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Abstract The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains a bottleneck for large-scale applications. We propose a shift towards a model-centric ecosystem, wherein a large atomic model (LAM), pre-trained across multiple disciplines, can be efficiently fine-tuned and distilled for various downstream tasks, thereby establishing a new framework for molecular modeling. In this study, we introduce the DPA-2 architecture as a prototype for LAMs. Pre-trained on a diverse array of chemical and materials systems using a multi-task approach, DPA-2 demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning methodologies. Our approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

Abstract Background NOD-like receptor protein 3 (NLRP3) inflammasome activation is indispensable for atherogenesis. Mitophagy has emerged as a potential strategy to counteract NLRP3 inflammasome activation triggered by impaired mitochondria. Our previous research has indicated that dihydromyricetin, a natural flavonoid, can mitigate NLRP3-mediated endothelial inflammation, suggesting its potential to treat atherosclerosis. However, the precise underlying mechanisms remain elusive. This study sought to investigate whether dihydromyricetin modulates endothelial mitophagy and inhibits NLRP3 inflammasome activation to alleviate atherogenesis, along with the specific mechanisms involved. Methods Apolipoprotein E-deficient mice on a high-fat diet were administered daily oral gavages of dihydromyricetin for 14 weeks. Blood samples were procured to determine the serum lipid profiles and quantify proinflammatory cytokine concentrations. Aortas were harvested to evaluate atherosclerotic plaque formation and NLRP3 inflammasome activation. Concurrently, in human umbilical vein endothelial cells, Western blotting, flow cytometry, and quantitative real-time PCR were employed to elucidate the mechanistic role of mitophagy in the modulation of NLRP3 inflammasome activation by dihydromyricetin. Results Dihydromyricetin administration significantly attenuated NLRP3 inflammasome activation and vascular inflammation in mice on a high-fat diet, thereby exerting a pronounced inhibitory effect on atherogenesis. Both in vivo and in vitro, dihydromyricetin treatment markedly enhanced mitophagy. This enhancement in mitophagy ameliorated the mitochondrial damage instigated by saturated fatty acids, thereby inhibiting the activation and nuclear translocation of NF-κB. Consequently, concomitant reductions in the transcript levels of NLRP3 and interleukin-1β (IL-1β), alongside decreased activation of NLRP3 inflammasome and IL-1β secretion, were discerned. Notably, the inhibitory effects of dihydromyricetin on the activation of NF-κB and subsequently the NLRP3 inflammasome were determined to be, at least in part, contingent upon its capacity to promote mitophagy. Conclusion This study suggested that dihydromyricetin may function as a modulator to promote mitophagy, which in turn mitigates NF-κB activity and subsequent NLRP3 inflammasome activation, thereby conferring protection against atherosclerosis.

Aim: This study investigated the association between participation in social activities and incident dementia among physically and socially independent older adults with or without diseases (hypertension and/or diabetes mellitus) in a Japanese age-specific cohort (the NISSIN Project). Methods: We conducted a prospective cohort study of 1,856 Japanese individuals (953 men and 903 women) aged 64/65 years. Information on medical status, demographics, and lifestyle characteristics was collected using a baseline questionnaire and health checkup (2000–2005). Incident dementia were confirmed among these received long-term care certifications using the nationally standardized dementia scale proposed by the Ministry of Health, Labor, and Welfare. A competing risk model was used to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs) for dementia incidence. We treated the censored cases of death as competing events. Results: During a median of 16.0 years of follow-up, incident dementia occurred in 332 participants. The presence of diseases and nonparticipation in social activities were associated with a significantly higher risk of incident dementia (HR 1.65; 95 % CI 1.21–2.26) after adjusting for potential confounders compared with participants without diseases and those who participated in social activities. Conclusions: In this age-specific cohort study, participants with diseases and those who did not participate in social activities were more likely to have incident dementia than those without diseases and those who participated in social activities. For older people with hypertension and/or diabetes mellitus, engaging in social activities could be a beneficial strategy for reducing the risk of developing dementia.

Objectives: This study investigated the association between depressive symptoms and the instrumental activities of daily living (IADL) decline among physically and socially independent older people according to being employed or participating in social activities in a Japanese age-specific cohort. Methods: We performed a prospective cohort study including 1,508 (716 men and 792 women) aged 64/65. Depressive symptoms were assessed at baseline (2000–2005). The change in IADL status was ascertained in the secondary survey when the participants reached 70 years of age. Multivariable odds ratios (ORs) and confidence intervals (CIs) of depressive symptoms for IADL decline were calculated using a logistic regression model adjusted for enroll year, sex, employment status, marital status, education, smoking status, alcohol consumption status, body mass index, walking status, daily sleep duration, and medical histories of cancer, cardio-cerebrovascular diseases, hypertension, and diabetes mellitus. We also formally tested for potential interaction effects by employment and participation in social activities. Results: The OR of the presence of depressive symptoms and not employed was 3.25 (95% CI 1.57–6.75), compared to participants without depressive symptoms and employed, after adjusting for potential confounders. Compared to participants without depressive symptoms and with a high frequency of participation in social activities, participants with depressive symptoms and a low frequency of participation in social activities were associated with IADL decline (OR 2.45; 95% CI 1.23–4.90). However, we observed no evidence of an interaction effect by employment and participation in social activities. Conclusions: This age-specific cohort study revealed that being employed or participating in social activities may prevent IADL decline among depressed older adults.

Abstract Polydopamine (PDA), which is derived from marine mussels, has excellent potential in early diagnosis of diseases and targeted drug delivery owing to its good biocompatibility, biodegradability, and photothermal conversion. However, when used as a solid nanoparticle, the application of traditional PDA is restricted because of the low drug-loading and encapsulation efficiencies of hydrophobic drugs. Nevertheless, the emergence of mesoporous materials broaden our horizon. Mesoporous polydopamine (MPDA) has the characteristics of a porous structure, simple preparation process, low cost, high specific surface area, high light-to-heat conversion efficiency, and excellent biocompatibility, and therefore has gained considerable interest. This review provides an overview of the preparation methods and the latest applications of MPDA-based nanodrug delivery systems (chemotherapy combined with radiotherapy, photothermal therapy combined with chemotherapy, photothermal therapy combined with immunotherapy, photothermal therapy combined with photodynamic/chemodynamic therapy, and cancer theranostics). This review is expected to shed light on the multi-strategy antitumor therapy applications of MPDA-based nanodrug delivery systems. Graphical Abstract

Abstract Background The receptor of severe respiratory syndrome coronavirus 2 (SARS-CoV-2), angiotensin-converting enzyme 2, is more abundant in kidney than in lung tissue, suggesting that kidney might be another important target organ for SARS-CoV-2. However, our understanding of kidney injury caused by Coronavirus Disease 2019 (COVID-19) is limited. This study aimed to explore the association between kidney injury and disease progression in patients with COVID-19. Methods A retrospective cohort study was designed by including 2630 patients with confirmed COVID-19 from Huoshenshan Hospital (Wuhan, China) from 1 February to 13 April 2020. Kidney function indexes and other clinical information were extracted from the electronic medical record system. Associations between kidney function indexes and disease progression were analyzed using Cox proportional-hazards regression and generalized linear mixed model. Results We found that estimated glomerular filtration rate (eGFR) and creatinine clearance (Ccr) decreased in 22.0% and 24.0% of patients with COVID-19, respectively. Proteinuria was detected in 15.0% patients and hematuria was detected in 8.1% of patients. Hematuria (HR 2.38, 95% CI 1.50–3.78), proteinuria (HR 2.16, 95% CI 1.33–3.51), elevated baseline serum creatinine (HR 2.84, 95% CI 1.92–4.21) and blood urea nitrogen (HR 3.54, 95% CI 2.36–5.31), and decrease baseline eGFR (HR 1.58, 95% CI 1.07–2.34) were found to be independent risk factors for disease progression after adjusted confounders. Generalized linear mixed model analysis showed that the dynamic trajectories of uric acid was significantly related to disease progression. Conclusion There was a high proportion of early kidney function injury in COVID-19 patients on admission. Early kidney injury could help clinicians to identify patients with poor prognosis at an early stage. Graphic abstract

Background: Although life satisfaction (LS) has been shown to predict mortality, research studying the relationship between LS and functional decline is scarce. This study examined the association between LS and functional decline across four time points in young-old Japanese adults. Methods: We analysed 1,899 community-dwelling 65-year-olds in this age-specific cohort study conducted between 2000 and 2005. The Life Satisfaction Index K was used to evaluate LS and was classified into quartiles. Functional decline was determined using the Japanese Long-Term Care Insurance (LTCI) system: 1) mild disability; 2) severe disability; 3) all-cause mortality; 4) mild or severe disability; 5) severe disability or death; 6) mild or severe disability, or death. Adjusted hazard ratios (HR) with 95% confidence intervals (CI) were calculated using the Cox proportional hazard model. The analyses were conducted in the 8th, 10th, 12th, and 14th years to assess the effect of LS on functional decline across time points. Results: The impact of LS gradually weakened over time. In the 8th year (aged 72–73), a higher LS was associated with a lower risk of mild or severe disability among the women participants (adjusted HR [95% CI] = 0.30 [0.11–0.81]). However, the effect disappeared gradually (adjusted HR [95% CI] = 0.55 [0.27–1.14]) in the 10th year (aged 74–75), 0.72 (0.41–1.26) in the 12th year (aged 76–77), and 0.68 (0.41–1.14) in the 14th year (aged 78–79). This trend continued in severe disability or death (adjusted HR [95% CI] = 0.24 [0.06–0.70], 0.31 [0.11–0.76], 0.57 [0.28–1.14], and 0.60 [0.32–1.12]) and mild or severe disability, or death (adjusted HR [95% CI] = 0.30 [0.14–0.68], 0.46 [0.24–0.87], 0.67 [0.41–1.10], and 0.65 [0.42–1.02]) in the 8th, 10th, 12th, and 14th years, respectively. No statistically significant association was found among men at any time points or in any classification of outcomes. Conclusions: Higher LS scores in 65-year-old women were associated with a lower risk for functional decline in any combination of mild disability, severe disability, or death. Additionally, the effect of LS was observed to weaken over time. Trial registration: This is not an intervention survey and does not require registration.

Abstract Background During outbreak of Coronavirus Disease 2019 (COVID-19), healthcare providers are facing critical clinical decisions based on the prognosis of patients. Decision support tools of risk stratification are needed to predict outcomes in patients with different clinical types of COVID-19. Methods This retrospective cohort study recruited 2425 patients with moderate or severe COVID-19. A logistic regression model was used to select and estimate the factors independently associated with outcomes. Simplified risk stratification score systems were constructed to predict outcomes in moderate and severe patients with COVID-19, and their performances were evaluated by discrimination and calibration. Results We constructed two risk stratification score systems, named as STPCAL (including significant factors in the prediction model: number of clinical symptoms, the maximum body temperature during hospitalization, platelet count, C-reactive protein, albumin and lactate dehydrogenase) and TRPNCLP (including maximum body temperature during hospitalization, history of respiratory diseases, platelet count, neutrophil-to-lymphocyte ratio, creatinine, lactate dehydrogenase, and prothrombin time), to predict hospitalization duration for moderate patients and disease progression for severe patients, respectively. According to STPCAL score, moderate patients were classified into three risk categories for a longer hospital duration: low (Score 0–1, median = 8 days, with less than 20.0% probabilities), intermediate (Score 2–6, median = 13 days, with 30.0–78.9% probabilities), high (Score 7–9, median = 19 days, with more than 86.5% probabilities). Severe patients were stratified into three risk categories for disease progression: low risk (Score 0–5, with less than 12.7% probabilities), intermediate risk (Score 6–11, with 18.6–69.1% probabilities), and high risk (Score 12–16, with more than 77.9% probabilities) by TRPNCLP score. The two risk scores performed well with good discrimination and calibration. Conclusions Two easy-to-use risk stratification score systems were built to predict the outcomes in COVID-19 patients with different clinical types. Identifying high risk patients with longer stay or poor prognosis could assist healthcare providers in triaging patients when allocating limited healthcare during COVID-19 outbreak.

Background: The prevalence of allergy and other common chronic diseases is higher in developed than developing countries, and higher in urban than rural regions. Urbanization through its modification of environmental microbiomes may play a predominant role in the development of these conditions. However, no studies have been conducted to compare the microbiome in house dust among areas with different urbanization levels. Methods: House dust from Xinxiang rural area (XR, n = 74), Xinxiang urban area (XU, n = 33), and Zhengzhou urban area (ZU, n = 32) in central China, and from Australia (AU, n = 58 [with pets AUP, n = 15, without pets AUNP, n = 43]) were collected during a summer season in China and Australia. High-throughput sequencing of 16S rDNA was employed to profile house dust bacterial communities. Results: Settled dust collected in China was dominant with 2 bacterial phyla: Proteobacteria and Actinobacteria, while floor dust collected in Australia had a higher proportion of phylum Proteobacteria, Firmicutes, and Actinobacteria. XR dust samples presented higher bacterial richness and diversity compared with XU or ZU samples. Urbanization level (r2 = 0.741 P 0.5) between urbanization level and bacterial genera Streptococcus, Bartonella, Staphylococcus, Pseudomonas, Acinetobacter, Bacteroides, Corynebacterium_1, and Enhydrobacter and a negative correlation (r coefficient

Abstract Spinal cord injury (SCI) has no effective treatment modalities. It faces a significant global therapeutical challenge, given its features of poor axon regeneration, progressive local inflammation, and inefficient systemic drug delivery due to the blood–spinal cord barrier (BSCB). To address these challenges, a new nano complex that achieves targeted drug delivery to the damaged spinal cord is proposed, which contains a mesoporous silica nanoparticle core loaded with microRNA and a cloaking layer of human umbilical cord mesenchymal stem cell membrane modified with rabies virus glycoprotein (RVG). The nano complex more readily crosses the damaged BSCB with its exosome‐resembling properties, including appropriate size and a low‐immunogenic cell membrane disguise and accumulates in the injury center because of RVG, where it releases abundant microRNAs to elicit axon sprouting and rehabilitate the inflammatory microenvironment. Culturing with nano complexes promotes axonal growth in neurons and M2 polarization in microglia. Furthermore, it showed that SCI mice treated with this nano complex by tail vein injection display significant improvement in axon regrowth, microenvironment regulation, and functional restoration. The efficacy and biocompatibility of the targeted delivery of microRNA by nano complexes demonstrate their immense potential as a noninvasive treatment for SCI.

In addressing the challenges of trajectory prediction in multi-ship interaction scenarios and aiming to improve the accuracy of multi-ship trajectory prediction, this paper proposes a multi-ship trajectory prediction model, GL-STGCNN. The GL-STGCNN model employs a ship interaction adjacency matrix extraction module to obtain a more reasonable ship interaction adjacency matrix. Additionally, after obtaining the distribution of predicted trajectories using the model, a model predictive control trajectory correction method is introduced to enhance the accuracy and reasonability of the predicted trajectories. Through quantitative analysis of different datasets, it was observed that GL-STGCNN outperforms previous prediction models with a 31.8% improvement in the average displacement error metric and a 16.8% improvement in the final displacement error metric. Furthermore, trajectory correction through model predictive control shows a performance boost of 44.5% based on the initial predicted trajectory distribution. While GL-STGCNN excels in multi-ship interaction trajectory prediction by reasonably modeling ship interaction adjacency matrices and employing trajectory correction, its performance may vary in different datasets and ship motion patterns. Future work could focus on adapting the model’s ship interaction adjacency matrix modeling to diverse environmental scenarios for enhanced performance.

Image recognition is vital for intelligent ships’ autonomous navigation. However, traditional methods often fail to accurately identify maritime objects’ spatial positions, especially under electromagnetic silence. We introduce the StereoYOLO method, an enhanced stereo vision-based object recognition and localization approach that serves autonomous vessels using only image sensors. It is specifically refined for maritime object recognition and localization scenarios through the integration of convolutional and coordinated attention modules. The method uses stereo cameras to identify and locate maritime objects in images and calculate their relative positions using stereo vision algorithms. Experimental results indicate that the StereoYOLO algorithm boosts the mean Average Precision at IoU threshold of 0.5 (mAP50) in object recognition by 5.23%. Furthermore, the variation in range measurement due to target angle changes is reduced by 6.12%. Additionally, upon measuring the distance to targets at varying ranges, the algorithm achieves an average positioning error of 5.73%, meeting the accuracy and robustness criteria for maritime object collision avoidance on experimental platform ships.