Current Science

The Mechanism of CCR5 in Tumors and Therapeutic Strategies

2026-05-20T14:57:06+00:00

With the continuous development of immunotherapy technology, immunotherapy has gradually become a key means of cancer treatment. Among them, chemokine receptor 5 (CCR5) can regulate immune responses and is an important target for a variety of tumor immunotherapies. CCR5 belongs to the β chemokine receptor family, a seven-transmembrane G protein-coupled receptor that is widely expressed in a variety of immune cells and tumor cells and is involved in tumorigenesis and tumor progression. CCR5 is aberrantly expressed in a variety of solid tumors (such as breast cancer, gastrointestinal cancer, pancreatic cancer, colon cancer, prostate cancer, melanoma) and hematologic malignancies, and is closely related to the poor prognosis of tumors by recruiting immune cells and regulating the tumor microenvironment, promoting tumor proliferation, invasion and metastasis. At present, initial results have been achieved in the treatment of CCR5-targeted tumors, and small molecule inhibitors of CCR5 such as leronlimab, maraviroc and vicriviroc have entered clinical studies. This article reviews the mechanism of CCR5 in tumorigenesis and progression, as well as the development history and application prospects of CCR5-targeted therapy strategies.

Predicting Varicella in Xuzhou City Using Autoregressive Integrated Moving Average Model

2026-06-04T08:16:59+00:00

Background: Varicella remains a public health concern in Xuzhou, China, with documented seasonal patterns and declining incidence from 2018–2023. Accurate forecasting is critical for resource allocation.

Methods: Monthly varicella cases (January 2018–December 2023) from China’s Disease Surveillance System were analyzed. A seasonal ARIMA model (ARIMA(p,d,q)(P,D,Q)₁₂) was developed using 2018–2023 data, with 2024 data for validation. Model selection criteria included Stationary R², Normalized BIC, and RMSE. Residual diagnostics involved Ljung-Box testing.

Results: Among 23,690 cases (2018–2023), incidence declined by 64.5% (peak: 5,718 cases in 2019; nadir: 2,027 cases in 2023), exhibiting bimodal seasonality (primary peak: October–January; secondary: May–August). ARIMA(2,0,0)(0,1,0)₁₂ demonstrated optimal fit (Stationary R²=0.813, Normalized BIC=9.693; all parameters p<0.001; residuals white noise, Ljung-Box p=0.210). Validation revealed systematic underprediction in spring (February–April: +81.97% to +79.03%) but alignment in May–December.

Conclusion: The ARIMA(2,0,0)(0,1,0)₁₂ model reliably forecasts varicella trends but underestimates spring incidence. Seasonal adjustments and real-time surveillance integration may enhance accuracy.

A Multi-Scale Spatiotemporal Feature Self-Adaptive Fusion Model for Traffic Flow Prediction

2026-05-26T14:46:39+00:00

Accurate short-term traffic flow prediction remains challenging because of the nonlinear, multi-scale and spatiotemporally coupled nature of traffic data. To address these issues, this study proposes a multi-scale spatiotemporal feature adaptive fusion model, termed MSCA-Former. The model employs a multi-branch convolution structure to capture spatial features under different receptive fields, introduces an SE-based channel recalibration mechanism to enhance informative features adaptively, and incorporates a cross-time residual enhancement module to strengthen temporal dependency modelling. In addition, an adaptive feature fusion strategy is designed to improve the integration of spatial and temporal representations. Experiments on four public datasets, namely PEMS03, PEMS04, PEMS07 and PEMS08, show that the proposed model consistently outperforms seven representative baseline models. In particular, on the PEMS08 dataset, the proposed model reduces MAE, RMSE and MAPE by 7.5%, 12.0% and 8.6%, respectively, compared with the best baseline model. On the PEMS04 dataset, the corresponding reductions in MAE and MAPE are 7.6% and 4.1%, respectively. Ablation studies further confirm that the multi-branch convolution structure, channel recalibration mechanism and cross-time residual enhancement module all contribute positively to the overall model performance. These results indicate that MSCA-Former can effectively improve the representation and prediction of complex traffic flow patterns, providing an effective approach for short-term traffic flow forecasting in intelligent transportation systems.

Research on Surface Structure Optimization and Water Film Phase Change of Plate-Tube Evaporative Condenser

2026-06-02T02:02:19+00:00

To investigate the flow and heat transfer characteristics of a plate-fin evaporative condenser and to optimize its internal cavity structure, this study employs a combination of experimental methods and numerical simulations based on the commercial software Fluent. A mathematical model describing the gas-liquid two-phase flow is established, and the heat transfer performance of the heat exchanger is thoroughly examined. By comparing the experimental results with the simulation outcomes, good agreement is found in key parameters, which validates the accuracy and reliability of the numerical model. Based on this, the study analyzes the variation of the Nusselt number on the plate surface and the distribution characteristics of the water film under different Reynolds numbers. Consequently, the optimal cavity depth is determined to be H=2.0, and the optimal small diameter is D1=6mm. Under these optimal structural conditions, the influence of ten different inlet Reynolds numbers (ranging from 3500 to 13500) on the water film thickness is further investigated. The results indicate that as the Reynolds number increases, the water film thickness initially increases and then gradually tends to stabilize; that is, once the Reynolds number reaches a certain value, the growth rate of the water film thickness slows down significantly and approaches a constant value.

Macroeconomic Costs and Benefits of Energy Storage Configuration in China: Evidence from a Storage-Augmented Multi-Regional CGE Framework

2026-06-08T11:23:09+00:00

Energy storage is usually evaluated as a power-system flexibility technology, but its economy-wide value also depends on investment demand, electricity-cost pass-through, renewable curtailment, sectoral output and interregional trade. This paper develops a transparent storage-augmented multi-regional computable general equilibrium (CGE) framework for China and applies it to a counterfactual experiment for 2024-2035. The framework explicitly separates public 2024 data anchors, calibrated regional-sectoral inputs, exogenous scenario assumptions and deterministic model outputs. The benchmark uses official GDP, macro-regional GDP, electricity consumption, renewable generation, renewable utilization and new-type energy-storage statistics. The 2035 values are not observed data or point forecasts; they are model-generated counterfactual outcomes under stated allocation rules, battery-cost assumptions and storage-coordination parameters. The model links a compact four-region, eight-sector SAM/MRIO benchmark with a storage-augmented electricity module in which storage affects effective variable renewable electricity through curtailment reduction, peak-cost smoothing and interregional balancing. Five scenarios are evaluated: business-as-usual growth, economically sized storage, resource-targeted storage, coordinated allocation and accelerated high deployment. In the central experiment, coordinated allocation reaches 320 GW and 1280 GWh of new-type energy storage by 2035, lowers the electricity-cost index to 97.4 relative to BAU, reduces the wind-solar curtailment proxy to 4.6%, and raises equivalent variation by 0.47%. The accelerated high-deployment scenario installs more capacity but produces a smaller welfare gain. Additional decomposition and robustness checks show that this ranking is driven by the interaction of allocation quality, coordination and investment crowding rather than by an assumed capacity target alone. The paper contributes a reproducible data pipeline, an explicit storage-CGE accounting structure and regional allocation rules that can be extended with a full provincial SAM and hourly dispatch module.

Synthesis and Herbicidal Activity of Novel p-Menthane Derivatives Containing Sulfone Unit

2026-06-19T14:51:31+00:00

A series of novel p-menthane derivatives incorporating a sulfone unit were synthesized and evaluated for herbicidal activity under greenhouse conditions. Most of the compounds exhibited good post‑emergence activity against Echinochloa crusgalli, Digitaria sanguinalis, and Amaranthus retroflexus, as well as good pre‑emergence activity against Digitaria sanguinalis, and Amaranthus retroflexus. Notably, compound 4h was identified as the most potent derivative, achieving an average control rate of 97.5% across the three weed species under both pre‑ and post‑emergence applications, and displayed a more favorable crop safety profile than the reference herbicide diuron. Furthermore, compound 4i showed herbicidal activity comparable to that of diuron, but with superior crop safety.

Investigate Placental Vascular Impedance Is Associated with Maternal Cardiac Performance and Remodeling in Pregnancy

2026-06-20T13:54:03+00:00

Abstract

Objectives: This study aimed to evaluate the relationship between the placental pulsatility index (PPI) and maternal cardiovascular adaptation, specifically assessing cardiac geometry, diastolic/systolic function, and global hemodynamics.

Methods: In this cross-sectional study of 389 singleton pregnancies (May 2024–April 2025), concurrent Doppler-derived PPI and comprehensive transthoracic echocardiography were performed. Pearson correlations were used to analyze the link between PPI and cardiac indices.

Results: Elevated PPI was significantly associated with attenuated physiological eccentric remodeling, evidenced by inverse correlations with LV end-diastolic volume (r = -0.125, p = 0.024) and interventricular septal thickness (r = -0.139, p = 0.012). PPI showed robust positive correlations with diastolic parameters, such as the mitral E/A ratio (r = 0.227, p < 0.001) and septal e'/a' ratio (r = 0.254, p < 0.001). Furthermore, higher PPI correlated with decreased cardiac output (r = -0.237, p < 0.001), while conventional systolic indices remained largely stable.

Conclusions: Increased placental vascular resistance is linked to detectable alterations in maternal diastolic function and ventricular geometry. Diastolic parameters appear more sensitive to placental impedance, suggesting their potential value in antenatal cardiovascular surveillance.

Three-Dimensional Geological Models (3D Gms) and Their Spatial Analysis Methods for Mineral Prospectivity Modelling (MPM)

2026-06-26T14:56:27+00:00

A comprehensive review of three-dimensional geological models (3D GMs) and their spatial analysis and statistics methods for mineral prospectivity modeling (MPM) is presented. Firstly, we explore both explicit and implicit 3D geological modeling techniques and examine data structures of 3D GMs. The primary challenge of representing and modeling complex geological structures remains still unresolved. The ultimate objective of 3D geological modeling is to facilitate further spatial analysis and practical applications. Thus, constructing 3D GMs with essential geological characteristics necessitates the abstraction, selection, and integration of multi-resource data. Secondly, 3D GMs can undergo further spatial analysis and statistics methods within 3D geographical information systems (GIS). In the realm of geological variable construction, commonly employed spatial analysis methods include interpolation analysis, stochastic simulation, distance analysis, direction analysis, iso-surface analysis, gradient analysis, spatial auto-correlation analysis, and clustering analysis. Moreover, when investigating the relationships among geological variables, techniques such as cross-correlation analysis and spatial regression analysis are commonly employed.