Phosphorus addition enhances heterotrophic respiration but reduces root respiration in a subtropical plantation forest.

Soil respiration (Rs) is a major component of the global carbon (C) cycle and is influenced by the availability of nutrients such as phosphorus (P). However, the response of Rs to P addition in P-limited subtropical forest ecosystems and the underlying mechanisms remain poorly understood. To address this, we conducted a P addition experiment (50 kg P ha-1 yr-1) in a subtropical Chinese fir (Cunninghamia lanceolata) plantation forest. We separated Rs into heterotrophic respiration (Rh), root respiration (Rr), and mycorrhizal hyphal respiration (Rm), and quantified soil properties, microbial biomass (phospholipid fatty acid, PLFA), fungal community composition (ITS), and the activity of extracellular enzymes. Phosphorus addition significantly increased Rs and Rh, but decreased Rr and did not influence Rm. Further, P addition increased fungal, bacterial, and total PLFAs, and phenol oxidase activity. Conversely, P application decreased root biomass and did not alter the relative abundance of symbiotrophic fungi. Phosphorus enrichment therefore enhances soil C emissions by promoting organic matter decomposition by heterotrophic activity, rather than via increases in root or mycorrhizal respiration. This advances our mechanistic understanding of the relationship between fertility and soil respiration in subtropical forests, with implications for predicting soil C emissions under global change.

Functional type mediates the responses of root litter-driven priming effect and new carbon formation to warming.

Input of root litter can alter soil organic carbon (SOC) dynamics via causing priming effect (PE) on native SOC decomposition and forming new SOC. However, it is unknown how functional type mediates the root litter-driven PE and new C formation as well as their response to warming, which are of pivotal for soil C budget. We mixed litter segments of absorptive roots and transport roots from a Chinese fir (Cunninghamia lanceolata) plantation into isotopically distinct soil and incubated at 19°C (local mean annual temperature) and 23°C (warming by 4°C) for 210 days. Cumulative PE was calculated via integrating the instantaneous PE rates during the incubation. And the newly formed root litter-derived SOC (SOCrl) was calculated by measuring the δ13C value of soil at the end of incubation using a two-source mixed model. We found that absorptive roots with faster decomposition rates, caused significantly higher cumulative PE and SOCrl than transport roots. The microbial biomass and enzyme activities involved in C, N and P acquisition were significantly higher in the absorptive- than the transport roots addition treatment, indicating a higher level of microbial activation caused by absorptive roots. Although warming significantly increased the litter decomposition for both of functional types, while just significantly increased the PE of transport roots, indicating a root functional type dependent sensitivity of PE to warming. However, warming had no significant effect on SOCrl either for absorptive roots or for transport roots. As a consequence, warming relatively decreased the net SOC balance (difference between PE and SOCrl) in the transport roots addition treatment. Overall, our study highlights, for the first time, that functional type primarily mediates the response of root litter-driven PE to climate warming but not the new C formation, which may advance our understanding of SOC dynamics in Chinese fir plantation under climate change.

Identification of potential therapeutic targets for plaque vulnerability based on an integrated analysis.

BACKGROUND AND AIMS: This study aimed to explore potential hub genes and pathways of plaque vulnerability and to investigate possible therapeutic targets for acute coronary syndrome (ACS). METHODS AND RESULTS: Four microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), weighted gene coexpression networks (WGCNA) and immune cell infiltration analysis (IIA) were used to identify the genes for plaque vulnerability. Then, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, Disease Ontology, Gene Ontology annotation and protein-protein interaction (PPI) network analyses were performed to explore the hub genes. Random forest and artificial neural networks were constructed for validation. Furthermore, the CMap and Herb databases were employed to explore possible therapeutic targets. A total of 168 DEGs with an adjusted P < 0.05 and approximately 1974 IIA genes were identified in GSE62646. Three modules were detected and associated with CAD-Class, including 891 genes that can be found in GSE90074. After removing duplicates, 114 hub genes were used for functional analysis. GO functions identified 157 items, and 6 pathways were enriched for the KEGG pathway at adjusted P < 0.05 (false discovery rate, FDR set at < 0.05). Random forest and artificial neural network models were built based on the GSE48060 and GSE34822 datasets, respectively, to validate the previous hub genes. Five genes (GZMA, GZMB, KLRB1, KLRD1 and TRPM6) were selected, and only two of them (GZMA and GZMB) were screened as therapeutic targets in the CMap and Herb databases. CONCLUSION: We performed a comprehensive analysis and validated GZMA and GZMB as a target for plaque vulnerability, which provides a therapeutic strategy for the prevention of ACS. However, whether it can be used as a predictor in blood samples requires further experimental verification.

Association of serum metal levels with type 2 diabetes: A prospective cohort and mediating effects of metabolites analysis in Chinese population.

Several studies have suggested an association between exposure to various metals and the onset of type 2 diabetes (T2D). However, the results vary across different studies. We aimed to investigate the associations between serum metal concentrations and the risk of developing T2D among 8734 participants using a prospective cohort study design. We utilized inductively coupled plasmamass spectrometry (ICP-MS) to assess the serum concentrations of 27 metals. Cox regression was applied to calculate the hazard ratios (HRs) for the associations between serum metal concentrations on the risk of developing T2D. Additionally, 196 incident T2D cases and 208 healthy control participants were randomly selected for serum metabolite measurement using an untargeted metabolomics approach to evaluate the mediating role of serum metabolite in the relationship between serum metal concentrations and the risk of developing T2D with a nested casecontrol study design. In the cohort study, after Bonferroni correction, the serum concentrations of zinc (Zn), mercury (Hg), and thallium (Tl) were positively associated with the risk of developing T2D, whereas the serum concentrations of manganese (Mn), molybdenum (Mo), barium (Ba), lutetium (Lu), and lead (Pb) were negatively associated with the risk of developing T2D. After adding these eight metals, the predictive ability increased significantly compared with that of the traditional clinical model (AUC: 0.791 vs. 0.772, P=8.85×10-5). In the nested casecontrol study, a machine learning analysis revealed that the serum concentrations of 14 out of 1579 detected metabolites were associated with the risk of developing T2D. According to generalized linear regression models, 7 of these metabolites were significantly associated with the serum concentrations of the identified metals. The mediation analysis showed that two metabolites (2-methyl-1,2-dihydrophthalazin-1-one and mestranol) mediated 46.81% and 58.70%, respectively, of the association between the serum Pb concentration and the risk of developing T2D. Our study suggested that serum Mn, Zn, Mo, Ba, Lu, Hg, Tl, and Pb were associated with T2D risk. Two metabolites mediated the associations between the serum Pb concentration and the risk of developing T2D.

TO-UGDA: target-oriented unsupervised graph domain adaptation.

Graph domain adaptation (GDA) aims to address the challenge of limited label data in the target graph domain. Existing methods such as UDAGCN, GRADE, DEAL, and COCO for different-level (node-level, graph-level) adaptation tasks exhibit variations in domain feature extraction, and most of them solely rely on representation alignment to transfer label information from a labeled source domain to an unlabeled target domain. However, this approach can be influenced by irrelevant information and usually ignores the conditional shift of the downstream predictor. To effectively address this issue, we introduce a target-oriented unsupervised graph domain adaptive framework for graph adaptation called TO-UGDA. Particularly, domain-invariant feature representations are extracted using graph information bottleneck. The discrepancy between two domains is minimized using an adversarial alignment strategy to obtain a unified feature distribution. Additionally, the meta pseudo-label is introduced to enhance downstream adaptation and improve the model's generalizability. Through extensive experimentation on real-world graph datasets, it is proved that the proposed framework achieves excellent performance across various node-level and graph-level adaptation tasks.

Soil warming-induced reduction in water content enhanced methane uptake at different soil depths in a subtropical forest.

Global warming can significantly impact soil CH4 uptake in subtropical forests due to changes in soil moisture, temperature sensitivity of methane-oxidizing bacteria (MOB), and shifts in microbial communities. However, the specific effects of climate warming and the underlying mechanisms on soil CH4 uptake at different soil depths remain poorly understood. To address this knowledge gap, we conducted a soil warming experiment (+4 °C) in a natural forest. From August 2020 to October 2021, we measured soil temperature, soil moisture, and CH4 uptake rates at four different soil depths: 0-10 cm, 10-20 cm, 20-40 cm, and 40-60 cm. Additionally, we assessed the soil MOB community structure and pmoA gene (with qPCR) at the 0-10 and 10-20 cm depths. Our findings revealed that warming significantly enhanced soil net CH4 uptake rate by 12.28 %, 29.51 %, and 61.05 % in the 0-10, 20-40, and 40-60 cm soil layers, respectively. The warming also led to reduced soil moisture levels, with more pronounced reductions observed at the 20-40 cm depth compared to the 0-20 cm depth. At the 0-10 cm depth, warming increased the relative abundance of upland soil cluster α (a type of MOB) and decreased the relative abundance of Methylocystis, but it did not significantly increase the pmoA gene copies. Our structural equation model analysis indicated that warming directly regulated soil CH4 uptake rate through the decrease in soil moisture, rather than through changes in the pmoA gene and MOB community structure at the 0-20 cm depth. In summary, our results demonstrate that warming enhances soil CH4 uptake at different depths, with soil moisture playing a crucial role in this process. Under warming conditions, the drier soil pores allow for better CH4 penetration, thereby promoting more efficient activity of MOB.

Genome-Driven Discovery of Hygrocins in Streptomyces rapamycinicus.

Ansamycins, represented by the antituberculosis drug rifamycin, are an important family of natural products. To obtain new ansamycins, Streptomyces rapamycinicus IMET 43975 harboring an ansamycin biosynthetic gene cluster was fermented in a 50 L scale, and subsequent purification work led to the isolation of five known and four new analogues, where hygrocin W (2) belongs to benzoquinonoid ansamycins, and the other three hygrocins, hygrocins X-Z (6-8), are new seco-hygrocins. The structures of ansamycins (1-8) were determined by the analysis of spectroscopic (1D/2D NMR and ECD) and MS spectrometric data. The Baeyer-Villiger enzyme which catalyzed the ester formation in the ansa-ring was confirmed through in vivo CRISPR base editing. The discovery of these compounds further enriches the structural diversity of ansamycins.

Osteoarthritis and hypertension: observational and Mendelian randomization analyses.

BACKGROUND: The association between osteoarthritis (OA) and hypertension is a subject of ongoing debate in observational research, and the underlying causal relationship between them remains elusive. METHODS: This study retrospectively included 24,871 participants in the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2020. Weighted logistic regression was performed to investigate the connection between OA and hypertension. Additionally, Mendelian randomization (MR) analysis was conducted to explore the potential causal relationship between OA and hypertension. RESULTS: In the NHANES data, after adjusting for multiple confounding factors, there was no significant relationship between OA and hypertension (OR 1.30, 95% CI, 0.97-1.73, P = 0.089). However, among males, OA appeared to be associated with a higher risk of hypertension (OR 2.25, 95% CI, 1.17-4.32, P = 0.019). Furthermore, MR results indicate no relationship between multiple OA phenotypes and hypertension: knee OA (IVW, OR 1.024, 95% CI: 0.931-1.126, P = 0.626), hip OA (IVW, OR 0.990, 95% CI: 0.941-1.042, P = 0.704), knee or hip OA (IVW, OR 1.005, 95% CI: 0.915-1.105, P = 0.911), and OA from UK Biobank (IVW, OR 0.796, 95% CI: 0.233-2.714, P = 0.715). Importantly, these findings remained consistent across different genders and in reverse MR. CONCLUSIONS: Our study found that OA patients had a higher risk of hypertension only among males in the observational study. However, MR analysis did not uncover any causal relationship between OA and hypertension.

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In order to understand the response and adaptation mechanisms of photosynthetic characteristics and growth for Cunninghamia lanceolata saplings in the subtropical region to global warming, we conducted the root-box warming experiment (ambient, ambient+4 ℃) at the Sanming Forest Ecosystem National Observation and Research Station in Fujian Province to investigate the effects of soil warming on the photosynthetic characteristics and growth of C. lanceolata saplings in different seasons. The results showed that the net photosynthetic rate (Pn) and stomatal conductance (gs) of C. lanceolata significantly decreased in summer compared with in spring and autumn. Soil warming had no effect on the Pn and gs of C. lanceolata. However, the interaction between warming and season significantly impacted the leaf water use efficiency (WUE). The tree height and ground diameter growth of C. lanceolata significantly increased in spring compared with in summer and autumn. Warming significantly reduced ground diameter growth, and it diminished the net diameter growth by 48.1% in autumn. However, warming had no impact on the tree height growth of C. lanceolata in each season. The specific leaf area, soluble sugar, and non-structural carbohydrates contents of C. lanceolata significantly improved in summer and autumn compared with in spring. Warming had rarely influence on leaf functional traits in each season. In conclusion, the response of photosynthesis for C. lanceolata to soil warming was insignificant. The photosynthesis of C. lanceolata exhibited significant seasonal dynamics, primarily controlled by gs. C. lanceolata adapted to soil warming by adjusting WUE, and it adjusted to high temperatures and drought stress in summer by increasing soluble sugar content and specific leaf area. The effect of warming on ground diameter growth of C. lanceolata was primarily driven by soil moisture. The seasonal difference in the growth of C. lanceolata was influenced by the photosynthesis of C. lanceolata and the trade-off between the utilization and storage of photosynthetic products.

Machine learning and experimental validation identified autophagy signature in hepatic fibrosis.

Background: The molecular mechanisms of hepatic fibrosis (HF), closely related to autophagy, remain unclear. This study aimed to investigate autophagy characteristics in HF. Methods: Gene expression profiles (GSE6764, GSE49541 and GSE84044) were downloaded, normalized, and merged. Autophagy-related differentially expressed genes (ARDEGs) were determined using the limma R package and the Wilcoxon rank sum test and then analyzed by GO, KEGG, GSEA and GSVA. The infiltration of immune cells, molecular subtypes and immune types of healthy control (HC) and HF were analyzed. Machine learning was carried out with two methods, by which, core genes were obtained. Models of liver fibrosis in vivo and in vitro were constructed to verify the expression of core genes and corresponding immune cells. Results: A total of 69 ARDEGs were identified. Series functional cluster analysis showed that ARDEGs were significantly enriched in autophagy and immunity. Activated CD4 T cells, CD56bright natural killer cells, CD56dim natural killer cells, eosinophils, macrophages, mast cells, neutrophils, and type 17 T helper (Th17) cells showed significant differences in infiltration between HC and HF groups. Among ARDEGs, three core genes were identified, that were ATG5, RB1CC1, and PARK2. Considerable changes in the infiltration of immune cells were observed at different expression levels of the three core genes, among which the expression of RB1CC1 was significantly associated with the infiltration of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. In the mouse liver fibrosis experiment, ATG5, RB1CC1, and PARK2 were at higher levels in HF group than those in HC group. Compared with HC group, HF group showed low positive area in F4/80, IL-17 and CD56, indicating decreased expression of macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell. Meanwhile, knocking down RB1CC1 was found to inhibit the activation of hepatic stellate cells and alleviate liver fibrosis. Conclusion: ATG5, RB1CC1, and PARK2 are promising autophagy-related therapeutic biomarkers for HF. This is the first study to identify RB1CC1 in HF, which may promote the progression of liver fibrosis by regulating macrophage, Th17 cell, natural killer cell and CD56dim natural killer cell.

Extracellular matrix stiffness as an energy metabolism regulator drives osteogenic differentiation in mesenchymal stem cells.

The biophysical factors of biomaterials such as their stiffness regulate stem cell differentiation. Energy metabolism has been revealed an essential role in stem cell lineage commitment. However, whether and how extracellular matrix (ECM) stiffness regulates energy metabolism to determine stem cell differentiation is less known. Here, the study reveals that stiff ECM promotes glycolysis, oxidative phosphorylation, and enhances antioxidant defense system during osteogenic differentiation in MSCs. Stiff ECM increases mitochondrial fusion by enhancing mitofusin 1 and 2 expression and inhibiting the dynamin-related protein 1 activity, which contributes to osteogenesis. Yes-associated protein (YAP) impacts glycolysis, glutamine metabolism, mitochondrial dynamics, and mitochondrial biosynthesis to regulate stiffness-mediated osteogenic differentiation. Furthermore, glycolysis in turn regulates YAP activity through the cytoskeletal tension-mediated deformation of nuclei. Overall, our findings suggest that YAP is an important mechanotransducer to integrate ECM mechanical cues and energy metabolic signaling to affect the fate of MSCs. This offers valuable guidance to improve the scaffold design for bone tissue engineering constructs.

Causal Relationship Between Immune Cells/Cytokines and Dilated Cardiomyopathy.

To date, whether there is any causal relationship between dilated cardiomyopathy (DCM) and the changes in the levels/expression of immune cells/cytokines is still unclear. This study aimed to investigate the causal relationship between the levels of various types of immune cells/cytokines and DCM. Herein, two-sample Mendelian randomization (MR) (TSMR) using R software was conducted. Single nucleotide polymorphisms (SNPs) related to the levels of various types of immune cells/cytokines and DCM were screened based on the genome-wide association studies (GWAS) obtained from open-source databases. The TSMR was conducted using inverse variance weighted (IVW), method, MR-Egger regression, weighted median method, and simple estimator based on mode to explore the causal association between the levels of each immune cell/cytokine and DCM. Sensitivity analysis was conducted using MR-Egger regression and a leave-one-out sensitivity test. A total of 1816 SNPs related to host immune status and DCM were identified. The IVW results showed a relationship between DCM and the circulating levels of basophils/eosinophils, total eosinophils-basophils, lymphocytes, and C-reactive protein (CRP). Increased lymphocytes levels (odds ratio (OR) = 0.91, 95% confidence interval (CI): 0.84-0.97, P = 0.005) were seen as protective against DCM, whereas increased basophil (OR = 1.18, 95% CI: 1.04-1.33, P = 0.022), eosinophil (OR = 1.1, 95% CI: 1.03-1.17, P = 0.007), eosinophil-basophil (OR = 1.09, 95% CI: 1.02-1.17, P = 0.014), and CRP (OR = 1.1, 95% CI: 1.03-1.18, P = 0.013) levels were associated with an increased risk of DCM. These analyses revealed that there may be a relationship between immune cells/select cytokine status and the onset of DCM. Future studies are required to further validate these outcomes in animal models and clinical trials.

Mechanical memory based on chromatin and metabolism remodeling promotes proliferation and smooth muscle differentiation in mesenchymal stem cells.

Stem cells respond and remember mechanical cues from the microenvironment, which modulates their therapeutic effects. Chromatin organization and energy metabolism regulate the stem cell fate induced by mechanical cues. However, the mechanism of mechanical memory is still unclear. This study aimed to investigate the effects of mechanical amplitude, frequency, duration, and stretch cycle on mechanical memory in mesenchymal stem cells. It showed that the amplitude was the dominant parameter to the persistence of cell alignment. F-actin, paxillin, and nuclear deformation are more prone to be remolded than cell alignment. Stretching induces transcriptional memory, resulting in greater transcription upon subsequent reloading. Cell metabolism displays mechanical memory with sustained mitochondrial fusion and increased ATP production. The mechanical memory of chromatin condensation is mediated by histone H3 lysine 27 trimethylation, leading to much higher smooth muscle differentiation efficiency. Interestingly, mechanical memory can be transmitted based on direct cell-cell interaction, and stretched cells can remodel the metabolic homeostasis of static cells. Our results provide insight into the underlying mechanism of mechanical memory and its potential benefits for stem cell therapy.

Molecular Stacking Dependent Molecular Oxygen Activation in Supramolecular Polymeric Photocatalysts.

Here, we showed that supramolecular assemblies based on perylene diimides (PDIs) are able to activate molecular oxygen through both the electron transfer and energy transfer pathways, which consequently leads to the formation of superoxide radicals (·O2-) and singlet oxygen species (1O2), respectively. These reactive oxygen species (ROS) can effectively lead to oxidative coupling of benzylamine and oxidation of 2-chloroethyl sulfide (CEES). We have designed and synthesized PDIs with similar molecular structures yet differing by the molecular stacking modes. We found that the photooxidation activities of the PDI supramolecular assemblies are inversely associated with the photoluminescence wavelength difference between the assemblies and the monomers (Δλ) quantitatively, and a smaller Δλ results in a higher catalytic efficiency accordingly. Overall, this work contributes to the design and fabrication of high performance photocatalysts based on metal-free organic materials.

Passive exercise is an effective alternative to HRT for restoring OVX induced mitochondrial dysfunction in skeletal muscle.

Background: Postmenopausal women are more prone to develop muscle weakness, which is strongly associated with impairment of mitochondrial function in skeletal muscle. This study aimed to examine the impact of a passive exercise modality, whole-body vibration training (WBVT), on muscle mitochondrial function in ovariectomized (OVX) mice, in comparison with 17ß-estradiol (E2) replacement. Methods: Female C57BL/6J mice were assigned to four groups: sham operation control group (Sham), ovariectomized group (OVX), OVX with E2 supplement group (OVX+E), and OVX with WBVT group (OVX+W). The estrous cycle, body weight, body composition, and muscle strength of the mice were monitored after the operation. Serum E2 level was assessed by enzyme-linked immunosorbent assay (ELISA). The ATP levels were determined using a luciferase-catalyzed bioluminescence assay. The activity of mitochondrial respiration chain complexes was evaluated using high-resolution respirometry (O2K). Expression levels of oxidative phosphorylation (OXPHOS), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α), and mitochondrial transcription factor A (TFAM) were detected using western blotting. Results: We observed decreased muscle strength and impaired mitochondrial function in the skeletal muscle of OVX mice. The vibration training alleviated these impairments as much as the E2 supplement. In addition, the vibration training was superior to the ovariectomy and the estradiol replacement regarding the protein expression of PGC-1α and TFAM. Conclusion: WBVT improves the OVX-induced decline in muscle strength and impairment of mitochondrial function in the skeletal muscle. This passive exercise strategy may be useful as an alternative to E2 replacement for preventing menopausal muscular weakness. Further studies are needed to understand the effects of WBVT on various physiological systems, and precautions should be taken when implementing it in patient treatment.

Characterization and in-vitro assessment of silicon-based apatite microspheres for bone tissue engineering applications.

In the field of bone tissue engineering, silicon (Si) has been found as an essential element for bone growth. However, the use of silicon in bioceramics microspheres remains limited. In this work, different weight percentages (0.8, 1.6, and 2.4 wt %) of silicon was incorporated into hydroxyapatite and fabricated into microspheres. 2.4 wt % of Si incorporated into HAp microspheres (2.4 SiHAp) were found to enhance functional properties of the microspheres which resulted in improved cell viability of human mesenchymal stem cells (hMSCs), demonstrating rapid cell proliferation rates resulting in high cell density accumulated on the surface of the microspheres which in turn permitted better hMSCs differentiation into osteoblasts when validated by bone marker assays (Type I collagen, alkaline phosphatase, osteocalcin, and osteopontin) compared to apatite microspheres of lower wt % of Si incorporated and non-substituted HAp (2.4 SiHAp >1.6 SiHAp >0.8 SiHAp > HAp). SEM images displayed the densest cell population on 2.4 SiHAp surfaces with the greatest degree of cell stretching and bridging between neighboring microspheres. Incorporation of silicon into apatite microspheres was found to accelerate the rate and number of apatite nucleation sites formed when subjected to physiological conditions improving the interface between the microsphere scaffolds and bone forming cells, facilitating better adhesion and proliferation.

Role of serum alkaline phosphatase as a potential biomarker of severity and prognosis in intracerebral hemorrhage.

OBJECTIVES: Alkaline phosphatase (ALP) catalyzes the hydrolysis of pyrophosphate and facilitates vascular calcification. We aimed at investigating serum ALP levels in intracerebral hemorrhage (ICH) patients and ascertaining its relationship to severity and prognosis. METHODS: Serum ALP levels from 148 patients and 148 healthy controls were detected. Glasgow coma scale (GCS) score and hematoma volume at admission were recorded to evaluate hemorrhagic severity. Modified Rankin Scale (mRS) score > 2 at 90 days after onset was judged as a poor prognosis. RESULTS: Serum ALP levels in patients with ICH were substantially elevated compared with healthy controls, and were significantly related to hematoma volume and GCS score. Serum ALP levels significantly distinguished ICH patients at risk for unfavorable prognosis. Serum ALP levels > 78.5 U/L in ICH patients may indicated a unfavorable prognosis with 69.1 % sensitivity and 83.6 % specificity, and served as an independent predictor for unfavorable prognosis. CONLUSIONS: Elevated serum ALP levels were intimately connected with increased severity and 90-day unfavorable prognosis in patients with ICH. Serum ALP could be a potential biomarker for severity and prognosis of ICH.

Temperature responses of leaf respiration in light and darkness are similar and modulated by leaf development.

Our ability to predict temperature responses of leaf respiration in light and darkness (RL and RDk ) is essential to models of global carbon dynamics. While many models rely on constant thermal sensitivity (characterized by Q10 ), uncertainty remains as to whether Q10 of RL and RDk are actually similar. We measured short-term temperature responses of RL and RDk in immature and mature leaves of two evergreen tree species, Castanopsis carlesii and Ormosia henry in an open field. RL was estimated by the Kok method, the Yin method and a newly developed Kok-iterCc method. When estimated by the Yin and Kok-iterCc methods, RL and RDk had similar Q10 (c. 2.5). The Kok method overestimated both Q10 and the light inhibition of respiration. RL /RDk was not affected by leaf temperature. Acclimation of respiration in summer was associated with a decline in basal respiration but not in Q10 in both species, which was related to changes in leaf nitrogen content between seasons. Q10 of RL and RDk in mature leaves were 40% higher than in immature leaves. Our results suggest similar Q10 values can be used to model RL and RDk while leaf development-associated changes in Q10 require special consideration in future respiration models.

Associations of body roundness index with cardiovascular and all-cause mortality: NHANES 2001-2018.

Body roundness index (BRI) was associated with cardiovascular diseases. But the relationship between BRI with cardiovascular disease (CVD) mortality and all-cause mortality remains largely unknown in hypertensive patients. This prospective cohort study included patients with hypertension who participated in the National Health and Nutrition Examination Survey (NHANES) from 2001 through 2018, and aimed to evaluate the association between BRI with CVD mortality and all-cause mortality. A total of 15570 patients were included. Over a median follow-up of 8.0 years (interquartile range, 4.3-12.6 years), 3445 individuals died, including 1166 CVD deaths. Weighted restricted cubic spline regression results showed a nonlinear association between BRI and CVD mortality and all-cause mortality (both P for nonlinear trend <0.001). The weighted multivariate Cox proportional hazards regression showed the hazard ratio (HRs) for CVD mortality were 0.93 (95% CI: 0.84-1.03, P = 0.160) in the low levels of BRI (≤5.9) and 1.11 (95% CI: 1.05-1.19, P < 0.001) in the high levels of BRI (>5.9). Similar associations were observed for all-cause mortality, the HRs were 0.91 (95% CI: 0.87-0.96, P < 0.001) in the low levels of BRI (≤6.3) and 1.09 (95% CI: 1.05-1.13, P < 0.001) in the high levels of BRI (>6.3). This cohort study supported that BRI was nonlinearly associated with CVD mortality and all-cause mortality among patients with hypertension. The thresholds of 5.9 and 6.3 for CVD mortality and all-cause mortality, respectively, may represent intervention targets for lowering the risk of premature death, but this needs to be confirmed in large clinical trials.