Molecular Engineering to Regulate the Pseudo-Graphitic Structure of Hard Carbon for Superior Sodium Energy Storage.

Resin-derived hard carbons have shown great advantages in serving as promising anode materials for sodium-ion batteries due to their flexible microstructure tunability. However, it remains a daunting challenge to rationally regulate the pseudo-graphitic crystallite and defect of hard carbon toward advanced sodium storage performance. Herein, a molecular engineering strategy is demonstrated to modulate the cross-linking degree of phenolic resin and thus optimize the microstructure of hard carbon. Remarkably, the resorcinol endows resin with a moderate cross-linking degree, which can finely tune the pseudo-graphitic structure with enlarged interlayer spacing and restricted surface defects. As a consequence, the optimal hard carbon delivers a notable reversible capacity of 334.3 mAh g-1 at 0.02 A g-1, a high initial Coulombic efficiency of 82.1%, superior rate performance of 103.7 mAh g-1 at 2 A g-1, and excellent cycling durability over 5000 cycles. Furthermore, kinetic analysis and in situ Raman spectroscopy are performed to reveal the electrochemical advantage and sodium storage mechanism. This study fundamentally sheds light on the molecular design of resin-based hard carbons to advance sodium energy for scale-up applications.

Mode-selective power splitters for mode-division multiplexing optical networks.

We propose an all-fiber mode-selective power splitter (MSPS) for non-circular-symmetric LPlm (l = 1, 2, …) modes, which is suitable for multicasting and optical performance monitoring in mode-division multiplexing optical fiber networks. The MSPSs are asymmetric two-core few-mode directional couplers composed of a few-mode fiber and a two-mode fiber. We theoretically studied the three conditions required by the MSPSs. By carefully choosing the core-to-core distance and coupling length, the MSPS can achieve arbitrary splitting ratio regardless of the modal field orientation of the input non-circular-symmetric LP mode. By using an asymmetric structure, the MSPS can ensure the power splitting only happens on the target non-circular-symmetric LP mode when the phase matching condition is satisfied. In addition, we designed and numerically simulated LP31 MSPSs with four kinds of splitting ratios, among which the one with 90/10 splitting ratio was fabricated based on tapering and polishing method. The fabricated LP31 MSPS is characterized and the results show that its splitting ratio is much more stable than regular LP31 mode-selective coupler.

Prognostic significance of serum monoclonal proteins based on immunofixation electrophoresis in B-cell non-Hodgkin lymphoma.

The presence of serum monoclonal components has been associated with poor outcomes in various hematological malignancies. The current study focused on exploring its prognostic role in B-cell non-Hodgkin lymphoma. Our study represented 314 patients with information on serum immunofixation electrophoresis at diagnosis that were available with B-cell non-Hodgkin lymphoma. IFE was positive in 61 patients (19%). Baseline features were comparable between pairs of groups, poor ECOG PS, B symptoms, advanced stage, and high-risk IPI score were significantly more frequent in the + IFE group. Shorter PFS and OS of B-NHL patients were observed in patients who presented at diagnosis with a + IFE, and IFE was the independent predictor of PFS and OS in multivariate analysis. Moreover, integrating IFE into the IPI-M1, IPI-M2, and IPI-M3 models improved the area under the curve for more accurate survival prediction and prognosis. Serum monoclonal proteins are significant prognostic indicators for newly diagnosed B-cell non-Hodgkin lymphoma that can early identify patients with poor prognosis and guide clinical treatment decisions.

An intelligent interval forecasting system based on fuzzy time series and error distribution characteristics for air quality index.

Due to the emergency environment pollution problems, it is imperative to understand the air quality and take effective measures for environmental governance. As a representative measure, the air quality index (AQI) is a single conceptual index value simplified by the concentrations of several routinely monitored air pollutants according to the proportion of various components in the air. With the gradual enhancement of awareness of environmental protection, air quality index forecasting is a key point of environment management. However, most of the traditional forecasting methods ignore the fuzziness of original data itself and the uncertainty of forecasting results which causes the unsatisfactory results. Thus, an innovative forecasting system combining data preprocessing technique, kernel fuzzy c-means (KFCM) clustering algorithm and fuzzy time series is successfully developed for air quality index forecasting. Concretely, the fuzzy time series that handle the fuzzy set is used for the main forecasting process. Then the complete ensemble empirical mode decomposition and KFCM are respectively developed for data denoising and interval partition. Furthermore, the interval forecasting method based on error distribution is developed to measure the forecasting uncertainty. Finally, the experimental simulation and evaluation system verify the great performance of proposed forecasting system and the promising applicability in a practical environment early warning system.

Energy-saving and CO2 reduction strategies for new energy vehicles based on the integration approach of voluntary advocacy and system dynamics.

The low-carbon development of new energy vehicles (NEVs) is critical to achieving the goals of carbon peaking and carbon neutrality. As such, combining gray model theory with system dynamics (SD-GM) and based on the bidirectional-cycle prediction theory, we propose a NEV annual average mileage algorithm considering the impact of the epidemic in China, taking private cars as an example. Then, combining a voluntary advocacy strategy (VA) with the SD-GM theory (VA-SD-GM integration), we establish an energy-saving and carbon-reduction management model. To evaluate the proposed algorithm, we performed a dynamic simulation. The results indicate that the enhanced green scenario enabled significant energy-saving and CO2 reduction performance but would cause side effects in the long term. Compared with the enhanced green scenario, the linkage mode reduced the impact of parking space tension, the number of NEV trips, and the intensification of traffic congestion by approximately 33%, 50%, and 34%, respectively. It effectively suppressed the continuous increase in side effects and had a synergistic effect of carbon reduction, energy conservation, congestion alleviation, and side-effect reduction. The study provides a theoretical basis for optimizing the energy-saving and CO2 reduction path of NEVs.

Global explanation supervision for Graph Neural Networks.

With the increasing popularity of Graph Neural Networks (GNNs) for predictive tasks on graph structured data, research on their explainability is becoming more critical and achieving significant progress. Although many methods are proposed to explain the predictions of GNNs, their focus is mainly on "how to generate explanations." However, other important research questions like "whether the GNN explanations are inaccurate," "what if the explanations are inaccurate," and "how to adjust the model to generate more accurate explanations" have gained little attention. Our previous GNN Explanation Supervision (GNES) framework demonstrated effectiveness on improving the reasonability of the local explanation while still keep or even improve the backbone GNNs model performance. In many applications instead of per sample explanations, we need to find global explanations which are reasonable and faithful to the domain data. Simply learning to explain GNNs locally is not an optimal solution to a global understanding of the model. To improve the explainability power of the GNES framework, we propose the Global GNN Explanation Supervision (GGNES) technique which uses a basic trained GNN and a global extension of the loss function used in the GNES framework. This GNN creates local explanations which are fed to a Global Logic-based GNN Explainer, an existing technique that can learn the global Explanation in terms of a logic formula. These two frameworks are then trained iteratively to generate reasonable global explanations. Extensive experiments demonstrate the effectiveness of the proposed model on improving the global explanations while keeping the performance similar or even increase the model prediction power.

Prevalence of congenital cryptorchidism in China: A nationwide population-based surveillance study, 2007-2021.

BACKGROUND: Despite cryptorchidism being a common genital abnormality in male newborns with significant prevalence variations globally, there is a notable scarcity of epidemiological data on this condition in China. OBJECTIVE: This study aimed to delineate the prevalence pattern of cryptorchidism in Chinese population over the past 15 years using nationwide surveillance data. MATERIALS AND METHODS: Data from the China National Population-based Birth Defects Surveillance System (2007-2021) were analyzed to calculate the prevalence rates of cryptorchidism, stratified by birth year, maternal age, maternal residence, and geographic region. Adjusted prevalence rate ratios were computed using Poisson regression, while trends in prevalence and average annual percent change (AAPC) were assessed using the joinpoint regression model. RESULTS: During the study period, a total of 1,833 cases of cryptorchidism were identified among 2,565,964 full-term male births, resulting in prevalence rates of 7.14, 5.60, and 1.54 per 10,000 births for overall, isolated, and associated cryptorchidism, respectively. The overall prevalence increased from 3.86 to 11.20 per 10,000 births, with an AAPC of 7.9% (95% confidence interval: 5.5-11.0). Significant variations were observed across maternal age (< 20 years, 7.62/10,000; 20-24 years, 6.14/10,000; 25-29 years, 6.96/10,000; 30-34 years, 7.48/10,000; ≥35 years, 9.22/10,000), maternal residence (urban vs. rural, 10.99/10,000 vs. 2.86/10,000), and geographic region (eastern, 12.38/10,000; central, 2.36/10,000; western, 2.63/10,000). Approximately one-third of cryptorchidism cases were bilaterally, while two-thirds were unilateral. Commonly observed associated abnormalities included congenital hydrocele testis, as well as anomalies in the genital organs, circulatory system, and musculoskeletal system. CONCLUSION: Despite lower rates compared to other countries, the increasing trend in prevalence of cryptorchidism necessitates further investigation and intervention.

Study on Plastic Constitutive Relation and Ductile Fracture Criterion of AM60B Magnesium Alloy.

It is currently a challenge to accurately predict the deformation and fracture behavior of metal parts in automobile crashes. Many studies have shown that the deformation and fracture behavior of materials are significantly affected by the stress state during automobile crashes with complex stress state characteristics. In order to further promote the application of die-cast magnesium alloys in automobiles, it is particularly important to study the material deformation and fracture behavior of die-cast magnesium alloys. In this paper, the mechanical properties of the AM60B die-cast magnesium alloy sheet under four stress states (shear, tension, R10 notch tension, and cupping) were designed and tested. Based on the von Mises isotropic constitutive model and Swift weighted Hockett-Sherby hardening model, the plastic constitutive model of die-cast magnesium alloy was established. Based on the plastic model and the fracture model (JC, MMC, and DIEM) considering the influence of three stress states, the deformation and fracture behavior of the AM60B die-cast magnesium alloy front-end members in three-point bending were predicted by experiments and finite element simulation. The experimental results show that the deformation mode and loading-displacement curve trend of the AM60B die-cast magnesium alloy front members are the same, the crack initiation point and crack initiation time are the same, and the crack shape is similar. The results show that the complex stress state constitutive model parameters and the DIEM fracture model obtained in this paper can accurately predict the deformation and fracture failure behavior of the AM60B die-cast magnesium alloy sheet.

Maternal PM2.5 exposure and hypospadias risk in Chinese offspring: Insights from a nationwide surveillance-based study.

Research on the association between maternal PM2.5 exposure and hypospadias risk in male offspring, particularly in highly polluted areas, has been limited and inconsistent. This study leveraged data from China's National Population-based Birth Defects Surveillance System spanning the years 2013 to 2019, and employed sophisticated machine learning models to estimate daily PM2.5 levels and other pollutants for mothers at a 1-km resolution and a 6-km buffer surrounding maternal residences. Multivariate logistic regression analyses were performed to evaluate the relationship between PM2.5 exposure and hypospadias risk. For sensitivity analyses, stratification analysis was conducted, and models for one-pollutant and two-pollutants, as well as distributed lag nonlinear models, were constructed. Of the 1194,431 boys studied, 1153 cases of hypospadias were identified. A 10 µg/m3 increase in maternal PM2.5 exposure during preconception and the first trimester was associated with an elevated risk of isolated hypospadias, with Odds Ratios (ORs) of 1.102 (95% CI: 1.023-1.188) and 1.089 (95% CI: 1.007-1.177) at the 1-km grid, and 1.122 (95% CI: 1.034-1.218) and 1.143 (95% CI: 1.048-1.246) within the 6-km buffer. Higher quartiles of PM2.5 exposure were associated with increased odds ratios compared to the lowest quartile. These findings highlight a significant association between PM2.5 exposure during the critical conception period and an elevated risk of isolated hypospadias in children, emphasizing the need for targeted interventions to reduce PM2.5 exposure among expectant mothers.

LMP1 enhances aerobic glycolysis in natural killer/T cell lymphoma.

Natural killer/T cell lymphoma (NKTCL) exhibits highly aggressive clinical behavior, and the outcomes for relapsed/refractory patients are still poor. Recently, the mechanism underlying the effect of Epstein-Barr virus (EBV) infection, which has not been fully defined in NKTCL, has attracted great attention. We explored how LMP1 promoted aerobic glycolysis via metabolic sequencing combined with mRNA sequencing and immunoprecipitation coupled to mass spectrometry. Experimental assays were used to determine the effects of LMP1 and its downstream pathway on the function and glucose metabolism of NKTCL cells. The correlations between LMP1 expression in patients and their clinical features, treatment response, and prognosis were analyzed. Results show that LMP1 enhances NKTCL cell proliferation in vitro and in vivo, inhibits apoptosis, and decreases gemcitabine sensitivity. In addition, LMP1 also enhances aerobic glycolysis in NKTCL cells, as indicated by increases in glucose uptake, lactate production, and extracellular acidification rate. Clinically, LMP1 expression is correlated with risk stratification, treatment response, and prognosis, and higher LMP1 expression indicates greater SUVmax for NKTCL patients. Mechanistically, LMP1 competitively binds to TRAF3 to promote cell proliferation and aerobic glycolysis by regulating the noncanonical NF-κB pathway. The application of an NF-κB pathway inhibitor or reactivation of the NF-κB pathway affects aerobic glycolysis and the biological function of NKTCL cells. In summary, this study is the first to describe and define in detail how LMP1 affects glucose metabolism in NKTCL and might provide a novel perspective for further treatment.

Microstructure and Mechanical Properties of Mg-Al-La-Mn Composites Reinforced by AlN Particles.

The Mg-Al-RE series heat-resistant magnesium alloys are applied in automotive engine and transmission system components due to their high-temperature performance. However, after serving at a high temperature for a long time, the Al11RE3 phase coarsened and even decomposed, while the Mg17Al12 phase grew and dissolved, which limits the service temperature of Mg-Al-RE series heat-resistant magnesium alloys to a maximum of 175 °C. In this study, a new preparation method for in situ AlN particles was presented. The AlN/Mg-4Al-4La-0.3Mn composites were prepared by a master alloy and casting method. The effects of various contents of AlN (0.5-3.0 wt.%) on the microstructure and mechanical properties of the Mg-4Al-4La-0.3Mn (AE44) alloy at room (25 °C) and high temperatures (150-250 °C) were investigated. Microstructure analysis revealed that the inclusion of AlN led to a reduction in both the grain size and second phase size in the AE44 alloy, while also improving the distribution of the second phase. The average grain size, Al11La3 phase, Al2La phase, and Al3La phase of the 2.0 wt.% AlN/AE44 composite were 135.7, 9.6, 1.9, and 12.6 µm, respectively, which were significantly lower than those of the AE44 matrix alloy (179.8, 12.6, 3.3, 17.8 µm). The refinement was attributed to the ability of AlN particles to serve as heterogeneous nucleation cores for α-Mg and, at the same time, impede the growth of the solid-liquid interface, eventually leading to grain refinement. With the increase in the AlN content, the mechanical properties of composites initially exhibited an increase at both room and high temperatures, followed by a subsequent decrease. When the AlN content was 2.0 wt.%, the composite exhibited optimal strength and plasticity matching. At room temperature, the TYS, UTS, and EL values of the 2.0 wt.% Mg-4Al-4La-0.3Mn composite were 96 MPa, 175 MPa, and 7.0%, respectively, which were increased by 26 MPa, 27 MPa, and 0.7% when compared with the base alloy. The TYS of the 2.0 wt.% Mg-4Al-4La-0.3Mn composite at 150 °C, 200 °C, and 250 °C were 17 MPa, 14 MPa, and 22 MPa higher than those of the matrix alloy, respectively. The main strengthening mechanisms were second phase strengthening, load transfer strengthening, and thermal mismatch strengthening. At elevated temperatures, AlN particles effectively pinned the grain boundaries, inhibiting their migration, and hindered dislocation climbing, resulting in excellent mechanical properties of the composites at high temperatures. This study contributes to the advancement of in situ AlN particle preparation methods and the exploration of effects of AlN on the properties and microstructure of Mg-Al-RE alloys at high temperatures (150-250 °C).

Ageing microenvironment mediates lymphocyte carcinogenesis and lymphoma drug resistance: From mechanisms to clinical therapy (Review).

Cellular senescence has a complex role in lymphocyte carcinogenesis and drug resistance of lymphomas. Senescent lymphoma cells combine with immunocytes to create an ageing environment that can be reprogrammed with a senescence­associated secretory phenotype, which gradually promotes therapeutic resistance. Certain signalling pathways, such as the NF­κB, Wnt and PI3K/AKT/mTOR pathways, regulate the tumour ageing microenvironment and induce the proliferation and progression of lymphoma cells. Therefore, targeting senescence­related enzymes or their signal transduction pathways may overcome radiotherapy or chemotherapy resistance and enhance the efficacy of relapsed/refractory lymphoma treatments. Mechanisms underlying drug resistance in lymphomas are complex. The ageing microenvironment is a novel factor that contributes to drug resistance in lymphomas. In terms of clinical translation, some senolytics have been used in clinical trials on patients with relapsed or refractory lymphoma. Combining immunotherapy with epigenetic drugs may achieve better therapeutic effects; however, senescent cells exhibit considerable heterogeneity and lymphoma has several subtypes. Extensive research is necessary to achieve the practical application of senolytics in relapsed or refractory lymphomas. This review summarises the mechanisms of senescence­associated drug resistance in lymphoma, as well as emerging strategies using senolytics, to overcome therapeutic resistance in lymphoma.

Joint effects of green space and air pollutant exposure on preterm birth: evidence from a nationwide study in China.

An association between green space exposure and preterm birth has been reported. However, evidence on the joint effects of air pollutant and green space exposure on preterm birth from nationwide research is limited in China. Based on a nationwide cohort, this study aims to explore the effect of green space exposure on preterm birth and analyze the joint effects of green space and air pollutant. Logistic regression models were developed to analyze the effects of green space exposure, and interaction effects were evaluated by adding interaction terms between green space and air pollutants. From 2013 to 2019, this study included 2,294,188 records of newborn births, of which 82,921 were preterm births. The results show that for buffer zones with 250 m, 500 m, 1000 m, and 1500 m, every 0.1 unit increase in NDVI exposure was associated with a decrease in the risk of preterm birth by 5.5% (95% CI: 4.6-6.4%), 5.8% (95% CI: 4.9-6.6%), 6.1% (95% CI: 5.3-7.0%), and 5.6% (95% CI: 4.7-6.5%), respectively. Under high-level exposure to air pollutants, high-level NDVI exposure was more strongly negatively correlated with preterm birth than low-level NDVI exposure. High-level green space exposure might mitigate the adverse effect of air pollutants on preterm birth by promoting physical activity, reducing stress, and adsorbing pollutants. Further investigation is needed to explore how green space and air pollution interact and affect preterm birth, in order to improve risk management and provide a reference for newborn health.