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Net primary productivity (NPP), a key indicator of terrestrial ecosystem quality and function, represents the amount of organic matter produced by vegetation per unit area and time. This study utilizes the MOD17A3 NPP dataset (2001–2022) to analyze the spatio-temporal dynamics of NPP in Xinjiang and projects future trends using Theil-Sen trend analysis, the Mann–-Kendall test, and the Hurst Index. By integrating meteorological data, this study employs partial correlation analysis, the Miami model, and residual analysis to explore the driving mechanisms behind NPP changes influenced by climatic factors and human activities. The results indicate that: (1) The average NPP in Xinjiang has increased over the years, displaying a spatial pattern with higher values in the north and west. Regions with increasing NPP outnumber those with declining trends, while 75.18% of the area shows un-certain future trends. (2) Precipitation exhibits a stronger positive correlation with NPP compared to temperature. (3) Climate change accounts for 28.34% of the variation in NPP, while human activities account for 71.66%, making the latter the dominant driving factor. This study aids in monitoring ecological degradation risks in arid regions of China and provides a scientific basis for developing rational coping strategies and ecological restoration initiatives.

Against the intensifying global climate change, rural tourism destinations in plateau areas are confronted with the dilemma of balancing economic development with ecological conservation. Pro-environmental behavior (PEB)has become pivotal to achieving regional environmental and tourism sustainability. This study proposes a conceptual model using a sample of 230 rural residents grounded in the Stimulus–Organism–Response (S-O-R) theory. A mediation model incorporating place attachment (PA) is constructed to examine the effects of climate change perception (CCP) and perceived value of tourism (PV) on pro-environmental behavior. Results from structural equation modeling (SEM) reveal the following: (1) Climate change perception directly and positively influences pro-environmental behavior. (2) Place attachment not only directly promotes pro-environmental behavior but also mediates the relationship between perceived value of tourism and pro-environmental behavior. (3) Perceived value of tourism exerts a direct positive effect on pro-environmental behavior in life, whereas its influence on pro-environmental behavior in agricultural production is indirect, mediated through place attachment. These findings suggest that strengthening residents’ emotional and functional connections to the local environment can effectively encourage pro-environmental actions in tourism areas, providing a theoretical basis for formulating environmental policies in high-altitude tourism destinations.

Climate change has widely impacted human and natural systems across regions worldwide. Agriculture is the most sensitive to climate change among all global production sectors. Many rural residents lack a clear understanding of climate change or its negative impacts, resulting in their inability to take timely adaptation measures and causing significant losses. This study investigates rural residents’ perceptions of climate change and their adaptation behaviors in the southeastern Qinghai–Tibetan Plateau using household survey and interview data. The results show that although climate change in the region is pronounced, rural residents’ perception remains relatively weak: only 61.74% of rural residents s perceive climate change, and 51.41% have consciously adopted adaptation measures. A Heckman selection model indicates that rural residents’ adaptation decisions are based on their perception of climate change, which is significantly associated with direct perceptions of rising temperatures and declining precipitation over the past five years, as well as with the diversity of climate information sources. Rural residents’ adaptation behavior is positively related to education of the household head, household size, and duration of residence. Further binary regression analyses reveal that technical adaptation is positively associated with age, education, household size, the proportion of household members engaged in agriculture, and perceived personal impacts of climate change, whereas economic and other adaptation strategies are positively related to education but negatively related to age and the perception that climate change has increased crop pests and diseases. Based on these findings, this study proposes targeted recommendations to better promote rural residents’ climate change adaptation and enhance the resilience of agricultural systems in the region.

In the context of global climate change, the Tibetan Plateau is particularly susceptible to meteorological disasters, including snow disasters. This study utilized daily temperature and precipitation data from 44 meteorological stations on the Tibetan Plateau spanning from 1960 to 2018 to construct a snow event dataset. Optimal marginal distribution and the copula function were chosen to calculate the joint return period and joint probability, which effectively assess the hazard of snow disasters in the region. Additionally, the study analyzed the comprehensive risk of snow disasters under various return periods by integrating social and economic data. The results indicate the following: (1) Based on the five different Archimedean copula functions, the joint return period of an error rate of each station was calculated to be less than 36%, which is significantly lower than the recurrence interval of univariate analysis; (2) High-hazard areas are predominantly concentrated in the northwest region of the Tanggula Mountains and the eastern foothills of the Bayankara Mountains. As the return period increases, the spatial distribution of snow disaster hazard probability shifts gradually from “double-core” to continuous distribution; and (3) the northwestern Karakorum Mountains and Bayankara Mountains are two distinct high-risk areas for snow disasters. The range of high-risk areas in the region expands with an increase in the return period.

Osteoarthritis (OA) and major depressive disorder (MDD) share inflammatory and oxidative stress pathways, but the role of programmed cell death (PCD) in their comorbidity remains unclear. This study used independent OA synovial and MDD peripheral blood transcriptomic datasets-not a unified comorbid discovery cohort-to identify candidate PCD-related molecular signatures commonly dysregulated in both conditions. Transcriptomic data from OA synovium and MDD brain tissues were obtained from GEO (six training [three OA synovial and three MDD peripheral-blood], seven validation, and two single-cell RNA-seq datasets). Differentially expressed genes (DEGs) were identified, and PCD-related DEGs were screened. Machine learning (LASSO, SVM-RFE, Random Forest) was used to identify hub PCD-DEGs from the OA training set. WGCNA identified MDD-associated modules for comorbidity-gene selection. Functional enrichment, immune infiltration, scRNA-seq localization, and clinical validation (qRT-PCR/WB) were performed. From the OA cohort, four hub PCD-DEGs (CDKN1A, CX3CR1, INHBB, RHOB) showed moderate diagnostic value for OA (nomogram AUC = 0.82). Eight candidate genes (VAMP8, PDK4, P2RX4, ITM2C, IL10RA, HSP90AA1, CTSO, CRIP1) were commonly dysregulated across both OA and MDD datasets. Immune infiltration revealed upregulated B memory cells, plasma cells, Tregs, and neutrophils in OA, and neutrophils in MDD. scRNA-seq localized CDKN1A/RHOB to OA synovial cells and HSP90AA1/ITM2C to MDD neurons. Enrichment analyses highlighted TNF signaling, apoptosis, and stress responses in both diseases. An independent OA-MDD clinical cohort confirmed differential expression of CDKN1A, RHOB, ITM2C, and HSP90AA1. This study identifies four PCD-related hub genes associated with OA and eight candidate comorbidity genes showing common dysregulation across OA and MDD datasets and in an independent clinical cohort. These findings generate hypotheses about shared inflammatory pathways linking OA and MDD. As these associations derive from independent disease-specific cohorts rather than a true comorbid discovery cohort, they represent candidate signatures requiring functional validation rather than established mechanisms.

Preserved ratio impaired spirometry (PRISm) is a common but understudied abnormal pulmonary function state and is strongly associated with poor health outcomes. However, there is a lack of uniformity in defining the factors and pulmonary function outcomes associated with PRISm. This scoping review aims to elucidate the associated factors and pulmonary function outcomes of PRISm, thereby enhancing healthcare professionals' understanding of PRISm and laying the groundwork for its prevention and treatment. This scoping review follows the 5-step framework developed by Arksey and O'Malley. Literature on PRISm was systematically searched from databases including PubMed, Embase, CINAHL, the Cochrane Library, Web of Science, CNKI, and Wan Fang, spanning from inception to July 2024. Inclusion and exclusion criteria were applied to enroll relevant studies. Data were extracted, collected, summarized, and reported. A total of 38 studies were included. The analysis revealed that associated factors for PRISm encompass possible pathogenic factors (older age, female, lower education level, smoking, obesity, etc), comorbidity associations (asthma, diabetes, cardiovascular diseases, etc), and disease characteristic factors (disease burden, physical performance, radiological characteristics, etc). The pulmonary function status of the PRISm population is unstable, making progression to airflow obstruction (AFO) more likely than in the normal population. PRISm exhibits multiple subgroups (incident or stable PRISm, definite PRISm or PRISm with AFO, non-restrictive or restrictive PRISm, etc) and significant differences exist in pulmonary function outcomes among different subgroups. This scoping review offers a more comprehensive understanding of PRISm. It is recommended that future research focus on a deeper investigation of the pulmonary function of PRISm, elucidating its pathophysiological characteristics, and proposing new strategies for its prevention and treatment. Furthermore, more research is needed in low-income and middle-income economies to understand PRISm comprehensively.

In this study, an optimized nanostructured lipid carriers (NLCs) were developed and investigated for improving the solubility and oral availability of 6-Gingerol (6G), an active and abundant component of ginger with limited applications due to its poor water solubility plus oral biological availability. The NLCs consisted of a solid lipid (glyceryl monostearate), another liquid lipid (decanoyl/octanoyl-glycerides) and mixed surfactants (Tween 80 and Poloxamer 188), and was prepared by high pressure homogenization method. The optimal 6G-NLC formulation was evaluated through physical properties such as appearance, mean particle size, zeta potential, encapsulation efficiency, and in vitro drug release, alongside techniques viz. , transmission electron microscopy (TEM), differential scanning calorimetry (DSC), as well as powder X-ray diffraction (XRD). Pharmacokinetics were also evaluated in rats. The 6G-NLCs prepared with optimal formulation exhibited a homogenous spherical shape with mean particle size and zeta potential of 63.59 ± 5.54 nm and − 12.18 ± 1.06 mV. Encapsulation efficiency and drug loading were 76.71 ± 1.11 and 1.17 ± 0.35%, respectively. In vitro release profile of 6G from NLCs was sustained and fitted with Weibull equation. After oral administration of the 6G-NLCs, drug concentrations in serum, MRT, and AUC 0-t were significantly higher as compared with the free 6G suspension. All these results indicated that the developed NLC formulation could be effective and promising drug carriers to improve the water solubility of 6G while sustaining the drug release as well as prolonging in vivo acting time of the drug coupled with oral bioavailability enhancement.

The low-density lipoprotein cholesterol (LDL-C)/(high-density lipoprotein C (HDL-C) + direct bilirubin (DBIL)) ratio has been linked to the development of atherosclerosis. However, the association of this ratio with clinical outcomes in patients with prior coronary artery bypass grafting (CABG) undergoing percutaneous coronary intervention (PCI) remains unclear. Therefore, this study aimed to explore whether the LDL/(HDL + DBIL) ratio is predictive of clinical outcomes in this patient group. We retrospectively reviewed 1352 patients who underwent re-PCI after CABG surgery and categorized the patients into three groups based on the third quartile of the ratio levels. The primary endpoint was major adverse cardiovascular and cerebrovascular events (MACCE), defined as a composite of all-cause death, stroke, myocardial infarction, or target vessel revascularization. During the follow-up period, the occurrence rate of MACCE in the high ratio group was significantly higher than that in the low to moderate ratio groups (9.9% vs. 11.4% vs. 20.1%; < 0.001). This trend was consistent for cardiac death (6.2% vs. 6.2% vs. 9.8%; = 0.021) and non-fatal myocardial infarction (3.2% vs. 4.0% vs. 7.4%; = 0.003). After adjusting for other risk factors, Cox multiple regression analysis suggested that LDL-C/(HDL-C + DBIL) remained significantly correlated with MACCE (hazard ratio (HR) = 1.33, 95% confidence interval (CI): 1.186-1.193; < 0.001) with the high ratio group having the highest risk (HR = 2.331, 95% CI: 1.585-3.427; < 0.001). According to the subgroup analysis, the selection of bypass graft or native vascular PCI did not affect the relationship between the ratio and the occurrence of MACCE. The LDL-C/(HDL-C + DBIL) ratio level is closely related to the risk of long-term MACCE in patients undergoing PCI after CABG surgery, and the LDL-C/(HDL-C + DBIL) level can be an important indicator for post-PCI risk assessment.

This study aims to identify the heterogeneous trajectories of inhaled medication adherence in COPD patients while examining their associated factors and exploring the longitudinal correlation between variables, so as to provide the basis for precise intervention. Adopting convenience sampling, chronic obstructive pulmonary disease (COPD) patients hospitalized at The First Affiliated Hospital of Guangzhou Medical University between December 2023 and September 2024 were recruited. General information, Test of the Adherence to Inhalers (TAI; scores of 50 indicate high adherence, 46-49 moderate adherence, and ≤45 low adherence), Chronic Obstructive Pulmonary Disease Knowledge Questionnaire (COPD-Q), Beliefs about Medicines Questionnaire-Specific (BMQ-Specific), Hospital Anxiety and Depression Scale (HADS), and Perceived Social Support Scale (PSSS) were assessed at hospitalization (T0) and 1 month (T1), 3 months (T2), and 6 months (T3) after discharge. The Group-Based Trajectory Model was employed to identify inhaled medication adherence trajectories. Associated factors of trajectories were determined using multinomial logistic regression, and the longitudinal association between variables was explored by the Group-Based Dual Trajectory Model. A total of 207 patients with COPD completed follow-up. The number and proportion of COPD patients with \"medium-low adherence\" showed a significant decrease from T0 to T1, followed by an increase from T1 to T3. Trajectories of inhaled medication adherence in COPD patients can be categorised into four classes: \"high adherence-persisting group\" (50.4%), \"medium-low adherence-persisting group\" (18.4%), \"low adherence rising-persisting group\" (15.0%), and \"low adherence rising- declining group\" (16.3%). Duration of inhalation device use, health literacy, beliefs about medicines, anxiety, and perceived social support were associated factors of trajectories of inhaled medication adherence ( < 0.05), with a significant positive correlation between trajectories of inhaled medication adherence and trajectories of beliefs about medicines. Nearly one-third of COPD patients exhibited poor inhaled medications adherence after discharge, with one month post-discharge serving as a critical turning point. Healthcare providers should prioritize monitoring adherence changes during this period. Four heterogeneous adherence trajectories were identified. Factors influencing each trajectory included: duration of inhaler device use ≤2 years, low level of health literacy, low level of beliefs about medicines, high level of anxiety, and low level of perceived social support. Early screening of these populations and implementation of targeted strategies are essential to enhance precision management.

In this work, poly(ethylene glycol) (PEG)/boron nitride nanosheets (BNNS) masterbatch was prepared by freeze-drying their ultrasonically homogenized aqueous suspension, followed by melt-mixing with poly(lactic acid) (PLA) to fabricate the nanocomposites. The effect of PEG and BNNS on the crystallization behavior of PLA was investigated. The dynamic mechanical properties, thermal conductivity and thermal stability of the nanocomposites were also evaluated. It was found that, under quiescent conditions, PEG and BNNS had a synergistic effect on accelerating the nonisothermal crystallization of PLA. Unexpectedly, under injection molding conditions, the combination of PEG and BNNS had a negative effect on PLA crystallization. This can be ascribed to the plasticizing effect of PEG, which relaxes the orientation of PLA chains and retards flow-induced crystallization. Dynamic mechanical analysis (DMA) showed that the presence of BNNS enhanced the heat resistance of PLA only when PLA was crystallized, while further incorporation of PEG had a negative effect. Nevertheless, simultaneous use of PEG and BNNS had a synergistic effect on enhancing the thermal conductivity of PLA.