Shaanxi University of Technology

Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.

Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to 15 November 2023. Inclusion criteria were English original studies focusing on cancer control with SDM methodology, including prevention, early detection, diagnosis and treatment, and palliative care. Exclusion criteria were non-original research, and studies lacking SDM focus. Analysis involved categorization of studies and extraction of relevant data to answer the research question, ensuring a comprehensive synthesis of the field. Quality assessment was used to evaluate the SDM for cancer control.

Sixteen studies were included in this systematic review predominantly from the United States (7, 43.75%), with a focus on breast cancer research (5, 31.25%). Studies were categorized by WHO cancer control modules, and some studies may contribute to multiple modules. The results showed that included studies comprised two focused on prevention (1.25%), ten on early detection (62.50%), six on diagnosis and treatment (37.50%), with none addressing palliative care. Seven studies presented a complete SDM process, among which nine developed causal loop diagrams for conceptual models, ten utilized stock-flow charts to develop computational models, and thirteen conducted simulations.

This review's macrofocus on SDM in cancer control missed detailed methodological analysis. The limited number of studies and lack of stage-specific intervention comparisons limit comprehensiveness. Detailed analysis of SDM construction was also not conducted, potentially overlooking nuances in cancer control strategies.

SDM in cancer control is underutilized, focusing mainly on early detection and treatment. Inconsistencies suggest a need for standardized SDM approaches. Future research should expand SDM's application and integrate it into cancer control strategies.

Electromagnetic interference (EMI) shielding materials with low reflection and high EMI shielding effectiveness (SE) have emerged as an important development trend. In this work, heterostructured Ti₃C₂T_x@CoNi were prepared by in-situ growth method. Then Ti₃C₂T_x@CoNi/Ti₃C₂T_x/cellulose nanofiber (CNF) composite foams (TCTCF) with asymmetric structure were prepared by layered freezing and freeze-drying technique. The Ti₃C₂T_x@CoNi/CNF layer could effectively absorb electromagnetic waves, and the Ti₃C₂T_x/CNF layer was set up to induce electromagnetic waves to go through the "absorption-reflection-reabsorption" process, so as to achieve excellent EMI SE and low reflection coefficient (R). With the electromagnetic synergy of CoNi and Ti₃C₂T_x and unique asymmetric structure, TCTCF showed EMI SE of up to 85 dB and reflection loss (SE_R) of 4 dB, and R was controlled between 0.22 and 0.47. The thermal conductivity (λ) of TCTCF could be adjusted between 26.91 and 84.31 mW/(m·K), meeting the requirements of heat insulation. In addition, TCTCF could autonomously switch between infrared camouflage and infrared response modes. The radiation temperature of TCTCF was only 34 °C when it was attached to a heating stage at 100 °C. Under simulated sunlight with a power density of 160 mW/cm², the surface temperature of TCTCF could rapidly rise from room temperature to 83.4 °C. When the applied voltage was 2 V, the surface temperature of TCTCF could rapidly increase from room temperature to 140.2 °C. This work provides a new strategy for the design of polymer-based composites with high EMI SE and low R, and promotes adaptive applications of EMI shielding materials in radar stealth and infrared camouflage.

Flavor deterioration during juice processing limits industrial-scale pomegranate juice (PJ) production. To evaluate the effects of thermal and non-thermal processing on PJ flavor, three samples-pasteurized (PS), high-temperature short-time treated (HTST), and ultrasound-treated (US)-were analyzed against a fresh control (FJ). Totally 144 volatiles were identified by the combination of GC-MS and GC × GC-TOF-MS. Among, 16 was screened out as key aroma-active compounds of different PJs through GC-olfactometry/aroma intensity and relative odor activity values analysis. Quantitative descriptive analysis revealed pronounced variations in cooked flavor intensity across thermally processed samples (PS, HTST), while US exhibited a sensory profile comparable to FJ. Partial least squares regression aligned with the sensory profile. Further OPLS-discriminant analysis identified 8 and 11 key markers differentiating FJ from processed PJs, and thermal (PS, HTST) from non-thermal (US) treated PJs, respectively. Precursor addition elucidated formation pathways of major off-flavor compounds (dimethyl sulfide, methanethiol) in processed PJs.