Understory planting of medicinal plants is a new planting mode that connects Chinese herbal medicine(CHM) with forest resources.The complex and variable understory environmental factors will inevitably affect the yield and quality of understory CHM.This research summarized the research progress on understory planting of medicinal plants based on forest types and environmental factors within the forest from the perspectives of understory light, air temperature and humidity, soil characteristics, and the interaction between crops within the forest.The results showed that the complex and variable light, temperature and humidity, and soil factors(such as fertility, acidity and alkalinity, and microorganisms) under the forest could affect the yield and quality of medicinal plants to varying degrees through physiological activities such as photosynthesis and respiration, resulting in a significant increase or decrease in yield and quality compared to open field cultivation.In addition, the competition or mutual benefit between different crops within the forest could lead to differences in the yield and quality of understory medicinal plants compared to open field cultivation.A reasonable combination of planting could achieve resource sharing and complementary advantages.Therefore, conducting systematic research on the effects of understory environmental factors on the yield and content of medicinal plants with different growth and development characteristics can provide theoretical guidance and technical references for formulating comprehensive strategies for understory planting of medicinal plants, such as selecting suitable medicinal plant varieties, optimizing planting density, and conducting reasonable forest management, thus contributing to the sustainable development and ecological protection of CHM.
Plants, Medicinal/growth & development* ; Forests ; Soil/chemistry* ; Environment ; Ecosystem ; Temperature

OBJECTIVE: To identify the underlying mechanism by which quercetin (Que) alleviates sepsis-related acute respiratory distress syndrome (ARDS). METHODS: In vivo, C57BL/6 mice were assigned to sham, cecal ligation and puncture (CLP), and CLP+Que (50 mg/kg) groups (n=15 per group) by using a random number table. The sepsisrelated ARDS mouse model was established using the CLP method. In vitro, the murine alveolar macrophages (MH-S) cells were classified into control, lipopolysaccharide (LPS), LPS+Que (10 μmol/L), and LPS+Que+acetylcysteine (NAC, 5 mmol/L) groups. The effect of Que on oxidative stress, inflammation, and apoptosis in mice lungs and MH-S cells was determined, and the mechanism with reactive oxygen species (ROS)/p38 mitogen-activated protein kinase (MAPK) pathway was also explored both in vivo and in vitro. RESULTS: Que alleviated lung injury in mice, as reflected by a reversal of pulmonary histopathologic changes as well as a reduction in lung wet/dry weight ratio and neutrophil infiltration (P<0.05 or P<0.01). Additionally, Que improved the survival rate and relieved gas exchange impairment in mice (P<0.01). Que treatment also remarkedly reduced malondialdehyde formation, superoxide dismutase and catalase depletion, and cell apoptosis both in vivo and in vitro (P<0.05 or P<0.01). Moreover, Que treatment diminished the release of inflammatory factors interleukin (IL)-1β, tumor necrosis factor-α, and IL-6 both in vivo and in vitro (P<0.05 or P<0.01). Mechanistic investigation clarifified that Que administration led to a decline in the phosphorylation of p38 MAPK in addition to the suppression of ROS expression (P<0.01). Furthermore, in LPS-induced MH-S cells, ROS inhibitor NAC further inhibited ROS/p38 MAPK pathway, as well as oxidative stress, inflammation, and cell apoptosis on the basis of Que treatment (P<0.05 or P<0.01). CONCLUSION Que was found to exert anti-oxidative, anti-inflammatory, and anti-apoptotic effects by suppressing the ROS/p38 MAPK pathway, thereby conferring protection for mice against sepsis-related ARDS.
Animals ; Sepsis/drug therapy* ; Quercetin/therapeutic use* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; Mice, Inbred C57BL ; Reactive Oxygen Species/metabolism* ; Apoptosis/drug effects* ; Male ; Oxidative Stress/drug effects* ; MAP Kinase Signaling System/drug effects* ; Lung/drug effects* ; Mice ; Lipopolysaccharides ; Macrophages, Alveolar/pathology* ; Inflammation/pathology* ; Protective Agents/therapeutic use*

Dendrobium moniliforme (D. moniliforme) is a traditional medicinal herb widely cultivated in Asia. Flavonoids, one of the largest groups of secondary metabolites in plants, are significant medicinal components in Dendrobium species. Several subgroups of R2R3-MYB proteins have been validated to directly regulate flavonoid biosynthesis. Using PacBio sequencing technology, we assembled a high-quality chromosome-level D. moniliforme genome with a total length of 1.20 Gb and a contig N50 of 3.97 Mb. The BUSCO assessment of genome annotation was 91.4%. By integrating the genome and transcriptome, we identified biosynthesis pathway enzyme genes related to flavonoids, polysaccharides, carotenoids, and alkaloids. A total of 90 R2R3-MYBs were identified in D. moniliforme and classified into 21 subgroups. Studies on the functions of R2R3-MYB transcription factors revealed that R2R3-MYB in SG6 can up-regulate flavonoid biosynthesis. Various validation experiments, including subcellular localization, transient overexpression, UPLC-MS/MS, HPLC, yeast one-hybrid, and dual-luciferase assays, demonstrated that DMYB69 directly up-regulates the expression of enzyme genes involved in flavonoid biosynthesis, increasing the content of flavonoids such as anthocyanin, flavone, and flavonol. Additionally, DMYB44 was shown to directly up-regulate the expression of carotenoid biosynthesis enzyme genes, thereby increasing carotenoid content. This study provides an essential genome resource and theoretical basis for molecular breeding research in D. moniliforme.

Background Non-optimal temperatures pose significant threats to public health. Analyzing the association between temperature exposure and the number of emergency cases of acute alcohol intoxication can provide evidence for optimizing emergency resource allocation and response strategies. Objective To analyze the overall impact and lag effects of non-optimal temperatures on the number of 120 emergency calls for acute alcohol intoxication in Wuxi, and to assess the attributable risk, in order to provide empirical evidence for formulating climate-adaptive public health strategies. Methods Call records of acute alcohol intoxication from Wuxi's 120 emergency service, concurrent air pollutant data, and meteorological data (including daily mean temperature) were collected from January 1, 2014 to December 31, 2020. Distributed lag nonlinear modeling was used for time-series analysis, with cross-basis functions to capture the nonlinear relationship and lag effects between temperature and emergency volume. Confounding factors such as long-term trends, humidity, pollutants [ultimately including ozone (O₃) and fine particulate matter (PM_2.5)], day of the week, and holidays were controlled. The maximum lag period was set to 14 days. Single-day lag and cumulative lag effects of extreme temperatures were analyzed, followed by sensitivity analysis. Effects were quantified using relative risk (RR) and 95% confidence intervals (95%CI), and attributable fractions and numbers for different temperature ranges were calculated. Results A total of 10705 emergency cases of acute alcohol intoxication were included during the study period, with males accounting for 89.5% and individuals aged 18–50 years accounting for 83.4%. A non-linear "U-shaped" association was observed between daily mean temperature and the number of emergency calls, with an optimal temperature of 13.3 ℃. The effect of the extreme low temperature (1.88 ℃) was statistically significant from lag1 to lag3 after exposure (P<0.05), with the maximum effect at lag1 (RR=1.063, 95%CI: 1.002, 1.129). The extreme high temperature (32.3 ℃) showed an immediate effect, with maximum effect at lag0 (RR=1.374, 95%CI: 1.248, 1.512). The cumulative effect analysis showed that the risk associated with high temperature was the highest at lag0–3 (RR=2.000, 95%CI: 1.667, 2.399), while the risk associated with low temperature was the highest at lag0–14 (RR=1.462, 95%CI: 1.042, 2.051). The attribution analysis indicated that the mild heat (>24.7–30.8 ℃) and heat (>30.8–33.5 ℃) contributed the largest numbers of attributable cases, with 591 cases (95%CI: 56, 1032) and 190 cases (95%CI: 51, 309), respectively. The corresponding attributable fractions were 5.81% (95%CI: 0.80%, 9.94%) and 1.87% (95%CI: 0.49%, 2.96%), respectively. Conclusion Both extreme high and low temperatures significantly increase the number of 120 emergency calls for acute alcohol intoxication in Wuxi. High temperature exhibit an acute effect, while low temperature show a delayed effect. Mild heat have a significant impact on the emergency burden. It is recommended that emergency departments optimize resource allocation according to climatic characteristics and strengthen emergency responses during extreme weather to reduce alcohol-related health burden.

Objective To explore the symptom clusters in renal transplant recipients and con-struct a concurrent symptom network to identify core symptoms.Methods A total of 343 patients with followed up after renal transplantation were selected as the study subjects.A general information questionnaire and the Chinese version of the Modified Transplant Symptom Occurrence and Symptom Distress Scale were employed to analyze the occurrence of symptoms in patients.In this study,only symptoms with an incidence rate greater than 20％and Spearman correlation coefficient greater than 0.40 between symptom severity and total score were retained.Exploratory factor analysis was used to extract symptom clusters with a factor loading of ≥0.45 as the criterion.The R language was utilized to construct symptom network,based on which core symptoms and bridge symptoms were identified.Results A total of 5 symptom clusters were extracted in this study:the neuro-gastrointestinal symp-tom cluster,the mood-related symptom cluster,the hormone-related symptom cluster,the energy de-ficiency symptom cluster and the vision-related symptom cluster.The core symptoms were anxiety(rs=1.75),mood swings(rs=1.50)and muscle weakness(rs=1.27).The top three symptoms in terms of bridge strength were muscle weakness(rb=0.87),lack of vitality(rb=0.66)and fa-tigue(rb=0.65).Conclusion Multiple symptoms are presented in patients after renal transplanta-tion.Based on the results of symptom network analysis,clinicians can strengthen the assessment of core symptoms and bridge symptoms to develop precise intervention strategies and improve the effectiveness of symptom management.

Background and aims:Despite growing evidence linking pretransplant exposure to immune checkpoint inhibitors(ICIs)to increased allograft rejection risk after liver transplantation(LT),a lack of comparative studies to definitively establish the correlation between ICI exposure and adverse short-term outcomes after LT exists.This study aimed to analyze the impact of preoperative ICI exposure on short-term post-LT prognosis and allograft rejection risk.Methods:This retrospective cohort study included 121 recipients who underwent LT for hepatocellular carcinoma(HCC)between June 2019 and March 2023.The recipients were categorized into ICI(n=35)and non-ICI(n=86)exposure groups based on pretransplant ICI exposure.Demographics,clinical characteristics,and short-term outcomes were compared between the cohorts.Kaplan-Meier analysis evaluated the impact of ICI exposure on graft survival.Univariate and multivariate logistic regression models assessed the impact of patient characteristics on allograft rejection.Results:Recipients with or without ICI exposure exhibited comparable demographic baseline charac-teristics.The incidences of early allograft dysfunction and biliary and vascular complications were similar between both groups.Post-transplant infection incidence was 37.1％and 20.9％in the ICI and non-ICI groups,respectively(P=0.064).Allograft rejection rates were significantly higher in the ICI group than in the non-ICI group(22.9％vs.5.8％,P=0.015).The ICI group exhibited a higher 90-day post-transplant mortality rate than that of the non-ICI group(14.3％vs.2.3％,P=0.034).Logistic regression analyses demonstrated that allograft rejection independently correlated with 90-day post-transplant mortality,with ICI exposure being an independent risk factor for allograft rejection.In recipients with ICI exposure,a shorter interval between ICIs and LT(washout period)was significantly associated with a higher allograft rejection risk,with the optimal washout period identified as 21 days for predicting 90-day rejection-free survival(P=0.0001).Moreover,in recipients with allograft rejection,the peripheral CD4+/CD8+T cell ratio was much lower in the ICI group than in the non-ICI group.Conclusions:Pretransplant ICI exposure was an independent risk factor for allograft rejection and was significantly associated with 90-day post-transplant mortality after LT for HCC.A ≤21-day washout period was significantly associated with allograft rejection.Future multicenter studies with larger cohorts and prospective designs are essential to validate these findings,confirm causality,and establish standardized clinical guidelines for ICI use before transplantation.Trail registration:ClinicalTrials.gov NCT05913583.

Objective Performing physical tasks in the low-pressure environment of space poses a significant physiological challenge for astronauts.This study investigates the localized thermophysiological effects of typical physical tasks on different body segments and analyzes the mechanisms by which low-pressure environments influence human task performance.The findings aim to provide a theoretical basis for the thermal control design of spacesuits,focusing on both localized thermoregulation and overall task performance.Methods Two typical physical tasks—15 kg weighted walking and 25 kg load-carrying—were conducted in a simulated low-pressure composite environment chamber.The chamber was set to an altitude-equivalent pressure of 57 kPa(4500 m),with a temperature of 26℃and humidity of 40％.Six non-acclimatized adult male participants were recruited.After environmental stabilization,12-point skin temperatures were recorded throughout the tasks,and localized temperature data were statistically analyzed.Results Under low-pressure conditions,different body regions exhibited distinct thermal responses over time depending on the task type,while the same body region showed varied responses under different task conditions.During walking,temperatures in the primary active regions(thighs and calves)decreased,with most other body regions(except the pelvis and feet)gradually cooling as the task progressed.In contrast,during load-carrying,temperatures in the primary active regions(back and upper arm muscles)increased significantly.Conclusion Astronauts performing different tasks in low-pressure environments experience distinct localized thermophysiological effects.Therefore,spacesuit thermal control systems should not only account for task intensity and metabolic differences but also adapt localized heating/cooling based on task-specific thermal profiles.This approach enables targeted intelligent thermal regulation,enhancing operational support in specific mission scenarios.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Geraniin, a polyphenol derived from the fruit peel of Nephelium lappaceum L., has been shown to possess anti-inflammatory and antioxidant properties in the cardiovascular system. The present study explored whether geraniin could protect against an isoproterenol (ISO)-induced cardiac hypertrophy model. Mice in the ISO group received an intraperitoneal injection of ISO (5 mg/kg) once daily for 9 days, and the administration group were injected with ISO after 5 days of treatment with geraniin or spironolactone. Potential therapeutic effects and related mechanisms analysed by anatomical coefficients, histopathology, blood biochemical indices, reverse transcription-PCR and immunoblotting. Geraniin decreased the cardiac pathologic remodeling and myocardial fibrosis induced by ISO, as evidenced by the modifications to anatomical coefficients, as well as the reduction in collagen I/III á1mRNA and protein expression and cross-sectional area in hypertrophic cardiac tissue. In addition, geraniin treatment reduced ISO-induced increase in the mRNA and protein expression levels of interleukin (IL)-6, IL-1β and tumor necrosis factor-α, whereas ISO-induced IL-10 showed the opposite behaviour in hypertrophic cardiac tissue.Further analysis showed that geraniin partially reversed the ISO-induced increase in malondialdehyde and nitric oxide, and the ISO-induced decrease in glutathione, superoxide dismutase and glutathione. Furthermore, it suppressed the ISO-induced cellular apoptosis of hypertrophic cardiac tissue, as evidenced by the decrease in Bcell lymphoma-2 (Bcl-2)-associated X/caspase-3/caspase-9 expression, increase in Bcl-2 expression, and decrease in TdT-mediated dUTP nick-end labeling-positive cells.These findings suggest that geraniin can attenuate ISO-induced cardiac hypertrophy by inhibiting inflammation, oxidative stress and cellular apoptosis.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.