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Abstract Chronic disease risk prediction based on electronic health record (EHR) is an important research direction of Internet healthcare. Current studies mainly focused on developing well-designed deep learning models to predict the disease risk based on large-scale and high-quality longitudinal EHR data. However, in real-world scenarios, people’s medical habits and low prevalence of diseases often lead to few-shot and imbalanced longitudinal EHR data. This has become an urgent challenge for chronic disease risk prediction based on EHR. Aiming at this challenge, this study combines EHR based pre-training and deep reinforcement learning to develop a novel chronic disease risk prediction model called CDR-Detector. The model adopts the Q-learning architecture with a custom reward function. In order to improve the few-shot learning ability of model, a self-adaptive EHR based pre-training model with two new pre-training tasks is developed to mine valuable dependencies from single-visit EHR data. In order to solve the problem of data imbalance, a dual experience replay strategy is realized to help the model select representative data samples and accelerate model convergence on the imbalanced EHR data. A group of experiments have been conducted on real personal physical examination data. Experimental results show that, compared with the existing state-of-art methods, the proposed CDR-Detector has better accuracy and robustness on the few-shot and imbalanced EHR data.

Abstract Background To clarify the fat attenuation index (FAI) change trend of peri-saphenous vein graft (SVG) and determine the association between FAI and graft disease progression based on CCTA images. Methods Patients with venous coronary artery bypass grafts (CABGs) were consecutively enrolled in this retrospective study. In study 1, 72 patients who had undergone 1, 3, and 5 years of CCTA examinations without graft occlusion were recruited, and generalized estimation equation was used to analyze the peri-SVG FAI change trend over time. In study 2, 42 patients with graft disease progression and 84 patients as controls were propensity score-matched. Generalized linear mixed model and continuous net reclassification improvement (NRI) were used for assessing the associations with graft disease progression. Multivariable Cox regression analysis was used for assessing risk factors predicting cardiac events. Results In study 1, both the FAI of proximal right coronary artery and SVG decreased over time. In study 2, the 1-year CTA-derived FAI of grafts and graft anastomosis were independent indicators of graft disease progression at the 3-year CCTA follow-up (graft: odds ratio [OR] = 1.106; 95% confidence interval [CI] = 1.030–1.188, P = 0.006; graft anastomosis: OR = 1.170, 95% CI = 1.091–1.254, P

The impact of geopolitical risks (GPR) on enterprises is significant, yet the existing literature lacks a comprehensive understanding of how GPR affects environmental, social, and governance (ESG) performance. This study addresses this gap by analysing data from Chinese enterprises over the period 2009 to 2021. It empirically examines the impact of GPR on ESG performance and explores the underlying mechanisms. Specifically, the analysis considers the roles of investor attention and government subsidies as moderating factors. The results indicate that GPR inhibits corporate ESG performance. State-owned enterprises are found to mitigate these adverse effects, while privately-owned enterprises tend to exacerbate them. Mechanism tests reveal that GPR negatively impacts ESG performance by increasing financing constraints and reducing financial performance. Furthermore, increased investor attention and government subsidies can alleviate the negative effects of GPR on ESG performance. These findings offer valuable insights for organisations, governments, and stakeholders, enabling them to better respond to GPR and achieve sustainable development.

Abstract Current radiotherapy (RT) lacks the ability to accurately discriminate between tumor and healthy tissues, resulting in significant radiation‐induced damage for patients. Therefore, there is an urgent need for precise RT techniques that can optimize tumor control while minimizing adverse effects on surrounding healthy tissues. In this study, we developed a nanodrug (AuNR@Peptide) composed of furin‐responsive RVRR peptide‐conjugated AuNRs, which integrates an activatable probe and a radiosensitizer into a single system for accurate tumor localization, enabling image‐guided precision RT. Upon reaching the tumor site after intravenous administration, proteolytic cleavage of RVRR substrates on AuNR@Peptide by biomarker triggers aggregation of gold nanorods (AuNRs) into larger aggregates, leading to activation of near‐infrared (NIR)‐II photoacoustic (PA) signals to precisely localize the tumor and enhance tumor retention by preventing migration and backflow of AuNRs. This significantly amplifies radiosensitivity efficiency. The peak time point at which the NIR‐II PA signal was observed at the tumor site after injection serves as a reference for initiating RT, demonstrating substantial improvement in tumor RT through investigations related to radiosensitization mechanisms. The integration of imaging and therapy in this study offers a promising image‐guided therapeutic modality for tumors.

Abstract Our study examines the relationship between intellectual property rights protection (IPRP) and carbon emissions (CE) using an unbalanced panel data set from 116 countries spanning 2008–2020. The analysis reveals a positive relationship between IPRP and CE. Mechanism tests and nonlinear analysis further elucidate this relationship. The mediation effect results indicated that IPRP indirectly fostered CE growth by inhibiting energy structure’s improvement, demonstrating that IPRP exacerbated the dependence on traditional high-carbon energy sources, hindering the transition to cleaner, more efficient energy systems. The analysis also revealed that IPRP indirectly promoted the increase of CE by promoting technological progress and economic growth. The moderation effect results suggest that political stability could mitigate the positive impact of IPRP on CE. Furthermore, the analysis reveals an inverted U-shaped relationship between IPRP and CE, indicating that while IPRP promotes an increase in CE in the initial stages, its intensification suppresses CE growth beyond a turning point. Hence, our study provides new theoretical and empirical evidence to understand the complex relationship between IPRP and CE. It also offers policy recommendations for effectively integrating global carbon reduction efforts with intellectual property policies.

Abstract The development of rural e-commerce in China is viewed as an opportunity to increase rural income. Using panel data from 592 national-level key poverty-stricken (NLKPS) counties from 2014 to 2020, we confirm that the National Rural E-commerce Comprehensive Demonstration Project (NRECDP), launched by the Chinese government, delivers significant rural income growth for selected counties by providing financial support. Digital inclusive finance has facilitated rural e-commerce development, thereby promoting rural income. Our study uses the endogeneity switching regression (ESR) model to address self-selection bias and finds that NRECDP participation increases rural income by ~12.97%. The determinants of participation in the NRECDP include levels of economic development, e-commerce development, infrastructure development, industry structure, and digital inclusive finance. Additionally, the determinants of rural income include education levels and population density. Moreover, our heterogeneity analysis reveals that the rural income growth effect of NRECDP involvement is more significant for NLKPS counties in non-ethnic regions, central regions, higher industry structures, and the three regions and three prefectures. Additionally, entrepreneurship serves as a potential channel linking NRECDP implementation and rural income growth.

This study investigates the impact of geopolitical risk (GPR) on green international technology spillovers through foreign direct investment (FDI) and import channels. The research aims to understand how GPR influences the transfer of green technologies, which are crucial for sustainable development, particularly in developing countries. Utilizing data from 30 Chinese provinces from 2003 to 2019, our findings indicate that increased GPR significantly hinders green technology spillovers through both FDI and imports. Additionally, the research demonstrates that advancements in local green technology levels (GTL), marketization (Mark), and intellectual property rights protection (IPRP) can mitigate the adverse effects of GPR. These results underscore the critical importance of political stability and robust internal mechanisms in promoting international technological exchanges. This study contributes to the literature on the intersection of political risks and technological advancement and provides actionable insights for policymakers to enhance resilience against geopolitical uncertainties, thereby fostering sustainable economic development.

Multimodal imaging, which combines the strengths of two or more imaging modalities to provide complementary anatomical and molecular information, has emerged as a robust technology for enhancing diagnostic sensitivity and accuracy, as well as improving treatment monitoring. Moreover, the application of multimodal imaging in guiding precision tumor treatment can prevent under- or over-treatment, thereby maximizing the benefits for tumor patients. In recent years, several intriguing magneto-optical nanosystems with both magnetic and optical properties have been developed, leading to significant breakthroughs in the field of multimodal imaging and image-guided tumor therapy. These advancements pave the way for precise tumor medicine. This review summarizes various types of magneto-optical nanosystems developed recently and describes their applications as probes for multimodal imaging and agents for image-guided therapeutic interventions. Finally, future research and development prospects of magneto-optical nanosystems are discussed along with an outlook on their further applications in the biomedical field.

Abstract Vaccine is one of the most promising strategies for cancer immunotherapy; however, there are no therapeutic cancer vaccine achieving significant clinical efficacy till now. The main limiting factors include the immune suppression and escape mechanisms developed by tumor and not enough capacity of vaccines to induce a vigorous anti-tumor immunity. This study aimed to develop a strategy of membrane-based biomimetic nanovaccine and investigate the immunological outcomes of utilizing the unique immunostimulatory mechanisms derived of immunogenic cell death (ICD) and of fulfilling a simultaneous nanoscale delivery of a highlighted tumor antigen and broad membrane-associated tumor antigens in the vaccine design. TC-1 tumor cells were treated in vitro with a mixture of mitoxantrone and curcumin for ICD induction, and then chitosan (CS)-coated polylactic co-glycolic acid (PLGA) nanoparticles loaded with HPV16 E744-62 peptides were decorated with the prepared ICD tumor cell membrane (IM); further, the IM-decorated nanoparticles along with adenosine triphosphate (ATP) were embedded with sodium alginate (ALG) hydrogel, And then, the immunological features and therapeutic potency were evaluated in vitro and in vivo. The nanovaccine significantly stimulated the migration, antigen uptake, and maturation of DCs in vitro, improved antigen lysosome escape, and promoted the retention at injection site and accumulation in LNs of the tumor antigen in vivo. In a subcutaneously grafted TC-1 tumor model, the therapeutic immunization of nanovaccine elicited a dramatical antitumor immunity. This study provides a strategy for the development of tumor vaccines. Graphical Abstract

Carbon dioxide emissions from the transport sector make a significant contribution to global greenhouse gases, and understanding the factors that influence these emissions is beneficial for devising effective emission reduction policies. Oil prices are an important influencing factor since the fuel used in the transport sector is primarily based on oil, and fluctuations in oil prices directly impact the sector’s CO2 emissions. Additionally, environmental policies, as a key means of controlling CO2 emissions, can affect the relationship between oil prices and CO2 emissions in the transport sector. Therefore, this study aims to examine the impact of oil prices on CO2 emissions in the transport sector and explore the nonlinear role of environmental policy stringency in this relationship. Based on data from 27 OECD member countries and 6 non-member countries from 1990 to 2019, we used the environmental policy stringency index as a threshold variable to construct a panel threshold regression model. The analysis results indicate a double-threshold effect: when the environmental policy stringency index is low, the impact of oil prices on CO2 emissions in the transport sector is not significant. However, when the index reaches the first threshold, the impact of oil prices significantly increases; upon reaching the second threshold, the effect is further intensified. This paper also analyzes the three subindicators—market-based policies, non-market-based policies, and technology support policies—to clarify the distinct impact mechanisms of different types of environmental policies. Finally, based on the research findings, we propose policy recommendations to achieve carbon dioxide emission reduction targets in the transport sector.

Immunoglobulin (Ig) isotype switching in multiple myeloma (MM) is a rare form of clonal evolution. The aim of this study was to investigate the clinical features and prognostic significance of Ig isotype switching by observing Ig transformation in patients with relapse. A retrospective analysis was performed on 506 patients with newly diagnosed MM who were treated at our hospital from February 2005 to February 2020. The patients who experienced relapse were divided into the following four groups according to Ig phenotype: original paraprotein, complete isotype switching, light chain escape (LCE),and non-secretory clinical relapse. For comparative purposes with the original paraprotein group, the last three groups were pooled as the transformation group. Among the 506 included patients, 376 (74.3%) relapsed. Among them, 13/376 (3.5%) patients exhibited Ig isotype switching, including 3 with complete isotype switching, 3 with LCE, and 7 with non-secretory clinical relapse. Eleven remained sensitive to therapy, exhibiting at least a partial response. Seven patients survived for at least 20 months after relapse. The median overall survival time of the LCE, clinical relapse, and complete isotype switching groups were 6, 20, and 76 months, respectively, after recurrence. The clinical manifestations and Ig phenotypes of MM recurrence were different from those at the initial diagnosis in the 13 patients exhibiting Ig isotype switching. These differences vividly conveyed the heterogeneity of the clonal populations and provides direct clinical evidence for MM clonal evolution.

Background: Autologous hematopoietic stem cell (HSC) transplantation remains the recommended treatment for eligible patients with multiple myeloma (MM). Increasing the number of transplanted CD34+ cells shorten the time to hematopoietic reconstitution and increases the overall survival of patients. With the harvest of a sufficient CD34+ cell number being crucial, this study aimed to predict the factors that affect stem cell collection. Methods: We conducted a retrospective study of 110 patients who were newly diagnosed with MM and underwent autologous HSC collection at Beijing Jishuitan Hospital between March 2016 and July 2022. Multiple factors were analyzed using the Mann–Whitney U tests for between-group comparisons. Differences were considered statistically significant at P ​

Abstract Background Medication recommendation based on electronic medical record (EMR) is a research hot spot in smart healthcare. For developing computational medication recommendation methods based on EMR, an important challenge is the lack of a large number of longitudinal EMR data with time correlation. Faced with this challenge, this paper proposes a new EMR-based medication recommendation model called MR-KPA, which combines knowledge-enhanced pre-training with the deep adversarial network to improve medication recommendation from both feature representation and the fine-tuning process. Firstly, a knowledge-enhanced pre-training visit model is proposed to realize domain knowledge-based external feature fusion and pre-training-based internal feature mining for improving the feature representation. Secondly, a medication recommendation model based on the deep adversarial network is developed to optimize the fine-tuning process of pre-training visit model and alleviate over-fitting of model caused by the task gap between pre-training and recommendation. Result The experimental results on EMRs from medical and health institutions in Hainan Province, China show that the proposed MR-KPA model can effectively improve the accuracy of medication recommendation on small-scale longitudinal EMR data compared with existing representative methods. Conclusion The advantages of the proposed MR-KPA are mainly attributed to knowledge enhancement based on ontology embedding, the pre-training visit model and adversarial training. Each of these three optimizations is very effective for improving the capability of medication recommendation on small-scale longitudinal EMR data, and the pre-training visit model has the most significant improvement effect. These three optimizations are also complementary, and their integration makes the proposed MR-KPA model achieve the best recommendation effect.

Investigating intraspecific trait variability is crucial for understanding plant adaptation to various environments, yet research on lithophytic mosses in extreme environments remains scarce. This study focuses on Indusiella thianschanica Broth. Hal., a unique lithophytic moss species in the extreme environments of the Tibetan Plateau, aiming to uncover its adaptation and response mechanisms to environmental changes. Specimens were collected from 26 sites across elevations ranging from 3642 m to 5528 m, and the relationships between 23 morphological traits and 15 environmental factors were analyzed. Results indicated that coefficients of variation (CV) ranged from 5.91% to 36.11%, with gametophyte height (GH) and basal cell transverse wall thickness (STW) showing the highest and lowest variations, respectively. Temperature, elevation, and potential evapo-transpiration (PET) emerged as primary environmental drivers. Leaf traits, especially those of the leaf sheath, exhibited a more pronounced response to the environment. The traits exhibited apparent covariation in response to environmental challenges and indicated flexible adaptive strategies. This study revealed the adaptation and response patterns of different morphological traits of I. thianschanica to environmental changes on the Tibetan Plateau, emphasizing the significant effect of temperature on trait variation. Our findings deepen the understanding of the ecology and adaptive strategies of lithophytic mosses.

Postharvest ripening is correlated to the quality and shelf life of European pear fruit. In this study, the effects of peppermint extract on fruit phenotype, related physiological activities, and aroma components during postharvest ripening of the European pear variety ‘Packham’s Triumph’ were examined. Fruit treated with 2.0 g L−1 peppermint extract for 12 h showed delayed softening by 4 d compared with that of the untreated control group. The peak values of ethylene and respiratory rate in fruit were reduced to a certain extent after peppermint extract treatment; however, the peppermint extract did not delay the occurrence of the respiratory climacteric peak. Peppermint extract treatment also did not significantly increase the content of the characteristic peppermint aroma in pear fruit. Further, widely targeted metabolome analysis revealed 298 significantly different metabolites, with flavonoids (40%) and lipid compounds (15%) accounting for the highest proportion on the first day after treatment. The Kyoto Encyclopedia of Genes and Genomes pathway result showed significant enrichment in the metabolic pathways of biosynthesis of flavonoid, isoflavonoid, flavone and flavonol, linoleic acid, and alpha-linolenic acid metabolism following peppermint extract treatment. The combined analysis of transcriptome and metabolome data showed significant enrichment in linoleic acid metabolism and alpha-linolenic acid metabolism on the first, third, and fifth days after peppermint extract treatment. This study indicates that peppermint extract mainly affects the pear fruit softening process in the early stage after treatment.

ObjectiveThis pilot study aimed to assess the practicability and effectiveness of percutaneous nephrolithotomy (PCNL) with vacuum-assisted nephrostomy sheaths for patients under modified local anesthesia (m-LA).MethodsPCNL with a vacuum-assisted nephrostomy sheath under m-LA was performed in 83 patients between November 2020 and May 2021. An 18F or 20F ClearPetra Nephrostomy Sheath connected vacuum aspiration was used in surgery to keep low pressure in the renal pelvis. For LA, lidocaine and ropivacaine hydrochloride were 1:1 mixed and instilled under ultrasound guidance through the percutaneous nephrolithotomy channel directed toward the design calix. Demographic characteristics, stone characteristics, visual analogue scale (VAS) score, vital signs, operation time, complications, and stone clear rate were recorded and analyzed.ResultsAll operations were completed. The mean VAS score was 3.9 ± 1.0. The mean operation time was 55.1 ± 23.6 min. The changes for systolic blood pressure, diastolic blood pressure, and heart rate were 3 ± 21 mmHg, 1 ± 14 mmHg, and −6 ± 14 beats/min, respectively. The change for hemoglobin was −10.7 ± 10.9 g/L. The change for C-reactive protein was 5.39 ± 43.1 mg/L. The total stone-free rate was 69.9% (93.8% for simple stones and 54.9% for complex stones).ConclusionPerforming PCNL with vacuum-assisted nephrostomy sheaths under modified local anesthesia under ultrasound guidance was found to be strongly practical and effective.

Brain ischemia has been associated with deficits in neural oscillations. Here in an animal model, the authors show that modulation of low-gamma oscillations using a light flicker can restore low gamma oscillations and protect ischemic neurons.

A major challenge in extracting high-quality DNA from bryophytes is the treatment of bryophyte material in the field. The existing and commonly used treatment methods in the field have several shortcomings. Natural drying methods can lead to DNA breaks. In addition, it is highly cumbersome to carry large quantities of silica gel in the field due to its weight and high risk of contamination among samples. In this study, we explored more convenient drying methods to treat bryophyte specimens and promote more efficient DNA recovery. The quantity and quality of genomic DNA extracted from every bryophyte species using different drying methods, including hot-air drying methods (150°C, 80°C, and 40°C), natural drying method, and silica gel drying method, were measured. Spectrophotometry, electrophoresis, and PCR amplification were performed to assess the effects of different drying methods. The results of total DNA purity, total DNA concentration, PCR success, and OD 260/230 ratios suggested that the hot-air drying (40–80°C) was the best method. The morphological comparison revealed that hot-air drying at 40°C and 80°C exerted no significant adverse effects on plant morphology and taxonomic studies. Thus, this method prevents rapid DNA degradation and silica gel pollution and saves the workforce from carrying large amounts of silica gel to the field. Several inexpensive devices, such as portable hairdryers, fan heaters, and electric blankets, are available that can be easily carried to the field for drying molecular specimens.

The costs and benefits of group living are not evenly distributed among individuals that occupy different spatial positions within a group (central or peripheral). However, the definitions of central and peripheral positions may artificially mask the true dynamics of cost and benefit of individuals. Using wintering foraging Greater White-fronted Geese (Anser albifrons) flocks as our study system, we measured individual spatial position within a flock as distance to the flock edge. First, we tested the effects of distance to edge on the antipredation cost and foraging benefit of individual goose using generalized linear mixed models (GLMMs). Flock size and number of neighbors and their interactions with distance to edge were included as fixed effects in GLMMs. Then we used piecewise regression to determine the threshold value of distance to edge to classify central and peripheral individuals. Our results indicated distance to edge significantly affected percent of time spent on vigilance (vigilance time), percent of time spent on foraging (foraging time) and intake rate (pecks/min), whereas other factors had no effects. We found that the critical distance that predicted changes in behavior was around 2.5 ​m. Birds 2.5 ​m or less from the edge of the group were more vigilant, and had less efficient foraging than more central individuals. Behavioral differences between central and peripheral individuals were more easily detected when the birds were classified by the method introduced in this study than by the traditional minimum convex polygon method. Our research provides researchers a dichotomous classification scheme that places individuals into peripheral and central positions from an individual's perspective.

Container shipping drives the development of international trade, yet previous studies have not fully appreciated the possible bidirectional causal relationship between container freight rates and international trade. In the context of the “twenty-first Century Maritime Silk Road,” we use data on export container freight rates and import/export data from Shanghai to ASEAN-6 countries (Singapore, Vietnam, Thailand, Philippines, Malaysia, and Indonesia) from February 2017 to January 2020 and apply a panel VAR to explore the relationship between maritime transport costs and international trade in the container shipping market. We use the freight rate data are from the Southeast Asia Freight Index, which is used for the first time in an empirical study. The quality and reliability of the freight rate data allow this paper to better identify causal relationships. The results of the panel Granger causality test and the orthogonal impulse response function suggest a bidirectional causal relationship between freight rates and export trade; to further explain, an increase in export trade lowers export freight rates, but an increase in export freight rates hinders export trade, and a growth in import trade unidirectionally raises export freight rates. We believe that international trade may impact freight rates through economies of scale and trade imbalances.

Acute myeloid leukemia (AML), a malignant disorder of hemopoietic stem cells. AML can escape immunosurveillance of natural killer (NK) by gene mutation, fusions, and epigenetic modification, while the mechanism is not clearly understood. Here we show that the expression of Intercellular adhesion molecule‐1 (ICAM‐1, CD54) is silenced in AML cells. Decitabine could upregulate ICAM-1 expression, which contributes to the NK-AML cell conjugates and helps NK cells kill AML cells. We also show that ICAM-1 high expression can reverse the AML immune evasion and activate NK cells function in vivo. This study suggests that a combination of the hypomethylating agent and NK cell infusion could be a new strategy to cure AML.

T cell immunoglobulin and mucin protein 3 (Tim-3) is an immune checkpoint and plays a vital role in immune responses during acute myeloid leukemia (AML). Targeting Tim-3 kills two birds with one stone by balancing the immune system and eliminating leukemia stem cells (LSCs) in AML. These functions make Tim-3 a potential target for curing AML. This review mainly discusses the roles of Tim-3 in the immune system in AML and as an AML LSC marker, which sheds new light on the role of Tim-3 in AML immunotherapy.

Completeness are comprehensive evaluation of the development status of irrigated areas. The study of their main influencing factors can provide strong data support for the high-quality development of irrigated areas. The paper choose the data during 2005 to 2014 of Sanyizhai Irrigation Area as analysis samples, clear different key factors affecting the evaluation target, in which six factors equal, according to different evaluation subjects and goals, the same impact factor of direct effect and indirect effect, decision coefficient and significant contribution to total R2. For the comprehensive completeness of Yellow River Sanyizhai Irrigation Area, the channel length is the most important influencing factor. The actual irrigation area, mechanism setting and channel lining rate have a significant influence on the comprehensive completeness evaluation of Yellow River Sanyizhai Irrigation Area, while the direct effect of the actual water amount is the least. Compared with the simple correlation coefficient and regression analysis method, the path analysis method can accurately calculate the direct and indirect effects of the independent variables on the dependent variables, which has the advantages of intuitive, scientific and reasonable. According to the analysis results, it can make clear the direction of efforts for the upgrading and transformation of the irrigation area and the development of high quality.

Consider a symmetric multivariate Gaussian source with ℓ components, which are corrupted by independent and identically distributed Gaussian noises; these noisy components are compressed at a certain rate, and the compressed version is leveraged to reconstruct the source subject to a mean squared error distortion constraint. The rate-distortion analysis is performed for two scenarios: centralized encoding (where the noisy source components are jointly compressed) and distributed encoding (where the noisy source components are separately compressed). It is shown, among other things, that the gap between the rate-distortion functions associated with these two scenarios admits a simple characterization in the large ℓ limit.