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Cancer is widely regarded as a leading cause of death in humans, with colon adenocarcinoma (COAD) ranking among the most prevalent types. Cuproptosis is a novel form of cell death mediated by protein lipoylation. Cuproptosis-related genes (CRGs) participate in tumourigenesis and development. Their role in pan-cancer and COAD require further investigation. This study comprehensively evaluated the relationship among CRGs, pan-cancer, and COAD. Our research revealed the differential expression of CRGs and the cuproptosis potential index (CPI) between normal and tumour tissues, and further explored the correlation of CRGs or CPI with prognosis, immune infiltration, tumor mutant burden(TMB), microsatellite instability (MSI), and drug sensitivity in pan-cancer. Gene set enrichment analysis (GSEA) revealed that oxidative phosphorylation and fatty acid metabolism pathways were significantly enriched in the high CPI group of most tumours. FDX1 and CDKN2A were chosen for further exploration, and we found an independent association between FDX1 and CDKN2A and prognosis, immune infiltration, TMB, and MSI in pan-cancer. Furthermore, a prognostic risk model based on the association between CRGs and COAD was built, and the correlations between the risk score and prognosis, immune-related characteristics, and drug sensitivity were analysed. COAD was then divided into three subtypes using cluster analysis, and the differences among the subtypes in prognosis, CPI, immune-related characteristics, and drug sensitivity were determined. Due to the level of LIPT1 was notably positive related with the risk score, the cytological identification was carried out to identify the association of LIPT1 with proliferation and migration of colon cancer cells. In summary, CRGs can be used as potential prognostic biomarkers to predict immune infiltration levels in patients with pan-cancer. In addition, the risk model could more accurately predict the prognosis and immune infiltration levels of COAD and better guide the direction of clinical medication. Thus, FDX1, CDKN2A, and LIPT1 may serve as prospective new targets for cancer therapy.

Summary: The importance of trained immunity in antitumor immunity has been increasingly recognized, but the underlying metabolic regulation mechanisms remain incompletely understood. In this study, we find that squalene epoxidase (SQLE), a key enzyme in cholesterol synthesis, is required for β-glucan-induced trained immunity in macrophages and ensuing antitumor activity. Unexpectedly, the shunt pathway, but not the classical cholesterol synthesis pathway, catalyzed by SQLE, is required for trained immunity induction. Specifically, 24(S),25-epoxycholesterol (24(S),25-EC), the shunt pathway metabolite, activates liver X receptor and increases chromatin accessibility to evoke innate immune memory. Meanwhile, SQLE-induced reactive oxygen species accumulation stabilizes hypoxia-inducible factor 1α protein for metabolic switching into glycolysis. Hence, our findings identify 24(S),25-EC as a key metabolite for trained immunity and provide important insights into how SQLE regulates trained-immunity-mediated antitumor activity.

Background: We aimed to investigate the clinical and dosimetric factors associated with radiation-induced rhinosinusitis, and further elucidate the optimal dose-volume constraints for nasopharyngeal cancer patients who underwent volumetric-modulated arc therapy (VMAT). Methods: A retrospective review of 196 nasopharyngeal carcinoma (NPC) patients who underwent definitive VMAT between August 2018 and May 2021 was conducted. Both clinical and dose-volume histogram (DVH) data of NPC patients without rhinosinusitis at baseline were selected for analysis. Results: The cumulative incidence of post-RT rhinosinusitis at the 3-, 6-, 9-, and 12-months, and >1 year were 29.6 %, 41.3 %, 42.9 %, and 45.4 %, and 47.4 %, respectively. Nasal irrigation was negatively associated with post-RT rhinosinusitis (p 1.16 % and >1.00 %, respectively (p = 0.027 and p = 0.002). Sphenoid sinusitis was more frequent when Dmax(maxillary sinus) exceeded 69.2Gy (p = 0.005). Conclusions: Regular nasal irrigation may reduce the development of rhinosinusitis. Dose-volume constraints of V70 and Dmax to the maxillary sinus are suggested for VMAT planning. Patients exceeding these thresholds should be closely monitored and potentially offered preventative interventions within 3–6 months post-RT.

Summary: Nasopharyngeal carcinoma (NPC) is known for high curability during early stage of the disease, and early diagnosis relies on nasopharyngeal endoscopy and subsequent pathological biopsy. To enhance the early diagnosis rate by aiding physicians in the real-time identification of NPC and directing biopsy site selection during endoscopy, we assembled a dataset comprising 2,429 nasopharyngeal endoscopy video frames from 690 patients across three medical centers. With these data, we developed a deep learning-based NPC detection model using the you only look once (YOLO) network. Our model demonstrated high performance, with precision, recall, mean average precision, and F1-score values of 0.977, 0.943, 0.977, and 0.960, respectively, for internal test set and 0.825, 0.743, 0.814, and 0.780 for external test set at 0.5 intersection over union. Remarkably, our model demonstrated a high inference speed (52.9 FPS), surpassing the average frame rate (25.0 FPS) of endoscopy videos, thus making real-time detection in endoscopy feasible.

ABSTRACT: This study developed and characterized a γ-aminobutyric acid (GABA)-enriched yogurt fermented by Levilactobacillus brevis CGMCC1.5954. The GABA content in the yogurt was 147.36 mg/100 mL, which was 317.06% higher than that of the control group. Furthermore, there was a significant improvement in the aroma, hardness, adhesion, cohesiveness, and gelatinousness of yogurt. The chromatography and metabolomics analyses further confirmed the high GABA content in yogurt and its nutritional value, and the metabolic pathway for GABA production by L. brevis 54 was identified. A total of 58 volatile flavor compounds were identified using headspace solid-phase microextraction-gas chromatography-mass spectrometry, of which 2-nonanone and 2-heptanone may be responsible for the high odor score of GABA-enriched yogurt. This study developed a nutritious and unique GABA-enriched flavored yogurt, summarized the metabolic pathway of GABA, and provided a flavor fingerprint that could guide the production of specifically flavored yogurts.

Summary: Indanone and its analogs are widely used intermediates for many useful chemicals. Decalin and its alkylated analogs are major components of thermal-stable aviation fuels and the additives used to improve the thermal stability of aviation fuel. In this work, we develop an integrated route to selectively produce trimethyl-indanone or alkylated decalin with cellulose. First, cellulose was hydrogenolyzed to 2,5-hexanedione in a biphasic reaction system of toluene/NH4Br aqueous solution over Pd/C catalyst. Under the catalysis of alkali hydroxide, 2,5-hexanedione was converted to a mixture of C12 oxygenates (with trimethyl-indanone as the main component) at room temperature. Trimethyl-indanone can be used as an intermediate for many useful chemicals. Moreover, the C12 oxygenates can be hydrodeoxygenated to a mixture of dimethyl decalin and C12 monocycloalkanes with a low freezing point (200 K) and high density (0.85 g mL−1). This work provides insights on the preparation of indanone or advanced aviation fuel with cellulose. Science for society: The production of valuable chemicals and sustainable aviation fuel (SAF) with renewable, cheap, and abundant lignocellulose has drawn a lot of attention. Indanone and its analogs are widely used as intermediates in the manufacture of many useful chemicals. Currently, these compounds are obtained from fossil resources at low yields. Decalin and alkylated decalins are additives to improve the thermal stability of aviation fuel. Herein, we report an integrated route for the selective preparation of trimethyl-indanone or alkylated decalins with cellulose, the most abundant biomass. Compared with the reported processes to produce indanone analogs or SAF, this new process has several advantages, such as renewable feedstock, mild reaction conditions, fewer steps, and excellent fuel properties (e.g., lower freezing point, higher volumetric heat value, thermal stability of final products, etc.). This work paves a new way for the high-value utilization of cellulose.

Heat transfer and temperature evolution in overburden fracture and ground fissures are one of the essential topics for the identification of ground fissures via unmanned aerial vehicle (UAV) infrared imager. In this study, discrete element software UDEC was employed to investigate the overburden fracture field under different mining conditions. Multiphysics software COMSOL were employed to investigate heat transfer and temperature evolution of overburden fracture and ground fissures under the influence of mining condition, fissure depth, fissure width, and month alternation. The UAV infrared field measurements also provided a calibration for numerical simulation. The results showed that for ground fissures connected to underground goaf (Fissure I), the temperature difference increased with larger mining height and shallow buried depth. In addition, Fissure I located in the boundary of the goaf have a greater temperature difference and is easier to be identified than fissures located above the mining goaf. For ground fissures having no connection to underground goaf (Fissure II), the heat transfer is affected by the internal resistance of the overlying strata fracture when the depth of Fissure II is greater than 10 m, the temperature of Fissure II gradually equals to the ground temperature as the fissures’ depth increases, and the fissures are difficult to be identified. The identification effect is most obvious for fissures larger than 16 cm under the same depth. In spring and summer, UAV infrared identification of mining fissures should be carried out during nighttime. This study provides the basis for the optimal time and season for the UAV infrared identification of different types of mining ground fissures.

Soil moisture is a significant variable in agricultural study and precision irrigation decision-making. It determines the soil water availability for plants, directly influencing plant growth, yield and quality. Owing to the variations in regional microclimate, landform difference, soil type and vegetation coverage, the soil moisture has strong spatial-temporal heterogeneity on a large regional scale. Micro-wave remote sensing can be used to invert soil moisture based on the dielectric constant under different weather conditions, while optical remote sensing utilizes spectral characteristics to estimate the physiological and ecological information of vegetation. In this study, two new hybrid models (ACO-RF and SSA-RF) were structured by optimizing the standalone random forest (RF) based on the ant colony optimization algorithm (ACO) and sparrow search algorithm (SSA), and six input combinations based on the multi-temporal Sentinel-1 and Landsat-8 remote sensing data from different sensors (optical, thermal and radar sensors) were used. The standalone RF, ACO-RF, and SSA-RF models with different combinations of inputs were employed to predict the soil moisture at different depths (5 cm, 10 cm, 20 cm, 40 cm) in a large-scale drip-irrigated citrus orchard. The results showed that the ACO-RF and SSA-RF outperformed the standalone RF model in terms of prediction accuracy at a depth of 0–40 cm, with R2 of 0.800–0.921 and 0.504–0.798, RRMSE of 7.214–16.284% and 11.124–22.214%, respectively. In the hybrid model, the ACO-RF model had better prediction accuracy than the SSA-RF model, with R2 of 0.805–0.921 and 0.800–0.911, RRMSE of 7.214–13.244% and 8.274–16.284%, respectively. At depths of 5 cm, 10 cm and 20 cm, the inversion accuracy of the model with microwave inputs was higher than that with multispectral inputs, with R2 of 0.556–0.888 and 0.541–0.886, RRMSE of 9.015–19.544% and 9.124–22.214%, respectively. However, at a depth of 40 cm, the inversion accuracy of the model with multispectral inputs was higher than that with microwave inputs, with R2 of 0.532–0.841 and 0.508–0.831, RRMSE of 9.124–21.021% and 9.142–21.214%, respectively. The model with multispectral, thermal, and microwave inputs exhibited the highest accuracy in predicting soil moisture, with R2 of 0.635–0.921, RRMSE of 7.214−18.564%, respectively. Therefore, the ACO-RF with multisource remote sensing data is recommended to predict the soil moisture in the drip-irrigated citrus orchard. This approach can provide data support for making intelligent irrigation decisions on a large-scale grid land lots.

Accurate evapotranspiration (ET) estimation is paramount for effective agricultural water management. As the key parameter of surface resistance (rs)-based ET models, the direct acquisition of canopy resistance (rc) remains challenge. Moreover, the applicability of rc models and rs-based ET models has not been fully validated on kiwifruit. To address above problems, this study investigates tree growth patterns, water consumption change, and soil water content (SWC) dynamics under different irrigation strategies based on a two-year experiment in Northwest China. Subsequently, the Whale Algorithm (WOA), Quantum Whale Algorithm (QWOA), and Differential Whale Algorithm (DWOA) were employed to optimize Jarvis-type rc models (JA) constructed by different constraint functions of SWC. After internal comparison within Jarvis-type models and external comparison with Kelliher-Perrier (KP), Faria (FA), and Stannard (ST) model, the recommended rc model was integrated into Penman-Monteith (PM), Shuttleworth-Wallace (SW), and Clumping (CL) to select most suitable kiwifruit ET model. The results indicated that the water stress coefficient is suitable for JA model as a constraint function of SWC, achieving R2, NSE, RMSE, and MAPE of 0.782–0.805, 0.672–0.737, 654.191–3396.594 s m−1, and 0.102–0.183 under sufficient irrigation strategy, respectively. Under deficit irrigation strategies, the corresponding R2, NSE, RMSE, and MAPE ranged 0.886–0.917, 0.828–0.885, 325.736–3251.434 s m−1, and 0.111–0.166, respectively. Besides, DWOA is the best algorithm during whole growth period, which improved original JA by 13.2–32.9% for R2, 23.0–60.2% for NSE, 26.8–36.8% for RMSE, and 17.5–36.2%, respectively. Regarding rs-based ET models, the CL performed best under various irrigation conditions, with values of R2, NSE, RMSE, and MAPE ranging 0.908–0.961, 0.842–0.947, 0.311–0.808 mm, and 0.088–0.197, respectively. Overall, the CL integrated with DWOA-JA3 is most recommended for estimating kiwifruit ET under different irrigation strategies, which is helpful for orchardists to enhance agricultural water utilization efficiency and promote sustainable kiwifruit production.

Deficit irrigation (DI) is widely recognized as an irrigation method to save water and increase/maintain yield. The objective of this study was to evaluate the effects of DI on yield and water productivity (WP, the ratio of yield divided by evapotranspiration (ET)) of woody fruits (apple, citrus, pear, peach), herbaceous fruits (strawberry, watermelon) and vine fruit (grape), and to identify the optimal irrigation management strategy for different fruit species groups. For this, we conducted a comprehensive meta-analysis with 591 observations from 56 peer-reviewed papers. Results showed that DI reduced the yield of woody, herbaceous, and vine fruits by 13.74%, 20.51%, and 9.03%, and increased WP by 13.34%, − 2.08%, and 9.89% compared with full irrigation (FI), respectively. Herbaceous fruits were more vulnerable to yield reduction than woody and vine fruits under DI. As for woody fruits, compared with FI, low degree (80%−100% irrigation amount of FI) DI performed better, increasing yield and WP by 0.87% and 9.77%. Woody fruits are suitable for DI in stage I and stage II (bud burst to leafing stage and flowering to fruit set stage), which can reduce the risk of yield reduction and significantly increase WP by 1.86%− 9.28%. Among irrigation methods, surge-root irrigation and sprinkler irrigation under DI performed better for woody fruits, increasing yield and WP by 1.81% and 11.89%, − 5.85% and 43.91%, respectively. In terms of herbaceous fruits, compared with FI, mild degree (60%−80% FI) DI declined the risk of yield reduction and significantly increased WP by 2.25%. DI at stage IV (fruit maturation stage) performed better, which can decrease the risk of herbaceous fruit yield reduction and improve WP by 0.37%. Among irrigation methods, furrow irrigation under DI performed better for herbaceous fruits, increasing yield and WP by − 0.66% and 2.29%. In terms of vine fruits, compared with FI, moderate degree (40%−60% FI) DI performed better, which can significantly increase yield and WP by − 8.05% and 13.87%. Vine fruits are suitable for DI in stage I, increasing yield and WP by 5.38% and 22.13%. For woody fruits, DI is suitable for higher seasonal precipitation (SP > 400 mm) and annual average temperature (AAT ≥ 10 °C). In contrast, for vine fruits and herbaceous fruits, DI is suitable for lower SP (< 200 mm) and AAT (< 10 °C). Our findings provide guidance for precise water deficit management of woody, herbaceous, and vine fruits.

Study region: Qilian Mountain National Park (QLMNP) in northwestern China. Study focus: The risk of soil erosion has increased noticeably at the global scale. In China, several ecological projects have been conducted to minimize the side effect of soil erosion in recent decades. Assessing soil erosion and identifying driving mechanisms are necessary due to the increased risk of ecological security in QLMNP. Here, we employed the Revised Universal Soil Loss Equation (RUSLE) to assess the soil erosion rate in QLMNP from 1982 to 2020. The driving mechanism was detected through the differences between the realistic scenario and four idealized scenarios with different fixed RUSLE input parameters. The contributions of different driving factors (soil type, digital elevation model, slope, extreme precipitation frequency and intensity, precipitation, vegetation coverage, and land use/cover change (LUCC)) were assessed through the geodetector model. New hydrological insights for the region: The soil erosion rate averaged over QLMNP increased at 0.13 t ha-1 yr-1 from 1982 to 2020, despite the slightly decrease shown in the majority (62.62%) area. Anthropic LUCC in eco-conservation measures tends to prevent soil erosion in QLMNP, but extreme precipitation has the opposite effect. The coupled impacts of extreme precipitation and LUCC dominate the soil erosion dynamics in this area. Our results indicate that ecological projects are effective to mitigate the soil erosion caused by climate change.