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Cancer development and its response to therapy are regulated by inflammation, which either promotes or suppresses tumor progression, potentially displaying opposing effects on therapeutic outcomes. Chronic inflammation facilitates tumor progression and treatment resistance, whereas induction of acute inflammatory reactions often stimulates the maturation of dendritic cells (DCs) and antigen presentation, leading to anti-tumor immune responses. In addition, multiple signaling pathways, such as nuclear factor kappa B (NF-kB), Janus kinase/signal transducers and activators of transcription (JAK-STAT), toll-like receptor (TLR) pathways, cGAS/STING, and mitogen-activated protein kinase (MAPK); inflammatory factors, including cytokines (e.g., interleukin (IL), interferon (IFN), and tumor necrosis factor (TNF)-α), chemokines (e.g., C-C motif chemokine ligands (CCLs) and C-X-C motif chemokine ligands (CXCLs)), growth factors (e.g., vascular endothelial growth factor (VEGF), transforming growth factor (TGF)-β), and inflammasome; as well as inflammatory metabolites including prostaglandins, leukotrienes, thromboxane, and specialized proresolving mediators (SPM), have been identified as pivotal regulators of the initiation and resolution of inflammation. Nowadays, local irradiation, recombinant cytokines, neutralizing antibodies, small-molecule inhibitors, DC vaccines, oncolytic viruses, TLR agonists, and SPM have been developed to specifically modulate inflammation in cancer therapy, with some of these factors already undergoing clinical trials. Herein, we discuss the initiation and resolution of inflammation, the crosstalk between tumor development and inflammatory processes. We also highlight potential targets for harnessing inflammation in the treatment of cancer.

The emergence and advancement of flexible electronics have great potential to lead development trends in many fields, such as “smart electronic skin” and wearable electronics. By acting as intermediates to detect a variety of external stimuli or physiological parameters, flexible sensors are regarded as a core component of flexible electronic systems and have been extensively studied. Unlike conventional rigid sensors requiring costly instruments and complicated fabrication processes, flexible sensors can be manufactured by simple procedures with excellent production efficiency, reliable output performance, and superior adaptability to the irregular surface of the surroundings where they are applied. Here, recent studies on flexible sensors for sensing humidity and strain/pressure are outlined, emphasizing their sensory materials, working mechanisms, structures, fabrication methods, and particular applications. Furthermore, a conclusion, including future perspectives and a short overview of the market share in this field, is given for further advancing this field of research.

To address the reduction in energy efficiency caused by severe signal attenuation during long-distance transmission in cognitive radio networks, this paper constructs an IRS-assisted and energy-constrained relay cognitive radio resource allocation model operating in the underlay mode. By introducing controllable reflective paths, the model enhances link quality and improves energy utilization efficiency. Our objective is to maximize the energy efficiency of secondary users while satisfying the interference constraints imposed on the primary user. To effectively solve the highly non-convex and high-dimensional optimization problem, we propose a Chaotic Spider Wasp Optimization algorithm. The algorithm employs chaotic mapping to initialize the population and enhance population diversity, and incorporates a dynamic trade-off factor to achieve an adaptive balance between hunting and nesting behaviors, thereby improving global search capability and avoiding premature convergence. In addition, the Jain fairness index is introduced to enforce fairness in the power allocation among secondary users. Simulation results demonstrate that the proposed model and optimization method significantly improve system energy efficiency and the stability of communication quality.

The use of a cognitive radio power allocation algorithm is an effective method to improve spectral utilization. However, there are three problems with traditional cognitive radio power allocation algorithms: (1) based on the ideal channel model analysis, channel fluctuation is not considered; (2) they do not consider fairness among cognitive users; and (3) some algorithms are complex and locating the optimal power allocation scheme is not an easy task. For the above problems, this study establishes a robust model which adds the cognitive user transmission rate variance constraint to solve the maximum channel capacity time power allocation scheme by considering the worst-case channel transmission model, and finally solves this complex non-convex optimization problem by using the hybrid particle swarm algorithm. Simulation results show that the algorithm has good robustness, improves the fairness among the cognitive users, makes full use of the channel resources under the constraints, and has a simple algorithm, fast convergence, and good optimization results.

Cognitive radio (CR) is a candidate for opportunistic spectrum implementation in wireless communications, allowing secondary users (SUs) to share the spectrum with primary users (PUs). In this paper, a robust adaptive target power allocation strategy for cognitive nonorthogonal multiple access (NOMA) networks is proposed, which involves the maximum transmission power of each SU and interference power threshold under PU constraints. By introducing the signal-to-interference-plus-noise ratio (SINR) adjustment factor, the strategy enables single-station communication to achieve energy efficiency (EE) or high throughput (HT), thus making the target function more flexible. In the same communication scenario, different cognitive users can choose different communication targets that meet their needs. Different QoS can be selected by the same cognitive user at different times. In the case of imperfect channel state information (CSI), semi-infinite (SI) constraints with bounded uncertainty sets are transformed into an optimization problem under the worst case, which is solved by the dual decomposition method. Simulation results show that this strategy has good adaptive selectivity and robustness.

Background: Empty-nest older adults are considered a high-risk group for frailty due to constrained social support systems, yet the heterogeneity in their frailty progression remains poorly characterized. This study aimed to identify distinct frailty trajectory classes among Chinese empty-nest older adults and explore class-specific predictive factors. Methods: We analyzed eight years of data from the China Health and Retirement Longitudinal Study. The analysis included 1399 empty-nest older adults after eligibility screening. Frailty was assessed by the frailty index (FI). Growth Mixture Modeling was employed to identify FI trajectory classes, an linear, quadratic, and freely estimated forms were compared. Variable selection was performed via LASSO regression with bootstrap stability verification. Final predictors were analyzed using multinomial logistic regression. Results: A three-class quadratic model best represented the FI trajectories: “Low-increasing”, “High-fluctuating”, and “Elevated-stable”. Common risk factors included older age, rural residence, lower grip strength, death of children, and lower life satisfaction. The “High-fluctuating” trajectory was associated with poorer childhood health and smoking. The “Elevated-stable” trajectory was predicted by worklessness and by drinking. Physiological indicators showed no independent associations. Conclusions: Frailty among Chinese empty-nest older adults follows heterogeneous pathways shaped by life-course, socioeconomic, and psychophysiological factors. These results support the need for trajectory-specific screening, early risk detection, and tailored interventions for high-risk subgroups.

Forsythia suspensa (Thunb.) Vahl ( F. suspensa ) is a traditional Chinese medical herb and only its fruit is currently used in clinical therapies. However, the discarded parts like leaves also contain a large number of active components. In this study, we used macroporous adsorption resin to enrich the effective components from F. suspensa leaves. The separated active compounds were then identified and quantified by ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC/Q-TOF MS) and high-performance liquid chromatography Active components with antibacterial properties extracted from F. suspensa leaves were confirmed in vitro and the corresponding mechanisms were explored. In sum, a stable and effective method for extracting antibacterial active components from F. suspensa leaves was established in this study, which proved the practicability of F. suspensa leaves as traditional Chinese medicine and is conducive to the more comprehensive utilization of the plant.

Self-reported skin discomfort is a common problem during pregnancy, but it is not clear whether skin barrier function is altered in the process. Few studies have described the skin barrier function during pregnancy. In this work, we used highly sensitive and high-resolution ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to distinguish skin surface lipid (SSL) combined with multivariate analysis of lipids and metabolic changes to determine the relationship between SSL changes and skin physiology during pregnancy in order to better understand the skin condition of pregnant women. The results showed a significant reduction in the total lipid content in pregnant women. A total of 2270 lipids were detected, and the relative abundances of fatty acyls and glycerolipids were significantly reduced, while glycerophospholipids (GPs), sphingolipids, and saccharolipids was significantly increased in the pregnancy group. Multivariate data analysis indicated that 23 entities constituted the most important individual species responsible for the discrimination and phosphatidylcholine was the most abundant lipid in pregnancy group. In addition, compared to SSL profile of control group, it was observed that the average chain length of ceramides and fatty acids both decreased in SSL profile of pregnancy group. The main and most commonly affected pathway was that of GP pathways. These findings indicate that skin lipids are significantly altered in mid-pregnancy compared to the control group. Changes in ostrogen during pregnancy also make the skin more susceptible to inflammatory factors and lead to more fragile and susceptible skin, weakening the skin barrier along with the lipid alterations.

Pulsatilla chinensis (Bunge) Regel is a commonly used Chinese medicine for clearing away heat and detoxification, cooling blood, stopping dysentery, and anti-inflammatory effects. Pulsatilla chinensis saponins (PRS) have been identified to be responsible for producing these pharmacological activities. Studies have shown that Pulsatilla decoction has a good therapeutic effect on ulcerative colitis (UC), however, the therapeutic effect of PRS on UC has not been reported. Therefore, the purpose of this study was to investigate the possible anti-UC activity of PRS using a dextran sulfate sodium (DSS)-induced rat model, and further study the mechanism of PRS in the treatment of UC. The fecal and colon samples were collected from rats to monitor the changes in the composition and diversity of the intestinal flora, and pathological colon sections were also made to examine the mesenteric hemorheological characteristics. The results showed that PRS significantly reduced the mesenteric blood flow in UC rats and significantly alleviated the inflammatory response, which indicates that saponins are involved in the anti-UC effects of PRS. At the same time, it is also suggested that the regulation of intestinal flora by Pulsatilla chinensis saponins is an important pathway for its anti-UC activity, which may be ascribed to the increase in beneficial bacteria like norank_F_Muribaculaceae and norank_F_norank_O_Clostridia_UCG-014, and decrease in the harmful Bacteroides.

Self-Reported Health (SRH) is an important covariate in health and gerontology research and may be related to dietary diversity. Therefore, this study aimed to analyze this association in a large-scale general population of rural older adults from China. It also investigates the mediating effect of the psychological equilibrium (PE) in the association between dietary variety and SRH in this population. Based on data from the 2018 Chinese Longitudinal Healthy Longevity Study (CLHLS), 4,643 rural older adults were included in the study. The Dietary Variety Index was found across seven food classes using latent class analysis (LCA). We examined the factors impacting self-reported health using unordered multiple logistic regression analysis. Model 4 of the PROCESS version 4.1 software was used to evaluate the mediation impact of psychological balance. 4,643 rural seniors from the CLHLS were included in the study. Four distinct dietary variation indices (DVIs) were identified for each of the seven food categories through Latent Class Analysis. Fruit, vegetables, meat, fish, eggs, nuts, and milk significantly influenced self-reported health (SRH), according to unordered multinomial logistic regression. Positive correlations between DVI and psychological equilibrium (PE) ( r  = 0.052, P  < 0.001), DVI and SRH ( r  = 0.054, P  < 0.001), and PE and SRH ( r  = 0.220, P  < 0.001) were revealed by Pearson correlation analysis. PE modifies the connection between DVI and SRH, with a significant indirect effect ( β  = 0.002, 95% CI  = 0.001 to 0.003), according to mediation analysis. The self-reported health (SRH) of older people living in rural areas has unique classification features; fruits, vegetables, meat, fish, eggs, nuts, and milk have all been found to be important influencing factors. The relationship between psychological equilibrium (PE) and SRH is indirect. Our results emphasize how critical it is to support a varied diet in order to improve SRH in older adults living in rural areas. Furthermore, this population’s psychological balance needs to be taken into consideration.