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Cytokines are pivotal mediators of cell communication in the tumor microenvironment. Multiple cytokines are involved in the host antitumor response, but the production and function of these cytokines are usually dysregulated during malignant tumor progression. Considering their clinical potential and the early successful use of cytokines in cancer immunotherapy, such as interferon alpha-2b (IFNα-2b; IntronA ® ) and IL-2 (Proleukin ® ), cytokine-based therapeutics have been extensively evaluated in many follow-up clinical trials. Following these initial breakthroughs, however, clinical translation of these natural messenger molecules has been greatly limited owing to their high-degree pleiotropic features and complex biological properties in many cell types. These characteristics, coupled with poor pharmacokinetics (a short half-life), have hampered the delivery of cytokines via systemic administration, particularly because of severe dose-limiting toxicities. New engineering approaches have been developed to widen the therapeutic window, prolong pharmacokinetic effects, enhance tumor targeting and reduce adverse effects, thereby improving therapeutic efficacy. In this review, we focus on the recent progress and competitive landscape in cytokine engineering strategies and preclinical/clinical therapeutics for cancer. In addition, aiming to promote engineered cytokine-based cancer immunotherapy, we present a profound discussion about the feasibility of recently developed methods in clinical medicine translation.

The detection of infrared vehicle targets by UAVs poses significant challenges in the presence of complex ground backgrounds, high target density, and a large proportion of small targets, which result in high false alarm rates. To alleviate these deficiencies, a novel YOLOv7-based, multi-scale target detection method for infrared vehicle targets is proposed, which is termed YOLO-ViT. Firstly, within the YOLOV7-based framework, the lightweight MobileViT network is incorporated as the feature extraction backbone network to fully extract the local and global features of the object and reduce the complexity of the model. Secondly, an innovative C3-PANet neural network structure is delicately designed, which adopts the CARAFE upsampling method to utilize the semantic information in the feature map and improve the model’s recognition accuracy of the target region. In conjunction with the C3 structure, the receptive field will be increased to enhance the network’s accuracy in recognizing small targets and model generalization ability. Finally, the K-means++ clustering method is utilized to optimize the anchor box size, leading to the design of anchor boxes better suited for detecting small infrared targets from UAVs, thereby improving detection efficiency. The present article showcases experimental findings attained through the use of the HIT-UAV public dataset. The results demonstrate that the enhanced YOLO-ViT approach, in comparison to the original method, achieves a reduction in the number of parameters by 49.9% and floating-point operations by 67.9%. Furthermore, the mean average precision (mAP) exhibits an improvement of 0.9% over the existing algorithm, reaching a value of 94.5%, which validates the effectiveness of the method for UAV infrared vehicle target detection.

This study probe the probable impacts of coal mining pollution and its impacts on human’s health and environment. A total of 144 samples including coal and coal wastes, soil, plants, foods, and water were collected from the Hancheng county and countryside of Shaanxi, China. All the samples were analyzed for trace elements using ICP-MS, OES, and AFS. Results showed that the concentration of Se, As, Cr, Cu, Pb, Cd, Co, Ni, Mo, U, Th (mgKg −1 ), Fe, Mn, Al, Ti (%) etc., in coal and coal wastes were 7.5, 12.1, 275, 55, 54.2, 0.8, 14.8, 94.5, 8.9, 4.9, 17.2, 3.5, 0.02, 19, 0.7, respectively. While in soil 0.6, 12, 194, 27.5, 7.4, 0.6, 11.3, 83.4, 0.7, 1.7, 9.9, 3.1, 0.04, 10.5, and 0.4 for the above elements, respectively. In Hancheng foods, the average concentration of Se-0.09, As-0.15, Cr-1.8, Cu-3.2, Pb-0.4, Cd-0.02, Co-0.09, Ni-0.4, Mo-0.64, U-0.01, Th-0.03, Fe-129, Mn-15.6, Al-234, and Ti-5.2 in mgKg −1 , respectively, which are comparably higher than the countryside. The elemental concentration in groundwater of both areas was below the WHO-2004 standard. In Hancheng, the average daily intake (mgKg −1 bw/d) of Se 0.004–0.0038, As 0.004–0.13, Cr 0.055–0.06, Cd 0.001–0.004, Ni 0.018–13.91, Pb 0.05–0.001 adult-children, respectively. The toxic trace elements such as Cr, Cu, Mn, Pb, Ti, Cd, Co, Th, Fe, Al, and Mo caused non-carcinogenic risk with high morbidity in children than adults. By assessing environmental risks, coal and coal wastes caused high risk, food and plants faced moderate to high risk, while mountain and agriculture soil are prone to low to considerable risk. The pollution in Hancheng County is extreme as compared to the countryside. The study concluded that the contamination is geogenic in both the areas but coal mining enhance the metals contamination and has extensive impacts on the living community and environment of Hancheng areas.

One of the classical questions in random graph theory is to understand the asymptotics of subgraph counts. In inhomogeneous random graph, this question has not been well studied. In this study, we investigate the asymptotic distribution of m-cliques in a sparse inhomogeneous random graph. Under mild conditions, we prove that the number of m-cliques converges in law to the standard normal distribution.

The relationship between hysterectomy and ovarian preservation and depression is controversial. This study aimed to determine the association of hysterectomy and ovarian preservation with depression using National Health and Nutrition Examination Survey. To assess the association between hysterectomy with or without ovariectomy and depression, we used 3 methods. Method 1: propensity score model (PSM) was established. Method 2 was logistics regression analysis of hysterectomy and depression before and after PSM. Method 3 was a logistics regression analysis of the relationship between hysterectomy and different depressive symptoms. At the same time, in order to evaluate the association between hysterectomy with or without oophorectomy and depression, we explored the effect of four different surgical procedures on depression using logistic regression equations. We enrolled 12,097 women, of whom 2763 underwent hysterectomy, 34.455% were positive for depression. After weighting, 33.825% of the total sample had a PHQ ≥ 5. Finally, a total of 2778 women were successfully matched by propensity score, and 35.537% of them were positive for depression. The OR for PHQ ≥ 5 was 1.236 after crude adjustment of covariates and 1.234 after exact adjustment. This suggests that Hysterectomy is strongly associated with positive depression. Positive depression (PHQ ≥ 5) was associated with little interest, feeling down and trouble concentrating. It was not associated with trouble sleeping, feeling tired, poor appetite, feeling bad, slow moving or speaking, and suicidal thoughts. Oophorectomy-alone is not associated with depression. Hysterectomy-alone is a risk factor for depression, but Hysterectomy combined with Oophorectomy has a stronger correlation with depression than Hysterectomy-alone. Women who have had a Hysterectomy are at higher risk of depression than women who have not had a Hysterectomy, and this risk may be exacerbated if the uterus and ovaries are removed. When clinically appropriate, surgeons should try to preserve the patient's ovaries.

In recent years, empowered by artificial intelligence technologies, computer-assisted language learning systems have gradually become a hot topic of research. Currently, the mainstream pronunciation assessment models rely on advanced speech recognition technology, converting speech into phoneme sequences, and then determining mispronounced phonemes through sequence comparison. To optimize the phoneme recognition task in pronunciation evaluation, this paper proposes a Chinese pronunciation phoneme recognition model based on the improved Zipformer-RNN-T(Pruned) architecture, aiming to improve recognition accuracy and reduce parameter count. First, the AISHELL1-PHONEME and ST-CMDS-PHONEME datasets for Mandarin phoneme recognition through data preprocessing. Then, three layers of the Zipformer Block architecture are introduced into the Zipformer encoder to significantly enhance model performance. In the stateless Pred Network, the GELU activation function is adopted to effectively prevent neuron deactivation. Furthermore, a hybrid Pruned RNN-T/CTC Loss fusion strategy is proposed, further optimizing recognition performance. The experimental results demonstrate that the method performs excellently in the phoneme recognition task, achieving a Word Error Rate (WER) of 1.92% (Dev) and 2.12% (Test) on the AISHELL1-PHONEME dataset, and 4.28% (Dev) and 4.51% (Test) on the ST-CMDS-PHONEME dataset. Moreover, the model requires only 61.1M parameters, striking a balance between performance and efficiency.

In order to understand the spatial distribution, influencing factors, pollution level and sources of heavy metals in black soil profiles in Northeast China, black soil profile samples were collected from five sampling points in Haicheng City, Liaoning Province, with the deepest profile depth of 50m. The contents of heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb and Zn) in soil at different depths were analyzed, and the distribution characteristics and influencing factors of heavy metals in black soil profiles were analyzed. The pollution level of heavy metals in soil was evaluated based on the geo-accumulation index method and enrichment factor method, and the sources of heavy metals in soil were analyzed based on principal component analysis. The results show that the content ranges of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in the surface soil of the five profile sampling points are 7.74–16.5μg/g, 0.14–0.38μg/g, 75.4–104μg/g, 20.6–36.1μg/g, 0.031–0.20μg/g, 27.8–45.6μg/g, 28.5–45.6μg/g and 56.8–158μg/g, respectively. The Cd, Cr, Ni and Pb contents in the surface soil of the five profiles all exceeded the soil background values in Liaoning and China. Except for profile HCZK02, the contents of 8 heavy metals generally decrease with increasing depth. As the depth of profile HCZK02 increases, As, Hg and Pb show a decrease-increase-decrease change; Cd and Cr show a decrease change and Ni shows a zigzag change; Cu and Zn show a decreasing-increasing-decreasing-increasing trend. Corg, N, TC and TFe 2 O 3 in the profile soil have a very significant impact on the vertical distribution characteristics of heavy metals. There are certain differences in the pollution degree of heavy metals in the surface soil of different profiles. Except for profile HCB01, where Cd and Hg in the surface soil are at moderate pollution levels, the heavy metals in the surface soil of the other profiles are at non-pollution to mild pollution levels. Principal component analysis results show that As, Cr, Cu and Ni belong to natural sources, Cd and Hg belong to anthropogenic sources from agricultural activities-atmospheric deposition, and Pb and Zn have both sources.

Growing evidences indicated that Long noncoding RNAs (lncRNAs) played important roles in tumor initiation and progression. However, the function and mechnism of lncRNA ferritin heavy chain 1 pseudogene 3 (FTH1P3) remain unknown in uveal melanoma. We showed that the expression level of FTH1P3 was upregulated in uveal melanoma cell lines and tissues. Elevated expression of FTH1P3 promoted uveal melanoma cell proliferation, cell cycle and migration. Moreover, we found that FTH1P3 was a direct target gene of miR-224-5p in uveal melanoma cell. Overexpression of FTH1P3 suppressed miR-224-5p expression and promoted the expression of Rac1 and Fizzled 5, which were the direct target genes of miR-224-5p. Furthermore, we showed that miR-224-5p expression level was downregulated in uveal melanoma cell lines and tissues. FTH1P3 expression was inversely correlated with the miR-224-5p expression in uveal melanoma tissues. Ectopic expression of miR-224-5p decreased uveal melanoma cell proliferation, cell cycle and migration. Elevated expression of FTH1P3 enhanced uveal melanoma cell proliferation and migration by inhibiting miR-224-5p expression. These results suggest that lncRNA FTH1P3 plays a crucial role in uveal melanoma. Investigation of the underlying mechanism may be a target for the treatment of uveal melanoma.

Background Healthcare inequities pose a substantial challenge to achieving universal health coverage, particularly in low- and middle-income countries (LMICs). The Chinese government implemented Hierarchical Medical System (HMS) to optimize resource allocation and improve healthcare access. This study aimed to evaluate the impact of HMS on healthcare utilization and the inequities. Methods This study utilized longitudinal data from the China Family Panel Studies (CFPS) conducted in 2012, 2014, 2016, and 2018, which included a final sample of 105,335 individuals. A multiple-period difference-in-differences method was employed to explore the impact on outpatient and inpatient utilization across socioeconomic dimensions. The concentration Index and the horizontal inequity index (HI) were used to assess inequities in healthcare utilization. Additionally, a decomposition analysis was performed to identify the contributors to inequalities. Results HMS demonstrated significant negative impacts on both outpatient and inpatient utilization (OR = 0.825, SE = 0.058; OR = 0.869, SE = 0.071, respectively), with a short-term decline in outpatient services and a lasting reduction in inpatient services. The heterogeneity tests revealed a pronounced impact in central and rural areas. The results indicated pro-poor inequities in outpatient utilization and pro-rich inequities in inpatient utilization. HMS reduced inequalities and inequities in healthcare utilization, particularly for outpatient services. HI in inpatient services increased in the initial year but decreased after 2 years of HMS. The decomposition analyses identified the primary contributors as economic level and health status. While the economic level exacerbated inequalities, health insurance and higher educational attainment mitigated inequalities in healthcare utilization. Conclusion HMS had an unintended impact on decreasing healthcare utilization in China. HMS improved equity in outpatient utilization, it faced challenges in enhancing equity in inpatient utilization. Policymakers should prioritize strengthening primary care infrastructure in central and rural areas, ensuring affordable healthcare models, reinforcing educational attainment, and expanding health insurance coverage to promote equity in healthcare utilization. These findings provide crucial insights for guiding equitable healthcare reform in LMICs and advancing progress toward the Sustainable Development Goals.

The study of circular orbits offers profound insights into the structure of spacetime around black holes. While the topological properties of these orbits are well-established for neutral particles, the influence of electric charge–particularly for massless particles–remains a subject of exploration. In this work, we employ a topological current ϕ -mapping approach to systematically investigate the circular orbits of charged test particles in static, spherically symmetric black hole spacetimes with flat, anti-de Sitter (AdS), and de Sitter (dS) asymptotics. We demonstrate that the particle’s charge significantly alters the topological classification of both timelike and null circular orbits. A key finding is that for multi-horizon black holes, if a circular orbit with fixed angular momentum and charge exists between two neighboring horizons, there will always be at least one unstable null and one unstable timelike circular orbit. Outside the outermost horizon, the asymptotic behavior of spacetime and the specific charge ratio crucially determine the topological charge W , dictating the existence and stability of orbits. Our results, validated through Reissner–Nordström (RN), RN-AdS, and RN-dS examples, extend the topological orbit classification framework and provide a foundation for potential applications in environments where effective charge dynamics may be relevant, such as magnetized plasmas around black holes.