexpression potentiated the proliferation, invasion, and tumorigenesis of lung adenocarcinoma cells. Antibody neutralization of VASN suppressed the aggressiveness of ARID1A-depleted lung adenocarcinoma cells both in vitro and in vivo. Addition of recombinant VASN protein promoted the proliferation and invasion of lung adenocarcinoma cells. Additionally, knockdown of Notch1 blocked the aggressive phenotype induced by recombinant VASN protein. In conclusion, our data uncover the role of VASN in mediating the progression of ARID1A-depleted lung adenocarcinoma and highlight VASN as a promising therapeutic target for this disease.

To address issues such as inadequate fault tolerance, long computation time, and limited universality in fault location for active distribution networks, this paper proposes a fault location method that combines Petri nets with an improved particle swarm optimization (PSO) algorithm. This method enhances the efficiency of fault location in distribution networks with distributed power sources, demonstrating good applicability and convergence, especially in complex network scenarios. The results from two test functions and simulation analyses of two types of node distribution networks show that (1) in the single-point fault simulation, the improved algorithm successfully located the fault in the ninth iteration, outperforming the 14th iteration result of the standard PSO algorithm. (2) In networks with randomly interconnected distributed power sources, the algorithm accurately located both single and multiple faults. (3) Experimental verification further supports the simulation results, proving the effectiveness of this method in practical applications.

We conducted a longitudinal cohort study of SARS-CoV-2 and influenza rates in childcare centers and schools in Wuxi, China, collecting 1,760 environmental samples and 9,214 throat swabs from 593 students (regardless of symptoms) in weekly collections during February–June 2023. We estimated a cumulative infection rate of 124.8 (74 episodes)/1,000 persons for SARS-CoV-2 and 128.2 (76 episodes)/1,000 persons for influenza. The highest SARS-CoV-2 infection rate was in persons 18 years of age, and for influenza, in children 4 years of age. The asymptomatic proportion of SARS-CoV-2 was 59.6% and 66.7% for influenza; SARS-CoV-2 symptomatic proportion was lower in 16–18-year-olds than in 4–6-year-olds. Only samples from frequently touched surface tested positive for SARS-CoV-2 (4/1,052) and influenza (1/1,052). We found asynchronous circulation patterns of SARS-CoV-2 and influenza, similar to trends in national sentinel surveillance. The results support vaccination among pediatric populations and other interventions, such as environmental disinfection in educational settings.

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 Background Catheter-related thrombosis (CRT) is a thrombotic complication associated with using central venous catheters (CVCs). Although risk factors for CRT were identified in children, no nomograms or predictive tools are available for the pediatric population with CVCs. This study aimed to develop and validate a prediction model of asymptomatic CRT in children with CVCs. Methods This retrospective observational study included consecutive pediatric patients who admitted to the Children’s Hospital Zhejiang University School of Medicine and received CVCs between October and December 2021. Results This study included 669 patients, 553 (314 males, aged 22.00 [0.36, 180.00] months, 62 with CRT) were in the training set, and 116 (62 males, aged 15.00 [1.13, 156.00] months, 16 with CRT) were in the validation set. Multivariate logistic regression showed that a catheter time of 0–3 days (OR = 0.201, 95%CI: 0.081–0.497, P = 0.001), catheter time of 4–7 days (OR = 0.412, 95%CI: 0.176–0.964, P = 0.041), male (OR = 3.976, 95%CI: 1.864–4.483, P

ABSTRACT Enterovirus 71 (EV71) is a major pathogen that causes hand, foot, and mouth disease (HFMD) in infants and children. Notably, no clinically approved drugs specifically target EV71. The EV71 2A protease (2Apro), a cysteine protease produced by the virus, is essential for the virus’ replication and has a significant impact on the functioning of host cells. Thus, it presents a valuable target for the discovery of antiviral medications. In this study, based on the monomers and their derivatives in the Library of Traditional Chinese Medicine (TCM), we performed virtual screening and biological experiments. We identified a derivative of a traditional herbal monomer, Etoposide, commonly isolated from the roots and rhizomes of Podophyllum spp. Etoposide inhibited replication of EV71 A, B, C, and CVA16 viruses in a concentration-dependent manner in a variety of cell lines with minimal cytotoxicity. Furthermore, both molecular dynamics simulations and site-directed mutagenesis assays revealed that Etoposide inhibited the activity of the EV71 2A protease by mainly binding to two residues, Y89 and P107. The findings indicate that Etoposide serves as a promising inhibitor of the EV71 2Apro, demonstrating strong antiviral properties and positioning itself as a formidable candidate for clinical trials against EV71.IMPORTANCEWe first used a drug screening approach focused on monomeric compounds and their derivatives from traditional Chinese medicine to identify an EV71 2Apro inhibitor—Etoposide. We then performed biological experiments to validate that Etoposide suppresses the replication of the EV71 virus in a concentration-dependent manner with minimal cytotoxicity to various cell lines. Remarkably, it shows inhibitory activity against EV71 A, B, C, and CVA16, suggesting that Etoposide may be a potential broad-spectrum inhibitor. We revealed a novel mechanism that Etoposide inhibits EV71 proliferation by targeting 2Apro, and the interactions with Y89 and P107 are of great importance. The findings suggest that Etoposide serves as a promising inhibitor of EV71 2Apro, demonstrating significant antiviral properties. It stands out as a strong candidate for broad-spectrum applications in clinical research.

Due to the fatigue and continuous energy input during high-speed dynamic friction polishing (DFP), the diamond crystal beneath the polished surface (roughness 50 nm) and even preferential crystal cleavage with the non-diamond phase (distributing at the position in micrometers range).

Abstract Background Solute carrier family 34 member 2 (SLC34A2) has been implicated in the development of various malignancies. However, the clinical significance and underlying molecular mechanisms of SLC34A2 in esophageal squamous cell carcinoma (ESCC) remain elusive. Methods Western blotting, quantitative real‐time PCR and immunohistochemistry were utilized to evaluate the expression levels of SLC34A2 mRNA/protein in ESCC cell lines or tissues. Kaplan–Meier curves were employed for survival analysis. CCK‐8, colony formation, EdU and xenograft tumor model assays were conducted to determine the impact of SLC34A2 on ESCC cell proliferation. Cell cycle was examined using flow cytometry. RNA‐sequencing and enrichment analysis were carried out to explore the potential signaling pathways. The autophagic flux was evaluated by western blotting, mRFP‐GFP‐LC3 reporter system and transmission electron microscopy. Immunoprecipitation and mass spectrometry were utilized for identification of potential SLC34A2‐interacting proteins. Cycloheximide (CHX) chase and ubiquitination assays were conducted to test the protein stability. Results The expression of SLC34A2 was significantly upregulated in ESCC and correlated with unfavorable clinicopathologic characteristics particularly the Ki‐67 labeling index and poor prognosis of ESCC patients. Overexpression of SLC34A2 promoted ESCC cell proliferation, while silencing SLC34A2 had the opposite effect. Moreover, SLC34A2 induced autophagy to promote ESCC cell proliferation, whereas inhibition of autophagy suppressed the proliferation of ESCC cells. Further studies showed that SLC34A2 interacted with an autophagy‐related protein STX17 to promote autophagy and proliferation of ESCC cells by inhibiting the ubiquitination and degradation of STX17. Conclusions These findings indicate that SLC34A2 may serve as a prognostic biomarker for ESCC.

Study region: The Changzhou Plain, the Taihu Lake Basin, Eastern China. Study focus: This study introduces an event-based approach for assessing the impact of river changes on flood regulation capacity in urbanized plain river network regions for the first time. The Changzhou Plain, river length decreasing by 7.55 %, was taken as an example to assess the effects of river changes on its flood regulation capacity from the 1980s to the 2020 s. New hydrological insights for the region: Two key indices, flood storage capacity (FSC) and remaining flood storage capacity (RFSC), were developed and calculated using a coupled flood model. Both the coefficient of determination (R2) and the Nash–Sutcliffe efficiency (NSE) exceeded 0.90 during model calibration and validation. The Changzhou Plain experienced river degradation from the 1980s to the 2020 s, with 11.14 % reduction in tributary river length and 3.05 % increase in main river length, leading to decreased water surface area and enhanced connectivity among main rivers. Regional FSC and RFSC increased by 8.42 % and 1.97 %, respectively, due to improved connectivity of main rivers from the 1980s to the 2020 s. The reduction in tributary rivers had minimal effects on FSC (increase of 1.62 %) and RFSC (decrease of 1.74 %), while improved connectivity of main rivers contributed to significant increases in both FSC (6.70 %) and RFSC (3.74 %). These findings underscore the effectiveness of enhancing river connectivity as a strategy to bolster flood prevention in the Taihu Plain, offering valuable insights for flood management and river planning.

The growing microbial resistance to traditional medicines necessitates in-depth analysis of medicine-microbe interactions (MMIs) to develop new therapeutic strategies. Widely used artificial intelligence models are limited by sparse observational data and prevalent noise, leading to over-reliance on specific data for feature extraction and reduced generalization ability. To address these limitations, we integrate Kolmogorov-Arnold Networks (KANs), independent subspaces, and collaborative decoding techniques into the masked graph autoencoder (Mask GAE) framework, creating an innovative MMI prediction model with enhanced accuracy, generalization, and interpretability. First, we apply Bernoulli distribution to randomly mask parts of the medicine-microbe graph, advancing self-supervised training and reducing noise impact. Additionally, the independent subspace technique enables graph neural networks (GNNs) to learn weights independently across different feature subspaces, enhancing feature expression. Fusing the multi-layer outputs of GNNs effectively reduces information loss caused by masking. Moreover, using KANs for advanced nonlinear mapping enhances the learnability and interpretability of weights, deepening the understanding of complex MMIs. These measures significantly enhanced the accuracy, generalization, and interpretability of our model in MMI prediction tasks. We validated our model on three public datasets with results showing that our model outperformed existing leading models. The relevant data and code are publicly accessible at: https://github.com/zhuoninnin1992/MKAN-MMI.

Abstract Photothermoelectric (PTE) detectors combine photothermal and thermoelectric conversion, surmounting material band gap restrictions and limitations related to matching light wavelengths, have been widely used in telecommunication band detection. Two‐dimensional (2D) materials with gate‐tunable Seebeck coefficient can induce the generation of photothermal currents under illumination by the asymmetric Seebeck coefficient, making them promising candidate for PTE detectors in the telecommunication band. In this work, we report that a newly explored van der Waals (vdW) layered material, SnP2Se6, possessing excellent field regulation capabilities and behaviors as an ideal candidate for PTE detector implementation. With the assistance of temperature‐dependent Raman characterization, the suspended atomic thin SnP2Se6 nanosheets reveal thickness‐dependent thermal conductivity of 1.4–5.7 W m−1 K−1 at room temperature. The 2D SnP2Se6 demonstrates high Seebeck coefficient (S) and power factor (PF), which are estimated to be −506 μV K−1 and 207 μW m−1 K−2, respectively. By effectively modulating the SnP2Se6 localized carrier concentration, which in turn leads to inhomogeneous Seebeck coefficients, the designed dual‐gate PTE detector with 2D SnP2Se6 channel demonstrates wide spectral photoresponse in telecommunication bands, yielding high responsivity (R = 1.2 mA W−1) and detectivity (D* = 6 × 109 Jones) under 1550 nm light illumination. Our findings provide a new material platform and device configuration for the telecommunication band detection.

Objective: Traumatic brain injury (TBI) is among the leading causes of death and disability globally. Identifying and assessing the risk of in-hospital mortality in traumatic brain injury patients at an early stage is challenging. This study aimed to develop a model for predicting in-hospital mortality in TBI patients using prehospital data from China. Methods: We retrospectively included traumatic brain injury patients who sustained injuries due to external forces and were treated by pre-hospital emergency medical services (EMS) at a tertiary hospital. Data from the pre-hospital emergency database were analyzed, including demographics, trauma mechanisms, comorbidities, vital signs, clinical symptoms, and trauma scores. Eligible patients were randomly divided into a training set (241 cases) and a validation set (104 cases) at a 7:3 ratio. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were employed to identify independent risk factors. Analyzed the discrimination, calibration, and net benefit of the nomogram across both groups. Results: 17.40 % (42/241) of TBI patients died in the hospital in the training set, while 18.30 % (19/104) in the validation set. After analysis, chest trauma (odds ratio [OR] = 4.556, 95 % confidence interval [CI] = 1.861–11.152, P = 0.001), vomiting (OR = 2.944, 95%CI = 1.194–7.258, P = 0.019), systolic blood pressure (OR = 0.939, 95%CI = 0.913–0.966, P

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe and fatal acute respiratory disease in humans. High fatality rates and continued infectiousness remain a pressing concern for global health preparedness. Antibodies targeted at the receptor-binding domain (RBD) are major countermeasures against human viral infection. Here, we report four potent nanobodies against MERS-CoV, which are isolated from alpaca, and especially the potency of Nb14 is highest in the pseudotyped virus assay. Structural studies show that Nb14 framework regions (FRs) are mainly involved in interactions targeting a novel epitope, which is entirely distinct from all previously reported antibodies, and disrupt the protein-carbohydrate interaction between residue W535 of RBD and hDPP4 N229-linked carbohydrate moiety (hDPP4-N229-glycan). Different from Nb14, Nb9 targets the cryptic face of RBD, which is distinctive from the hDPP4 binding site and the Nb14 epitope, and it induces the β5-β6 loop to inflect towards a shallow groove of the RBD and dampens the accommodation of a short helix of hDPP4. The particularly striking epitopes endow the two Nbs administrate synergistically in the pseudotyped MERS-CoV assays. These results not only character unprecedented epitopes for antibody recognition but also provide promising agents for prophylaxis and therapy of MERS-CoV infection.

Extracellular vesicles (EVs) are nanovesicles containing bioactive molecules including proteins, nucleic acids and lipids that mediate intercellular and inter-organ communications, holding promise as potential therapeutics for multiple diseases. Adipose tissue (AT) serves as a dynamically distributed energy storage organ throughout the body, whose accumulation leads to obesity, a condition characterized by infiltration with abundant immune cells. Emerging evidence has illustrated that EVs secreted by AT are the novel class of adipokines that regulate the homeostasis between AT and peripheral organs. However, most of the studies focused on the investigations of EVs derived from adipocytes or adipose-derived stem cells (ADSCs), the summarization of functions in cellular and inter-organ crosstalk of EVs directly derived from adipose tissue (AT-EVs) are still limited. Here, we provide a systemic summary on the key components and functions of EVs derived from healthy adipose tissue, showing their significance on the tissue recovery and metabolic homeostasis regulation. Also, we discuss the harmful influences of EVs derived from obese adipose tissue on the distal organs. Furthermore, we elucidate the potential applications and constraints of EVs from healthy patients lipoaspirates as therapeutic agents, highlighting the potential of AT-EVs as a valuable biological material with broad prospects for future clinical use.

Abstract A central role for nature-based solution is to identify optimal management practices to address environmental challenges, including carbon sequestration and biodiversity conservation. Inorganic fertilization increases plant aboveground biomass but often causes a tradeoff with plant diversity loss. It remains unclear, however, whether organic fertilization, as a potential nature-based solution, could alter this tradeoff by increasing aboveground biomass without plant diversity loss. Here we compile data from 537 experiments on organic and inorganic fertilization across grasslands and croplands worldwide to evaluate the responses of aboveground biomass, plant diversity, and soil organic carbon (SOC). Both organic and inorganic fertilization increase aboveground biomass by 56% and 42% relative to ambient, respectively. However, only inorganic fertilization decreases plant diversity, while organic fertilization increases plant diversity in grasslands with greater soil water content. Moreover, organic fertilization increases SOC in grasslands by 19% and 15% relative to ambient and inorganic fertilization, respectively. The positive effect of organic fertilization on SOC increases with increasing mean annual temperature in grasslands, a pattern not observed in croplands. Collectively, our findings highlight organic fertilization as a potential nature-based solution that can increase two ecosystem services of grasslands, forage production, and soil carbon storage, without a tradeoff in plant diversity loss.

Abstract Neoantigens derived from somatic mutations in Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), the most frequently mutated oncogene, represent promising targets for cancer immunotherapy. Recent research highlights the potential role of human leukocyte antigen (HLA) allele A*11:01 in presenting these altered KRAS variants to the immune system. In this study, we successfully generate and identify murine T-cell receptors (TCRs) that specifically recognize KRAS8–16 G12V from three predicted high affinity peptides. By determining the structure of the tumor-specific 4TCR2 bound to KRASG12V-HLA-A*11:01, we conduct structure-based design to create and evaluate TCR variants with markedly enhanced affinity, up to 15.8-fold. This high-affinity TCR mutant, which involved only two amino acid substitutions, display minimal conformational alterations while maintaining a high degree of specificity for the KRASG12V peptide. Our research unveils the molecular mechanisms governing TCR recognition towards KRASG12V neoantigen and yields a range of affinity-enhanced TCR mutants with significant potential for immunotherapy strategies targeting tumors harboring the KRASG12V mutation.

Under the requirements of the “double carbon” goal and the new development concept of high-quality development, the coordinated promotion of pollution, carbon reduction, and high-quality development is significant in promoting the social economy’s comprehensive green transformation. The coupling and coordination degree between pollution, carbon reduction, and high-quality development of 110 cities in the Yangtze River Economic Belt from 2010 to 2021 was measured, and the modified gravity model and social network analysis were then employed to assess the spatial network characteristics, patterns, and structure evolution. The results indicated that the coupling and coordination of urban clusters in the Yangtze River Economic Belt showed an increasing pattern, and the spatial arrangement shifted from dispersed to centralized. The spatial linkage strength and potential increased, while the spatial linkage pattern was steady. The direction of spatial connectivity remained consistent, with significant central city orientation and geographical proximity. The overall network structure was characterized by increased network density and an increased number of network links within each urban cluster, while network effectiveness fluctuated and decreased. The predominance of central or developed cities characterized individual network characteristics. This study is of great significance for exploring the coordinated development of pollution reduction, carbon reduction, and high-quality development, providing a theoretical basis for implementing ecological civilization, promoting carbon neutrality, promoting regional coordinated development, and achieving green, low-carbon, and sustainable development.

Abstract Since the advent of COVID-19 vaccine, the long-term monitoring and evaluation of vaccine effectiveness worldwide has never stopped. Real-world research of the mainstream vaccines in China (BBIBP-CorV and CoronaVac) is extremely valuable as a supplement to clinical research data. Venous blood of this study was collected from 111 blood donors and from 6 volunteers, who had received 2 doses of SAR-CoV-2 vaccine. Cross-sectional study and cohort study was adopted. Venous blood of 11 COVID-19 convalescent plasma donors was collected as a positive control. The seroconversion rate of neutralizing antibodies in 111 vaccine recipients was 90.99% (101/111); The level of SAR-CoV-2 antibodies peaked around 28 days after inoculation, then fast descended followed by gentle descended until it was still detectable around 280 days later. The changes in antibody levels were similar to those of the 6 participants and those of convalescent plasma donors after infection. 5 of the 6 participants still maintained a high level of neutralizing antibodies (> 60% of the peak value) around 28 days after receiving 2 doses of vaccine; one participant had an antibody reaction that was almost always negative for 4 weeks. BBIBP-CorV and CoronaVac can produce good immune effects in most vaccinators aged 20 to 59 years in Nanjing area. Nevertheless, significant individual discrepancies of the humoral immunity are still existed.