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Introduction: This study aimed to identify whether interleukin-6 (IL-6) is better than C-reactive protein (CRP) for the prediction of severe acute pancreatitis (SAP), infected pancreatic necrosis (IPN), and mortality.Methods: Sixty-seven patients with acute pancreatitis (AP) who were hospitalized within 48 h of onset and received serum CRP and IL-6 tests from September 2018 to September 2019 were included. Spearman’s correlation was performed to assess their associations with severity. The areas under the curve (AUCs) for the prediction of SAP, organ failure, pancreatic necrosis, IPN, and mortality were estimated using receiver operating characteristic curves.Result: Serum CRP and IL-6 levels were significantly positively correlated with the severity of AP (p < 0.05). The AUC for the prediction of SAP based on the CRP level was 0.78 (95% CI, 0.66–0.89) and that based on the IL-6 level was 0.69 (95% CI, 0.56–0.82). For the prediction of organ failure and pancreatic necrosis, CRP was more accurate than IL-6 (AUC 0.80 vs. 0.72 and 0.75 vs. 0.68, respectively). However, CRP was less accurate than IL-6 for predicting mortality and IPN (AUC 0.70 vs. 0.75 and 0.65 vs. 0.81, respectively). Systemic inflammatory response syndrome plus CRP was more accurate than systemic inflammatory response syndrome plus IL-6 (AUC 0.79 vs. 0.72) for the prediction of SAP.Conclusions: IL-6 was more accurate than CRP for predicting mortality and IPN in patients with AP.

Vehicle platooning can significantly increase throughput of transportation, while the impairment of communication may affect the control performance of vehicle platooning. Communication delays are inevitable in the process of driving, which will cause the instability of the platoon. Moreover, the transmission power level between vehicles is finite, resulting in a limited communication range. A nonlinear control algorithm is proposed where the car-following interactions between vehicles are considered. First, a third-order heterogeneous dynamic model is established for vehicles in the platoon. The control gains and parameters are heterogeneous. Then considering the constant time headway spacing policy and the gap supplement, conditions of the control gains for maintaining the internal stability of the platoon are obtained. Second, with time-varying communication delays taken into account, the allowed upper bound of communication delays is derived. Third, given the ability of each vehicle to receive information from multiple predecessors and followers, conditions of string stability are obtained, where the communication range is limited. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed controller.

Smart agriculture is rapidly evolving in response to growing global demands for food security and sustainable resource management. Cloud–edge–device collaborative computing has emerged as a transformative paradigm, addressing the limitations of traditional centralized architectures by enabling distributed intelligence, real-time processing, and adaptive decision-making. This review provides a comprehensive overview of the architectures, technical characteristics, and application scenarios of cloud–edge–device collaboration in agriculture. Key domains covered include environmental monitoring, intelligent irrigation, UAV–machinery coordination, livestock health management, and pest and disease control. Major challenges such as device heterogeneity, data consistency, resource constraints, and privacy concerns are identified and discussed. Furthermore, six critical research directions are outlined, including intelligent scheduling algorithms, lightweight edge AI, hierarchical data fusion, federated learning, interoperability frameworks, and digital twin technologies. This review aims to serve as a practical reference and theoretical foundation for advancing the design and implementation of next-generation smart agriculture systems.

Genetic analyses have linked microRNA-137 (MIR137) to neuropsychiatric disorders, including schizophrenia and autism spectrum disorder. miR-137 plays important roles in neurogenesis and neuronal maturation, but the impact of miR-137 loss-of-function in vivo remains unclear. Here we show the complete loss of miR-137 in the mouse germline knockout or nervous system knockout (cKO) leads to postnatal lethality, while heterozygous germline knockout and cKO mice remain viable. Partial loss of miR-137 in heterozygous cKO mice results in dysregulated synaptic plasticity, repetitive behavior, and impaired learning and social behavior. Transcriptomic and proteomic analyses revealed that the miR-137 mRNA target, phosphodiesterase 10a (Pde10a), is elevated in heterozygous knockout mice. Treatment with the Pde10a inhibitor papaverine or knockdown of Pde10a ameliorates the deficits observed in the heterozygous cKO mice. Collectively, our results suggest that MIR137 plays essential roles in postnatal neurodevelopment and that dysregulation of miR-137 potentially contributes to neuropsychiatric disorders in humans.

A long-standing question in the field of embryogenesis is how the zygotic genome is precisely activated by maternal factors, allowing normal early embryonic development. We have previously shown that N6-methyladenine (6mA) DNA modification is highly dynamic in early Drosophila embryos and forms an epigenetic mark. However, little is known about how 6mA-formed epigenetic information is decoded. Here we report that the Fox-family protein Jumu binds 6mA-marked DNA and acts as a maternal factor to regulate the maternal-to-zygotic transition. We find that zelda encoding the pioneer factor Zelda is marked by 6mA. Our genetic assays suggest that Jumu controls the proper zygotic genome activation (ZGA) in early embryos, at least in part, by regulating zelda expression. Thus, our findings not only support that the 6mA-formed epigenetic marks can be read by specific transcription factors, but also uncover a mechanism by which the Jumu regulates ZGA partially through Zelda in early embryos. N6-methyladenine (6mA) DNA modification is a dynamic epigenetic mark in Drosophila embryos, but how 6mA is decoded is unclear. Here, the authors show that the protein Jumu binds 6mA-marked DNA to regulate the maternal-to-zygotic transition, partly through regulation the expression of the 6mA marked pioneer factor zelda.

Development in economics and social society has led to rapid growth in electricity demand. Accurate residential electricity load forecasting is helpful for the transformation of residential energy consumption structure and can also curb global climate warming. This paper proposes a hybrid residential short-term load forecasting framework (DCNN-LSTM-AE-AM) based on deep learning, which combines dilated convolutional neural network (DCNN), long short-term memory network (LSTM), autoencoder (AE), and attention mechanism (AM) to improve the prediction results. First, we design a T-nearest neighbors (TNN) algorithm to preprocess the original data. Further, a DCNN is introduced to extract the long-term feature. Secondly, we combine the LSTM with the AE (LSTM-AE) to learn the sequence features hidden in the extracted features and decode them into output features. Finally, the AM is further introduced to extract and fuse the high-level stage features to achieve the prediction results. Experiments on two real-world datasets show that the proposed method is good at capturing the oscillation characteristics of low-load data and outperforms other methods.

Pediatric primary immune thrombocytopenia (ITP) is an acquired autoimmune disease that can be partially restored by glucocorticoids. TCRαβ CD4 CD8 double negative T cells (TCRαβ DNT) has been linked to the pathophysiology of ITP; however, the role of TCRαβ DNT in response to high-dose dexamethasone (HD-DXM) is unclear. In this study, we aimed to explore the alteration in TCRαβ DNT in ITP and the effect of HD-DXM on this subset. Pediatric patients (aged <18 years) newly diagnosed with ITP were recruited for this retrospective study. Th1, Th17, Treg, and TCRαβ DNT levels were measured by flow cytometry using specific antibodies. All patients received HD-DXM treatment and underwent periodic outpatient follow-up for 2-6 months. Patients were divided into the overall response (OR) and no response (NR) groups according to their responses to HD-DXM treatment. We enrolled 130 pediatric patients with ITP (OR, 95 cases; NR, 35 cases) and 50 age- and sex-matched healthy controls. Compared with Th17-to Treg, Th17, and Th1, univariate analysis identified that the proportion of TCRαβ DNT at baseline was more effective in predicting the response to HD-DXM ( <0.05). A significantly increased frequency of TCRαβ DNT was found in patients with ITP compared to healthy controls (percentage of T cells: 1.31% vs. 1.00%, <0.0001; percentage of lymphocytes: 0.76% vs. 0.68%, =0.010). Patients in the NR group had a higher percentage of TCRαβ DNT than the OR at the initial diagnosis (TCRαβ DNT/T: 1.52% vs. 1.30%, <0.01; TCRαβ DNT/Lym: 0.84% vs. 0.72%, <0.01). After treatment with HD-DXM, the elevated TCRαβ DNT was effectively reduced in the OR group, but not in the NR group (TCRαβ DNT/T: <0.05; TCRαβ DNT/Lym: =0.001; TCRαβ DNT counts: <0.01). TCRαβ DNT appears to play a significant role in the pathogenesis of pediatric ITP and may be involved in the immune response to HD-DXM. The correction of elevated TCRαβ DNT in patients who respond to HD-DXM may provide a novel insight for immune therapy in pediatric ITP.

Hemophilia B (HB) is a hereditary bleeding disorder caused by a deficiency of coagulation factor IX (FIX), which represents 15% to 20% of all patients with hemophilia. Clinical studies have found significant benefits of prophylaxis treatment with FIX versus on-demand (OD) treatment. However, these benefits are associated with an increase in FIX consumption and a considerable increase in cost. Most Chinese children with HB receive OD treatment. Only a small proportion of patients with HB receive prophylaxis treatment in China. The patients with inhibitors could result in more complicated bleeding events, joint status, or treatment patterns. The objective of this study is to assess the cost-effectiveness of prophylaxis compared with OD treatment in children with HB without inhibitors from the Chinese health care perspective. A Markov model was used to analyze cost-effectiveness by comparing prophylaxis with OD treatment. The model uses a 17-year time horizon with a yearly cycle. Transition probabilities and utility weights were estimated using published studies. The cost data for patients with HB were collected from Beijing Children's Hospital and Capital Medical University. One-way and probabilistic sensitivity analyses were performed to assess the robustness of the results. The model projects that prophylaxis has an incremental 1.23 quality-adjusted life-years (QALYs). The incremental cost per QALY gained for individuals with HB receiving prophylaxis was ¥155,709.80 ($23,530.36) compared with the OD group, which is under the willingness-to-pay threshold (3 times the gross domestic product per capital according to the World Health Organization recommendations) in China of ¥193,932 ($29,306.37). Moreover, 1-way sensitivity analysis found that the results were sensitive to the utility of nonarticular bleeding. The lower this parameter is, the higher the probability is of the incremental cost-effectiveness ratio for prophylaxis not being cost-effective. This finding infers that when the patients have a better QALY (higher utility) at the beginning, the cost for benefit from prophylaxis treatment is lower. The results of the probabilistic sensitivity analyses indicate that the probability of prophylaxis being cost-effective is 89.3%. Although prophylaxis is a costly treatment, the results of this study indicate that it is cost-effective compared with OD treatment for children with HB in China.

Amino acids (AAs) are relevant for nitrogen cycles, climate change and public health. Their size distribution may help to uncover the source, transformation and fate of protein in the atmosphere. This paper explores the use of compound-specific δ15N patterns of hydrolyzed amino acid (HAA), δ15N values of total hydrolyzed amino acid (δ15NTHAA), degradation index (DI) and the variance within trophic AAs (∑V) as markers to examine the sources and processing history of different sizes of particle in the atmosphere. Two weeks of daily aerosol samples from five sampling sites in the Nanchang area (Jiangxi Province, China) and samples of main emission sources of AAs in aerosols (biomass burning, soil and plants) were collected (Zhu et al., 2020). Here, we measured the concentrations and δ15N values of each HAA in two size-segregated aerosol particles (> 2.5 µm and PM2.5). Our results showed that the average concentrations of THAA in fine particles was nearly 6 times higher than that in coarse particles (p < 0.01) and composition profiles of fine and coarse particles were quite different from each other. The δ15N values of hydrolyzed glycine and THAA in both fine and coarse particles were typically in the range of those from biomass burning, soil and plant sources. Moreover, the average difference in the δ15NTHAA value between fine and coarse particles was smaller than 1.5 ‰. These results suggested that the sources of atmospheric HAAs for fine and coarse particles might be similar. Meanwhile, compared to fine particles, significantly lower DI values (p  <  0.05), “scattered” δ15N distribution in trophic AA and higher ∑V values (p < 0.05) were observed in coarse particles. But the difference in δ15N values of source AA (glycine, serine, phenylalanine and lysine) and THAA between coarse particles and fine particles was relatively small. It is likely that AAs in coarse particles have advanced bacterial degradation states compared to fine particles. Besides that, the significant increase in DI values and a decrease in ∑V values for coarse particles were observed on days on which precipitation fell (p  <  0.05). This implies that “fresh” AAs in coarse particles were likely released following the precipitation.

Owing to their high intrinsic safety, dispersed fuel particles are an important fuel pattern for fourth-generation nuclear reactors. Due to the unique cladding layers and the random dispersion characteristics, dispersed fuel particles significantly differ from pressurized water reactors regarding operation-induced uncertainty. This study quantitatively analyzed overall uncertainty while considering a random distribution of dispersed fuel particles, material thickness, and fuel enrichment. The results demonstrated that, for all packing fractions, the uncertainty induced by the random dispersion of dispersed fuel particles was below 0.03%. For every packing fraction, the differences between the results obtained by the regular and the random distribution models increased, and then decreased, until reaching its maximum (1.297%) at 15%. Keff decreased as the radius of the UO2 kernel increased; Keff increased as the thickness of the cladding layer increased; the uncertainty of Keff was 1.003% when a random distribution of particles, material thickness, and fuel enrichment were taken into consideration; the uncertainty of the power distribution of reactor core assemblies was maximized (1.495%) at the edge of the reactor core. Quantitative analysis of uncertainty provides references for the optimization of design and safety margin analysis for reactors.